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<Journal>
				<PublisherName>University of Isfahan</PublisherName>
				<JournalTitle>Geography and Environmental Planning</JournalTitle>
				<Issn>2008-5362</Issn>
				<Volume>31</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2020</Year>
					<Month>05</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Trend analysis of snow accumulation season start in Iran using remote sensing data</ArticleTitle>
<VernacularTitle>Trend analysis of snow accumulation season start in Iran using remote sensing data</VernacularTitle>
			<FirstPage>1</FirstPage>
			<LastPage>14</LastPage>
			<ELocationID EIdType="pii">24911</ELocationID>
			
<ELocationID EIdType="doi">10.22108/gep.2020.120775.1249</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Seyed Abolfazl</FirstName>
					<LastName>Masoodian</LastName>
<Affiliation>Professor of Climatology, Department of Physical Geography, University of Isfahan, Isfahan, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Mohammad Sadegh</FirstName>
					<LastName>Keikhosravi Kiany</LastName>
<Affiliation>Postdoctoral Researcher in Climatology, Department of Physical Geography, University of Isfahan, Isfahan,</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2020</Year>
					<Month>01</Month>
					<Day>01</Day>
				</PubDate>
			</History>
		<Abstract>&lt;strong&gt;1. Introduction&lt;/strong&gt;:
By advances in remote sensing techniques, it has been possible to better monitor environmental phenomena. Satellite data with appropriate temporal and spatial coverage along with high spatial resolutions are valuable resources in environmental studies. During the past two decades, many studies have been conducted to evaluate the temporal variations of accumulation and melting as well as the seasonal characteristics of snow covers using remote sensing data. For instance, Hall et al. (2015) used Landsat satellite data from 1972 to 2013 to study changes in snowmelt time in the Fremont Lake Basin in the United States. The results have shown that snow melting time in this region begins earlier in the 2000s than in the 1972-1999 periods and that increasing nighttime temperature in spring and autumn resulted in earlier melting of snow cover. In another study, Bi et al. (2015) used MODIS data for the period 2003–2013 to investigate the time of beginning and end of snow cover in the northeast Tibetan Plateau. Their findings showed that although during the study period, the timing of snow accumulation and ablation varied, the spatial distribution of the number of snow-covered days has shown a stable behavior.
 
&lt;strong&gt;2. Methodology&lt;/strong&gt;
In the present study, in order to investigate the trend of changes at the beginning of the snow cover accumulation season in Iran, the version six of MODIS Terra (MOD10A1) and MODIS Aqua (MYD10A1) for the time span from 1379/7/1 to 1397/6/31 (1999 to 2007) was used. One of the natural barriers to monitoring snow cover is the cloud issue problem. Cloud contamination causes snow cover to hide beneath the satellite&#039;s field of view. Various techniques have been suggested by researchers to reduce cloudiness and better observation of snow cover. In the present study, three techniques including the combination of two satellite and temporal and spatial filtering were applied to the raw data. The application of these three techniques resulted in a significant reduction of the cloud cover effect on the data. After the preparation and construction of the snow cover dataset, the first day of the snow cover reported by the MODIS (based on the first day of October) was computed and that day was defined as the start of the snow cover season, this process was carried out for all the 7541502 pixels in the country. This process was repeated over 18 years of available data and finally, the slope of the regression line was calculated on more than seven million pixels.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;3. Discussion&lt;/strong&gt;
Calculations of the trend of spatial variations of the snow cover accumulation season showed that generally there was a significant increasing trend in the western parts of the country on the Zagros Mountains, it means that the first time that snow was accumulated during the snow cover season is advancing towards late fall and winter. In a clearer sense, it means that the first day of snow cover was occurring later in these areas. But in parts of central Zagros, the beginning of the snow cover season had a negative trend, meaning that the early days of the snow cover were occurring sooner than the long-term condition. The negative trend of the beginning of the snow cover accumulation season was also seen in the Alborz Mountains and the northwestern parts of the country. This negative trend appeared to be due to the earlier onset of autumn precipitation in the study period. Investigating temporal changes at the beginning of snow cover accumulation season in Iran, on each of the altitude belts in 50 meters, spatial steps showed that up to the altitude belt of 2750 meters, the beginning of snow accumulation season was advancing toward late fall and winter. However, from the altitudes of 2800 meters upwards, the onset of the snow cover season was turning backward. In a clearer sense, it was moving back toward the early autumn season.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;4. Conclusion&lt;/strong&gt;
The purpose of the present study was to investigate the temporal and spatial variations of the beginning of snow cover accumulation season in Iran. For this purpose, MODIS Terra and MODIS Aqua data were obtained at the spatial resolution of 500 × 500 meters for the time interval from 1379/7/1 to 1397/6/31 (1999 to 2007). After the construction and preparation of the snow cover database in Iran, the trend of changes at the beginning of the snow cover accumulation season was calculated temporally and spatially. The beginning of the snow cover accumulation season means the first day that a pixel was covered by snow based on the first day of October. For each hydrological year, the beginning of the snow cover season was calculated for each of the MODIS pixels and finally, the regression slope of changes was then computed. The findings showed that snow cover accumulation season was advancing towards winter on the western and northeast highlands of the country while snow cover accumulation season on the north and northwest of the country was forwarding back to fall. The calculations also showed that up to 2750 meters the onset of the snow cover season was moving toward winter, while from the height of 2800 meters, the onset of snow cover season was forwarding back to the fall season.</Abstract>
			<OtherAbstract Language="FA">&lt;strong&gt;1. Introduction&lt;/strong&gt;:
By advances in remote sensing techniques, it has been possible to better monitor environmental phenomena. Satellite data with appropriate temporal and spatial coverage along with high spatial resolutions are valuable resources in environmental studies. During the past two decades, many studies have been conducted to evaluate the temporal variations of accumulation and melting as well as the seasonal characteristics of snow covers using remote sensing data. For instance, Hall et al. (2015) used Landsat satellite data from 1972 to 2013 to study changes in snowmelt time in the Fremont Lake Basin in the United States. The results have shown that snow melting time in this region begins earlier in the 2000s than in the 1972-1999 periods and that increasing nighttime temperature in spring and autumn resulted in earlier melting of snow cover. In another study, Bi et al. (2015) used MODIS data for the period 2003–2013 to investigate the time of beginning and end of snow cover in the northeast Tibetan Plateau. Their findings showed that although during the study period, the timing of snow accumulation and ablation varied, the spatial distribution of the number of snow-covered days has shown a stable behavior.
 
&lt;strong&gt;2. Methodology&lt;/strong&gt;
In the present study, in order to investigate the trend of changes at the beginning of the snow cover accumulation season in Iran, the version six of MODIS Terra (MOD10A1) and MODIS Aqua (MYD10A1) for the time span from 1379/7/1 to 1397/6/31 (1999 to 2007) was used. One of the natural barriers to monitoring snow cover is the cloud issue problem. Cloud contamination causes snow cover to hide beneath the satellite&#039;s field of view. Various techniques have been suggested by researchers to reduce cloudiness and better observation of snow cover. In the present study, three techniques including the combination of two satellite and temporal and spatial filtering were applied to the raw data. The application of these three techniques resulted in a significant reduction of the cloud cover effect on the data. After the preparation and construction of the snow cover dataset, the first day of the snow cover reported by the MODIS (based on the first day of October) was computed and that day was defined as the start of the snow cover season, this process was carried out for all the 7541502 pixels in the country. This process was repeated over 18 years of available data and finally, the slope of the regression line was calculated on more than seven million pixels.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;3. Discussion&lt;/strong&gt;
Calculations of the trend of spatial variations of the snow cover accumulation season showed that generally there was a significant increasing trend in the western parts of the country on the Zagros Mountains, it means that the first time that snow was accumulated during the snow cover season is advancing towards late fall and winter. In a clearer sense, it means that the first day of snow cover was occurring later in these areas. But in parts of central Zagros, the beginning of the snow cover season had a negative trend, meaning that the early days of the snow cover were occurring sooner than the long-term condition. The negative trend of the beginning of the snow cover accumulation season was also seen in the Alborz Mountains and the northwestern parts of the country. This negative trend appeared to be due to the earlier onset of autumn precipitation in the study period. Investigating temporal changes at the beginning of snow cover accumulation season in Iran, on each of the altitude belts in 50 meters, spatial steps showed that up to the altitude belt of 2750 meters, the beginning of snow accumulation season was advancing toward late fall and winter. However, from the altitudes of 2800 meters upwards, the onset of the snow cover season was turning backward. In a clearer sense, it was moving back toward the early autumn season.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;4. Conclusion&lt;/strong&gt;
The purpose of the present study was to investigate the temporal and spatial variations of the beginning of snow cover accumulation season in Iran. For this purpose, MODIS Terra and MODIS Aqua data were obtained at the spatial resolution of 500 × 500 meters for the time interval from 1379/7/1 to 1397/6/31 (1999 to 2007). After the construction and preparation of the snow cover database in Iran, the trend of changes at the beginning of the snow cover accumulation season was calculated temporally and spatially. The beginning of the snow cover accumulation season means the first day that a pixel was covered by snow based on the first day of October. For each hydrological year, the beginning of the snow cover season was calculated for each of the MODIS pixels and finally, the regression slope of changes was then computed. The findings showed that snow cover accumulation season was advancing towards winter on the western and northeast highlands of the country while snow cover accumulation season on the north and northwest of the country was forwarding back to fall. The calculations also showed that up to 2750 meters the onset of the snow cover season was moving toward winter, while from the height of 2800 meters, the onset of snow cover season was forwarding back to the fall season.</OtherAbstract>
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<Article>
<Journal>
				<PublisherName>University of Isfahan</PublisherName>
				<JournalTitle>Geography and Environmental Planning</JournalTitle>
				<Issn>2008-5362</Issn>
				<Volume>31</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2020</Year>
					<Month>05</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Evaluation of Heavy Metal Contamination in Soil Samples around the Lead-Zinc Mine of Kushk, Bafq, using Pollution Indicators and Principal Component Analysis</ArticleTitle>
<VernacularTitle>Evaluation of Heavy Metal Contamination in Soil Samples around the Lead-Zinc Mine of Kushk, Bafq, using Pollution Indicators and Principal Component Analysis</VernacularTitle>
			<FirstPage>15</FirstPage>
			<LastPage>34</LastPage>
			<ELocationID EIdType="pii">24804</ELocationID>
			
<ELocationID EIdType="doi">10.22108/gep.2020.121263.1260</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Zahra</FirstName>
					<LastName>Sohrabizadeh</LastName>
<Affiliation>PhD Candidate of Desertification, Department of Arid and Desert Management, Faculty of Natural Resources, Yazd University, Yazd, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Hamid</FirstName>
					<LastName>Sodaiezadeh</LastName>
<Affiliation>Associate Professor, Department of Arid and Desert Management, Faculty of Natural Resources, Yazd University, Yazd, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Mohammad Ali</FirstName>
					<LastName>Hakimizadeh</LastName>
<Affiliation>Associate Professor, Department of Arid and Desert Management, Faculty of Natural Resources, Yazd University, Yazd, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Rouhollah</FirstName>
					<LastName>Taghizadeh Mehrjardi</LastName>
<Affiliation>Assistant Professor, Department of Desert Management, Ardakan University, Yazd, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Mohammad Javad</FirstName>
					<LastName>Ghanei Bafaqi</LastName>
<Affiliation>Assistant Professor, Department of Desert Management, Ardakan University, Yazd, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2020</Year>
					<Month>01</Month>
					<Day>23</Day>
				</PubDate>
			</History>
		<Abstract>&lt;strong&gt;Abstract&lt;/strong&gt;
Soil is a major component of the biosphere that is exposed to pollutants such as heavy metals. Soil pollution by heavy metals is an important issue and heavy metals originate from the two main sources of natural resources and human inputs including mining, various industries, road transport, mineral and chemical fertilizers for agriculture, sewage sludge, and industrial wastes. Mining and mineral processing activities are the most important sources of potentially toxic elements entering the environment and pollute various parts of the environment (including water, soil, air, and vegetation sources). Along with population growth and industrial development, mining activities for metal extraction have also expanded and as a result, the environment around the mines has been more and more affected by metal pollutants.
Kushk Pb-Zn mine has been manually worked since 1940 and mechanized since 1964 and is located in a condensing and processing plant next to the mine. Mining waste is located on the margin of the mine deposited and can be spread downstream by wind or water. Because so far few studies have been conducted on the level and extent of pollution of soil sources around the lead and zinc mine, so the present study aims to evaluate the concentration of heavy metals (Cd, Mn, Cu, Fe, Pb, and Zn) and the extent of pollution and their environmental hazards were assessed in the study area.
Sampling was done in November 2018 and 102 soil samples were collected from the Kushk mine area and its surroundings. Sampling has been done inside and outside the mine up to a radius of about eight kilometers. The location of the samples was determined by the Latin square method. The Latin Square Method is an almost modern sampling method that is stratified or layered. Their concentration was measured using a German model atomic absorption spectrometer (Jena330). After reading the concentration by the atomic absorption spectrometer, the obtained data were analyzed by Excel and IBM SPSS Statistic 22 software. Also, to show the spatial distribution of pollution of different elements considered in the research, the IDW method was used to prepare the maps using Arc GIS 10.3 software. Also, soil pollution was assessed using the pollution factor (CF), enrichment factor (EF), and land accumulation index (Igeo).
This study evaluated six heavy metals in 102 soil samples (Cd, Mn, Cu, Fe, Pb, and Zn) conducted in the Kushk Pb-Zn mine in Bafq. The concentration of the studied heavy metals was in the order of Zn &gt; Pb &gt; Mn &gt; Fe &gt; Cd &gt; Cu and only three elements of cadmium, lead, and zinc were above the alert threshold. The highest amount of elements was present in the southern part of the mine and near the mineral tailings and downstream of the road and sometimes on the road and machine traffic. The results showed the distribution of lead and zinc elements in the margins of the mine, especially in the margins of mineral tailings and downstream of the road. The reasons for this can be considered as the effect of wind and the existence of seasonal waterways in the transfer of these elements due to human activities such as mining and transportation to the mentioned points. Lead and zinc are gallons, so the amount of lead in the soil can indicate the geological origin of the contamination. The concentrations of copper, iron, and manganese for the soil in the study area were below the warning threshold. The results of the pollution indices used (except the Nemro index) indicated that the area was either not polluted or had little pollution. The Nemro index indicated that all elements (except copper) were severely contaminated. The lead was the highest element in all indicators, which can be said to be due to the type of parent rock and the geology of the region. On the other hand, the results of multivariate statistical analysis of heavy metals showed that vehicle and geological activities were the most important sources of zinc, lead, and cadmium contamination. Iron, copper, and manganese were mainly controlled by geological sources and parent materials, and manganese concentrations can be affected by fertilizers and agricultural soils. Due to the fact that the soil of the study area was contaminated with other heavy metals in addition to lead and zinc, so the need for more research in the area to evaluate strategic plans for soil resource management is necessary.</Abstract>
			<OtherAbstract Language="FA">&lt;strong&gt;Abstract&lt;/strong&gt;
Soil is a major component of the biosphere that is exposed to pollutants such as heavy metals. Soil pollution by heavy metals is an important issue and heavy metals originate from the two main sources of natural resources and human inputs including mining, various industries, road transport, mineral and chemical fertilizers for agriculture, sewage sludge, and industrial wastes. Mining and mineral processing activities are the most important sources of potentially toxic elements entering the environment and pollute various parts of the environment (including water, soil, air, and vegetation sources). Along with population growth and industrial development, mining activities for metal extraction have also expanded and as a result, the environment around the mines has been more and more affected by metal pollutants.
Kushk Pb-Zn mine has been manually worked since 1940 and mechanized since 1964 and is located in a condensing and processing plant next to the mine. Mining waste is located on the margin of the mine deposited and can be spread downstream by wind or water. Because so far few studies have been conducted on the level and extent of pollution of soil sources around the lead and zinc mine, so the present study aims to evaluate the concentration of heavy metals (Cd, Mn, Cu, Fe, Pb, and Zn) and the extent of pollution and their environmental hazards were assessed in the study area.
Sampling was done in November 2018 and 102 soil samples were collected from the Kushk mine area and its surroundings. Sampling has been done inside and outside the mine up to a radius of about eight kilometers. The location of the samples was determined by the Latin square method. The Latin Square Method is an almost modern sampling method that is stratified or layered. Their concentration was measured using a German model atomic absorption spectrometer (Jena330). After reading the concentration by the atomic absorption spectrometer, the obtained data were analyzed by Excel and IBM SPSS Statistic 22 software. Also, to show the spatial distribution of pollution of different elements considered in the research, the IDW method was used to prepare the maps using Arc GIS 10.3 software. Also, soil pollution was assessed using the pollution factor (CF), enrichment factor (EF), and land accumulation index (Igeo).
This study evaluated six heavy metals in 102 soil samples (Cd, Mn, Cu, Fe, Pb, and Zn) conducted in the Kushk Pb-Zn mine in Bafq. The concentration of the studied heavy metals was in the order of Zn &gt; Pb &gt; Mn &gt; Fe &gt; Cd &gt; Cu and only three elements of cadmium, lead, and zinc were above the alert threshold. The highest amount of elements was present in the southern part of the mine and near the mineral tailings and downstream of the road and sometimes on the road and machine traffic. The results showed the distribution of lead and zinc elements in the margins of the mine, especially in the margins of mineral tailings and downstream of the road. The reasons for this can be considered as the effect of wind and the existence of seasonal waterways in the transfer of these elements due to human activities such as mining and transportation to the mentioned points. Lead and zinc are gallons, so the amount of lead in the soil can indicate the geological origin of the contamination. The concentrations of copper, iron, and manganese for the soil in the study area were below the warning threshold. The results of the pollution indices used (except the Nemro index) indicated that the area was either not polluted or had little pollution. The Nemro index indicated that all elements (except copper) were severely contaminated. The lead was the highest element in all indicators, which can be said to be due to the type of parent rock and the geology of the region. On the other hand, the results of multivariate statistical analysis of heavy metals showed that vehicle and geological activities were the most important sources of zinc, lead, and cadmium contamination. Iron, copper, and manganese were mainly controlled by geological sources and parent materials, and manganese concentrations can be affected by fertilizers and agricultural soils. Due to the fact that the soil of the study area was contaminated with other heavy metals in addition to lead and zinc, so the need for more research in the area to evaluate strategic plans for soil resource management is necessary.</OtherAbstract>
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			<Param Name="value">Environmental Standard</Param>
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			<Param Name="value">Soil pollution</Param>
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			<Param Name="value">Cluster analysis</Param>
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			<Param Name="value">Human Activity</Param>
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<Article>
<Journal>
				<PublisherName>University of Isfahan</PublisherName>
				<JournalTitle>Geography and Environmental Planning</JournalTitle>
				<Issn>2008-5362</Issn>
				<Volume>31</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2020</Year>
					<Month>05</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Analysis of Changes in the Scale of the Watershed Based on the Metrics and Spatial Patterns of the Landscape (Case Study: Anzali Watershed)</ArticleTitle>
<VernacularTitle>Analysis of Changes in the Scale of the Watershed Based on the Metrics and Spatial Patterns of the Landscape (Case Study: Anzali Watershed)</VernacularTitle>
			<FirstPage>35</FirstPage>
			<LastPage>52</LastPage>
			<ELocationID EIdType="pii">24739</ELocationID>
			
<ELocationID EIdType="doi">10.22108/gep.2020.120800.1245</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Mohammad</FirstName>
					<LastName>Panahandeh</LastName>
<Affiliation>Assistant Professor, Academic Center for Education, Culture, and Research (ACECR), Environmental Research Institute, Rasht, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Sadaf</FirstName>
					<LastName>Feyzi</LastName>
<Affiliation>Research Expert, Academic Center for Education, Culture, and Research (ACECR), Environmental Research Institute, Rasht, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2019</Year>
					<Month>12</Month>
					<Day>29</Day>
				</PubDate>
			</History>
		<Abstract>&lt;strong&gt;Extended abstract&lt;/strong&gt; &lt;br /&gt;&lt;strong&gt;Introduction:&lt;/strong&gt; Human beings have extremely changed the shape, pattern, and function of nearly all landscapes. The cumulative effects of human activities on the environment have been the impetus for extensive research aimed at identifying guiding metrics to assess the quality of the environment in terms of planning, monitoring, and resource management purposes. In order to control and restrict human impacts scientists, planners, and natural resource managers are looking for holistic approaches to interpret the relation between land use and the quality of the environment. In this regard habitat fragmentation, alteration of the hydrologic system of the watershed, and water quality have attracted the most attention. Landscapes have been studied at different scales and various metrics have been introduced to measure the quality of the environment. In the past years, ecological recognition has introduced a big picture based on the main pattern and landscape ecology principles. The foundation of this big picture is based on the idea that there are indispensables patterns in the landscapes that if they are maintained the important functions are protected. In this regard, some of the ecosystem&#039;s attributes are not saved and important natural assets will be protected. A landscape is a mosaic including a mix of ecosystems and land uses that repeat in a similar form. The mosaic pattern of landscape or spatial arrangement of landscape elements determines the movement of material, energy, organisms, and humans between local ecosystems. Also the movement of animals, water, nutrient, and human determine the arrangement of mosaic patterns. Landscape ecologists identified five main ways in which human alter landscape spatially: perforation, dissection, fragmentation, shrinkage, and attrition. These changes result in different spatial patterning of landscape elements that can alter the ecological process and population distribution of plants and animals. So, the purpose of this study was to investigate the landscape pattern change of Anzali watershed in the north of Iran. &lt;br /&gt;&lt;strong&gt; &lt;/strong&gt; &lt;br /&gt;&lt;strong&gt;Methodology:&lt;/strong&gt; &lt;br /&gt;In this study, Landsat satellite imagery for 1994, 2008, and 2018 was used to determine land cover/land use using remote sensing. For landscape analysis, metrics of a number of patches (NP), class area (CA), patch density (PD), percentage of land (PLAND), and large patch index (LPI) were used. Based on how to change landscape metrics, landscape pattern change was examined through patterns of attrition, aggregation, creation, and dissection. &lt;br /&gt;&lt;strong&gt; &lt;/strong&gt; &lt;br /&gt;&lt;strong&gt;Discussion:&lt;/strong&gt; &lt;br /&gt;Findings indicated a 10 percent decrease in forest cover and a 5.8 percent increase in agricultural land use. Also, a large patch index decreased for forest cover. According to landscape pattern change, Attrition was a dominated pattern that occurred mainly in forest cover. The second pattern was Creation that occurred for agriculture land use. Findings indicated decreasing in Anzali watershed integrity and connectivity of the forest patches as the most important patches in the watershed. Forest patches decreased in the area through attrition, aggregation, and dissection. In contrast, agriculture land use developed through aggregation and direct convert of isolated natural patches. &lt;br /&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt; &lt;br /&gt;The pattern of land cover changes in the Anzali watershed indicated a shift in the balance towards the development of disturbed land cover, especially agriculture. However, forest cover as the most important land cover in the area has not been fragmented yet (simultaneous increase in the number of patches and drastic reduction of the area). The reason for this is based on the largest patch index of forest class. One of the forest patches alone, covering an area of 2071/34 hectares in 2018. Patterns of attrition, aggregation, creation, and dissection have provided the basis for the occurrence of disruption in forest cover. In this case, forest cover loses many of its capabilities, especially habitat services, water conservation, and decreasing soil erosion.</Abstract>
			<OtherAbstract Language="FA">&lt;strong&gt;Extended abstract&lt;/strong&gt; &lt;br /&gt;&lt;strong&gt;Introduction:&lt;/strong&gt; Human beings have extremely changed the shape, pattern, and function of nearly all landscapes. The cumulative effects of human activities on the environment have been the impetus for extensive research aimed at identifying guiding metrics to assess the quality of the environment in terms of planning, monitoring, and resource management purposes. In order to control and restrict human impacts scientists, planners, and natural resource managers are looking for holistic approaches to interpret the relation between land use and the quality of the environment. In this regard habitat fragmentation, alteration of the hydrologic system of the watershed, and water quality have attracted the most attention. Landscapes have been studied at different scales and various metrics have been introduced to measure the quality of the environment. In the past years, ecological recognition has introduced a big picture based on the main pattern and landscape ecology principles. The foundation of this big picture is based on the idea that there are indispensables patterns in the landscapes that if they are maintained the important functions are protected. In this regard, some of the ecosystem&#039;s attributes are not saved and important natural assets will be protected. A landscape is a mosaic including a mix of ecosystems and land uses that repeat in a similar form. The mosaic pattern of landscape or spatial arrangement of landscape elements determines the movement of material, energy, organisms, and humans between local ecosystems. Also the movement of animals, water, nutrient, and human determine the arrangement of mosaic patterns. Landscape ecologists identified five main ways in which human alter landscape spatially: perforation, dissection, fragmentation, shrinkage, and attrition. These changes result in different spatial patterning of landscape elements that can alter the ecological process and population distribution of plants and animals. So, the purpose of this study was to investigate the landscape pattern change of Anzali watershed in the north of Iran. &lt;br /&gt;&lt;strong&gt; &lt;/strong&gt; &lt;br /&gt;&lt;strong&gt;Methodology:&lt;/strong&gt; &lt;br /&gt;In this study, Landsat satellite imagery for 1994, 2008, and 2018 was used to determine land cover/land use using remote sensing. For landscape analysis, metrics of a number of patches (NP), class area (CA), patch density (PD), percentage of land (PLAND), and large patch index (LPI) were used. Based on how to change landscape metrics, landscape pattern change was examined through patterns of attrition, aggregation, creation, and dissection. &lt;br /&gt;&lt;strong&gt; &lt;/strong&gt; &lt;br /&gt;&lt;strong&gt;Discussion:&lt;/strong&gt; &lt;br /&gt;Findings indicated a 10 percent decrease in forest cover and a 5.8 percent increase in agricultural land use. Also, a large patch index decreased for forest cover. According to landscape pattern change, Attrition was a dominated pattern that occurred mainly in forest cover. The second pattern was Creation that occurred for agriculture land use. Findings indicated decreasing in Anzali watershed integrity and connectivity of the forest patches as the most important patches in the watershed. Forest patches decreased in the area through attrition, aggregation, and dissection. In contrast, agriculture land use developed through aggregation and direct convert of isolated natural patches. &lt;br /&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt; &lt;br /&gt;The pattern of land cover changes in the Anzali watershed indicated a shift in the balance towards the development of disturbed land cover, especially agriculture. However, forest cover as the most important land cover in the area has not been fragmented yet (simultaneous increase in the number of patches and drastic reduction of the area). The reason for this is based on the largest patch index of forest class. One of the forest patches alone, covering an area of 2071/34 hectares in 2018. Patterns of attrition, aggregation, creation, and dissection have provided the basis for the occurrence of disruption in forest cover. In this case, forest cover loses many of its capabilities, especially habitat services, water conservation, and decreasing soil erosion.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Metrics</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Attrition</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Aggregation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Dissection</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Land cover</Param>
			</Object>
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			<Param Name="value">Land Use</Param>
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</Article>

<Article>
<Journal>
				<PublisherName>University of Isfahan</PublisherName>
				<JournalTitle>Geography and Environmental Planning</JournalTitle>
				<Issn>2008-5362</Issn>
				<Volume>31</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2020</Year>
					<Month>05</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Evaluation of Land Suitability for Horticultural Use
Case Study: Saman County, Chaharmahal and Bakhtiari Province</ArticleTitle>
<VernacularTitle>Evaluation of Land Suitability for Horticultural Use
Case Study: Saman County, Chaharmahal and Bakhtiari Province</VernacularTitle>
			<FirstPage>53</FirstPage>
			<LastPage>72</LastPage>
			<ELocationID EIdType="pii">25086</ELocationID>
			
<ELocationID EIdType="doi">10.22108/gep.2020.119932.1224</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Mohsen</FirstName>
					<LastName>Bagheri Bodaghabadi</LastName>
<Affiliation>Soil and Water Research Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran 
 (*Corresponding Author Email: m.baghery@areeo.ac.ir)</Affiliation>

</Author>
<Author>
					<FirstName>Fatemeh</FirstName>
					<LastName>Ebrahimi Meiman</LastName>
<Affiliation>Soil and Water Research Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Abdolmohammad</FirstName>
					<LastName>Mehnatkesh</LastName>
<Affiliation>Soil and Water Research Department, Chaharmahal and Bakhtiari Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Shahrekord, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Seyyed Asghar</FirstName>
					<LastName>Mousavi</LastName>
<Affiliation>Crop and Horticultural Science Research Department, Chaharmahal and Bakhtiari Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Shahrekord, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2019</Year>
					<Month>11</Month>
					<Day>05</Day>
				</PubDate>
			</History>
		<Abstract>&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Introduction&lt;/strong&gt;
Agriculture is the main source of national income and food for all developing countries, but the main problem facing many managers and farmers is when and where they can cultivate. Horticulture is one of the agricultural activities, the maintenance and development of which requires sustainable economic, social, cultural, ecological and institutional infrastructure. It also requires the participation and comprehensive planning at a local to national scale. The first step in achieving sustainable development, especially in the agricultural activities and the subsequent orchard farming, is to recognize the ecological potential and the land capability in each region. In this regard, the knowledge of land evaluation plays a decisive role in determining the land suitability or evaluating the ecological potential of each region for the intended uses, including the development of gardens. Numerous studies have been conducted to evaluate the land suitability for crop cultivation, including horticultural and agricultural products. Since orchards require more investment and time than crop farming, the importance of basic studies and research for the orchards will be much greater than that the crop; because if an unsuitable land is used for orchard establishment, after it, for several years, more important than wasting the money paid is the loss of time, which is not compensable. But, only one crop season is lost for crop farming.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Materials and Methods&lt;/strong&gt;
In Chaharmahal and Bakhtiari province, the development of the orchard is very important for the people as well as the relevant officials. Therefore, the selection of the suitable location for the orchard farming is a very important issue. For this purpose, this research was conducted with the aim of achieving the best and most sustainable use of land in Saman County, which has the first rank in the province with about 13,000 hectares of gardens. Due to the climate of this area, the orchard products for cold regions, such as apricots, almonds, apples, peaches and grapes was selected and the possibility of sustainable development of these orchards was studied using the land suitability evaluation based on the FAO standard method. For this purpose, the land characteristics (LC) related to the intended crops, which mostly included the climatic characteristics and the characteristics of the soil and the land, were first collected and classified. Then, the requirements of the these crops or products were determined and at the end, the characteristics or qualities collected were compared and evaluated with the requirement tables of the selected crops. Each land feature was then given a class or numerical value, which combined two important indicators, including the climate index and the land index. In this study, the process of land suitability assessment was performed with a size approach and numerical (parametric) method and then land fit maps of the desired products were prepared.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Results and Discussion &lt;/strong&gt;
Table 1 shows the class and subclass of land suitability for apricots. As can be seen, 42530.7 hectares or 86.87% of the whole land are in the suitable order. The subclasses include climatic (c) and soil physical (s) limitations. The most important soil physical limiting factors are soil depth, lime percentage and gravel percentage. Also, the land with an area of ​​6429.7 hectares or 13.13% of the land is in the not-suitable order, which due to the limitations of the gravel percentage and soil depth is in the permanently unsuitable class or N2s class.
The results of land suitability assessment for peaches, apples, grapes, and almonds are shown in tables 2 and 3. The findings showed that according to climatic and soil characteristics, different regions had different degrees of proportionality or ecological potential, so that the study area had S3 and N classes in 86.87% and 13.33% of the area, respectively.
For grapes and almonds, the land suitability classes were S2, S3 and N classes, in 21.90%, 65.57% and 90% of the area, respectively (Table 3). The most important limitations were the soil depth, gravel, slope, and climatic constraints. According to such findings, planners and decision makers can plan and choose the best options to take into account both the product profitability and sustainability. Of course, in addition to ecological requirements, it is recommended to study other requirements such as social characteristics, economic conditions, cultural acceptance, and the current situation of orchards to complete the process of sustainable development for horticulture.
Table 1. Land Suitability Classification for Apricots





Percent (%)


Area (Ha)


Sub Class


Percent (%)


Area (Ha)


Class


Percent (%)


Area (Ha)


Order




13.66


6687.1


S2cs


13.66


6687.1


S2


86.87


42530.7


Suitable (S)




73.21


35843.6


S3s


73.21


35843.6


S3




13.13


6429.7


N


13.13


6429.7


N


13.13


6429.7


Not Suitable (N)




100


48960.4


Total



 
 
 
 
 
 
 
 
 
 
 




&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Table 2. Land Suitability Classification for Peaches and Apples&lt;/strong&gt;





Percent (%)


Area (Ha)


Sub Class


Percent (%)


Area (Ha)


Class


Percent (%)


Area (Ha)


Order




86.87


42530.7


S3s


86.87


42530.7


S3


86.87


42530.7


Suitable (S)




13.13


6429.7


N


13.13


6429.7


N


13.13


6429.7


Not Suitable (N)




100


48960.4


Total



 
 
 
 
 
 
 
 
 
 
 




&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Table 3. Land Suitability Classification for Grapes&lt;/strong&gt;&lt;strong&gt; and Almonds&lt;/strong&gt;





Percent (%)


Area (Ha)


Sub Class


Percent (%)


Area (Ha)


Class


Percent (%)


Area (Ha)


Order




21.90


10723.03


S2cs


21.90


10733.03


S2


87.47


42830.34


Suitable (S)




65.57


32107.31


S3s


65.57


32107.31


S3




12.52


6131.01


N


12.52


6131.01


N


12.52


6131.01


Not Suitable (N)




100


48960.4


Total</Abstract>
			<OtherAbstract Language="FA">&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Introduction&lt;/strong&gt;
Agriculture is the main source of national income and food for all developing countries, but the main problem facing many managers and farmers is when and where they can cultivate. Horticulture is one of the agricultural activities, the maintenance and development of which requires sustainable economic, social, cultural, ecological and institutional infrastructure. It also requires the participation and comprehensive planning at a local to national scale. The first step in achieving sustainable development, especially in the agricultural activities and the subsequent orchard farming, is to recognize the ecological potential and the land capability in each region. In this regard, the knowledge of land evaluation plays a decisive role in determining the land suitability or evaluating the ecological potential of each region for the intended uses, including the development of gardens. Numerous studies have been conducted to evaluate the land suitability for crop cultivation, including horticultural and agricultural products. Since orchards require more investment and time than crop farming, the importance of basic studies and research for the orchards will be much greater than that the crop; because if an unsuitable land is used for orchard establishment, after it, for several years, more important than wasting the money paid is the loss of time, which is not compensable. But, only one crop season is lost for crop farming.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Materials and Methods&lt;/strong&gt;
In Chaharmahal and Bakhtiari province, the development of the orchard is very important for the people as well as the relevant officials. Therefore, the selection of the suitable location for the orchard farming is a very important issue. For this purpose, this research was conducted with the aim of achieving the best and most sustainable use of land in Saman County, which has the first rank in the province with about 13,000 hectares of gardens. Due to the climate of this area, the orchard products for cold regions, such as apricots, almonds, apples, peaches and grapes was selected and the possibility of sustainable development of these orchards was studied using the land suitability evaluation based on the FAO standard method. For this purpose, the land characteristics (LC) related to the intended crops, which mostly included the climatic characteristics and the characteristics of the soil and the land, were first collected and classified. Then, the requirements of the these crops or products were determined and at the end, the characteristics or qualities collected were compared and evaluated with the requirement tables of the selected crops. Each land feature was then given a class or numerical value, which combined two important indicators, including the climate index and the land index. In this study, the process of land suitability assessment was performed with a size approach and numerical (parametric) method and then land fit maps of the desired products were prepared.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Results and Discussion &lt;/strong&gt;
Table 1 shows the class and subclass of land suitability for apricots. As can be seen, 42530.7 hectares or 86.87% of the whole land are in the suitable order. The subclasses include climatic (c) and soil physical (s) limitations. The most important soil physical limiting factors are soil depth, lime percentage and gravel percentage. Also, the land with an area of ​​6429.7 hectares or 13.13% of the land is in the not-suitable order, which due to the limitations of the gravel percentage and soil depth is in the permanently unsuitable class or N2s class.
The results of land suitability assessment for peaches, apples, grapes, and almonds are shown in tables 2 and 3. The findings showed that according to climatic and soil characteristics, different regions had different degrees of proportionality or ecological potential, so that the study area had S3 and N classes in 86.87% and 13.33% of the area, respectively.
For grapes and almonds, the land suitability classes were S2, S3 and N classes, in 21.90%, 65.57% and 90% of the area, respectively (Table 3). The most important limitations were the soil depth, gravel, slope, and climatic constraints. According to such findings, planners and decision makers can plan and choose the best options to take into account both the product profitability and sustainability. Of course, in addition to ecological requirements, it is recommended to study other requirements such as social characteristics, economic conditions, cultural acceptance, and the current situation of orchards to complete the process of sustainable development for horticulture.
Table 1. Land Suitability Classification for Apricots





Percent (%)


Area (Ha)


Sub Class


Percent (%)


Area (Ha)


Class


Percent (%)


Area (Ha)


Order




13.66


6687.1


S2cs


13.66


6687.1


S2


86.87


42530.7


Suitable (S)




73.21


35843.6


S3s


73.21


35843.6


S3




13.13


6429.7


N


13.13


6429.7


N


13.13


6429.7


Not Suitable (N)




100


48960.4


Total



 
 
 
 
 
 
 
 
 
 
 




&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Table 2. Land Suitability Classification for Peaches and Apples&lt;/strong&gt;





Percent (%)


Area (Ha)


Sub Class


Percent (%)


Area (Ha)


Class


Percent (%)


Area (Ha)


Order




86.87


42530.7


S3s


86.87


42530.7


S3


86.87


42530.7


Suitable (S)




13.13


6429.7


N


13.13


6429.7


N


13.13


6429.7


Not Suitable (N)




100


48960.4


Total



 
 
 
 
 
 
 
 
 
 
 




&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Table 3. Land Suitability Classification for Grapes&lt;/strong&gt;&lt;strong&gt; and Almonds&lt;/strong&gt;





Percent (%)


Area (Ha)


Sub Class


Percent (%)


Area (Ha)


Class


Percent (%)


Area (Ha)


Order




21.90


10723.03


S2cs


21.90


10733.03


S2


87.47


42830.34


Suitable (S)




65.57


32107.31


S3s


65.57


32107.31


S3




12.52


6131.01


N


12.52


6131.01


N


12.52


6131.01


Not Suitable (N)




100


48960.4


Total</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">land use planning</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Ecological assessment</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Sustainable Development</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Agriculture</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://gep.ui.ac.ir/article_25086_0a6e0132002a2544a5419d4e77681a73.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>University of Isfahan</PublisherName>
				<JournalTitle>Geography and Environmental Planning</JournalTitle>
				<Issn>2008-5362</Issn>
				<Volume>31</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2020</Year>
					<Month>05</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Evaluation of Sentinel-2 and Landsat-8 Satellite Images Capability and Evaluation of Image Fusion Capability in Seasonal Zoning of NSFWQI and IRWQIsc Qualitative Indices in Surface Water
(Case Study: Karoun River)</ArticleTitle>
<VernacularTitle>Evaluation of Sentinel-2 and Landsat-8 Satellite Images Capability and Evaluation of Image Fusion Capability in Seasonal Zoning of NSFWQI and IRWQIsc Qualitative Indices in Surface Water
(Case Study: Karoun River)</VernacularTitle>
			<FirstPage>73</FirstPage>
			<LastPage>102</LastPage>
			<ELocationID EIdType="pii">25095</ELocationID>
			
<ELocationID EIdType="doi">10.22108/gep.2020.123228.1309</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Kazem</FirstName>
					<LastName>Rangzan</LastName>
<Affiliation>Associate Professor of Department of Remote Sensing and GIS, Earth Sciences Faculty, Shahid Chamran University of Ahvaz, Ahvaz, Iran (*Corresponding Author Email: kazemrangzan@scu.ac.ir)</Affiliation>

</Author>
<Author>
					<FirstName>Mostafa</FirstName>
					<LastName>Kabolizadeh</LastName>
<Affiliation>Assistant Professor of Department of Remote Sensing and GIS, Earth Sciences Faculty, Shahid Chamran University of Ahvaz, Ahvaz,Iran</Affiliation>

</Author>
<Author>
					<FirstName>Danya</FirstName>
					<LastName>Karimi</LastName>
<Affiliation>PhD Candidate of Remote Sensing and GIS, Earth Sciences Faculty, Shahid Chamran University of Ahvaz, Ahvaz, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2020</Year>
					<Month>05</Month>
					<Day>26</Day>
				</PubDate>
			</History>
		<Abstract>&lt;strong&gt;Extended Abstract&lt;/strong&gt;
&lt;strong&gt;Introduction&lt;/strong&gt;
Given the importance of surface water for drinking, agriculture, and industry, the protection of these resources against pollution is of great importance for national and regional health.
The integration of satellite imagery to produce data with a higher information level is called image fusion. Fusion methods are generally divided into three categories: pixel-based methods, feature-based methods, and decision-based methods.
The main objective of this research is to optimize seasonal zoning of the water quality indices of Karoun River based on two indices of NSFWQI (National Health Foundation Water Quality Index) and IRWQIsc (Iran Surface Water Quality Index for Conventional Pollutants) and therefore, the fusion of Sentinel-2 and Landsat 8 images will be evaluated. It is noteworthy that based on our knowledge the evaluation of image fusion methods in the field of qualitative indices zoning has not been conducted yet.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Materials and Methods&lt;/strong&gt;
&lt;strong&gt;Measured Quality Parameters&lt;/strong&gt;
Seven sampling stations were selected for seasonal measurement of water quality parameters along a part of the Karoun River in 2018. The measured qualitative parameters included chemical oxygen demand, biological oxygen demand, dissolved oxygen, electrical conductivity, fecal coliform, PH, nitrate, phosphate, total hardness, and turbidity.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;NSFWQI&lt;/strong&gt;
NSFWQI was introduced by the US National Health Organization in 1970. In this index, several questionnaires were filled out by experts in the United States, which are the basis for adjusting this index. Based on the answers, a curve was plotted for each parameter to determine the sub-indices of each parameter.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;IRWQIsc&lt;/strong&gt;
To evaluate the quality of rivers and compare their pollution rates in Iran concerning natural conditions and water resources problems, an index (IRWQIsc) was introduced to provide a good perspective about the quality status of water resources in Iran.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Utilized satellite imageries &lt;/strong&gt;
Four pairs of geometrically and atmospherically corrected Sentinel-2 and Landsat-8 images were used to seasonally map the water quality indices in the Karoun River.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Results and discussion&lt;/strong&gt;
&lt;strong&gt;Calculation of NSFWQI quality index and its seasonal zoning&lt;/strong&gt;
Using the measured field qualitative parameters and equation, the NSFWQI parameter value was calculated. Next, by calculating the CR value between the input images and this index, optimal regression models based on the maximum CR values were developed to seasonally map the entire region.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Calculating the IRWQIsc and its seasonal zoning&lt;/strong&gt;
Based on the measured qualitative field parameters, the value of the IRWQIsc index was calculated. Next, by calculating the CR value between the input images and this index, optimal regression models based on the maximum CR values were developed to seasonally map the entire region.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Conclusion&lt;/strong&gt;
Comparison of the output maps of NSFWQI and IRWQIsc indices showed that Karoun River&#039;s quality status is inappropriate during most of the year and in most areas and it is best to use it with water treatment. According to the NSFWQI index in the NSFWQI2 map of the spring, the qualitative status of the study area changes from bad to moderate and to bad again considering north to south direction. In the summer NSFWQI2 map, the quality of the Karoun River changes from bad to moderate. In the autumn, based on the NSFWQI1 map, the qualitative status changes from bad to medium and again to bad. The qualitative status of the river in the winter shows moderate status. A survey of the qualitative status of the study area based on the IRWQIsc index also shows that in the spring, the river status changes from bad to relatively bad and again to bad. The qualitative change of the region in summer based on the IRWQI2 map changes from bad and relatively bad to relatively good and finally to relatively bad. In the autumn, the IRWQI1 map shows the change from bad to relatively bad and again to bad. In winter, according to the IRWQI2 map, the quality of the Karoun River changes from relatively good to relatively bad.</Abstract>
			<OtherAbstract Language="FA">&lt;strong&gt;Extended Abstract&lt;/strong&gt;
&lt;strong&gt;Introduction&lt;/strong&gt;
Given the importance of surface water for drinking, agriculture, and industry, the protection of these resources against pollution is of great importance for national and regional health.
The integration of satellite imagery to produce data with a higher information level is called image fusion. Fusion methods are generally divided into three categories: pixel-based methods, feature-based methods, and decision-based methods.
The main objective of this research is to optimize seasonal zoning of the water quality indices of Karoun River based on two indices of NSFWQI (National Health Foundation Water Quality Index) and IRWQIsc (Iran Surface Water Quality Index for Conventional Pollutants) and therefore, the fusion of Sentinel-2 and Landsat 8 images will be evaluated. It is noteworthy that based on our knowledge the evaluation of image fusion methods in the field of qualitative indices zoning has not been conducted yet.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Materials and Methods&lt;/strong&gt;
&lt;strong&gt;Measured Quality Parameters&lt;/strong&gt;
Seven sampling stations were selected for seasonal measurement of water quality parameters along a part of the Karoun River in 2018. The measured qualitative parameters included chemical oxygen demand, biological oxygen demand, dissolved oxygen, electrical conductivity, fecal coliform, PH, nitrate, phosphate, total hardness, and turbidity.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;NSFWQI&lt;/strong&gt;
NSFWQI was introduced by the US National Health Organization in 1970. In this index, several questionnaires were filled out by experts in the United States, which are the basis for adjusting this index. Based on the answers, a curve was plotted for each parameter to determine the sub-indices of each parameter.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;IRWQIsc&lt;/strong&gt;
To evaluate the quality of rivers and compare their pollution rates in Iran concerning natural conditions and water resources problems, an index (IRWQIsc) was introduced to provide a good perspective about the quality status of water resources in Iran.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Utilized satellite imageries &lt;/strong&gt;
Four pairs of geometrically and atmospherically corrected Sentinel-2 and Landsat-8 images were used to seasonally map the water quality indices in the Karoun River.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Results and discussion&lt;/strong&gt;
&lt;strong&gt;Calculation of NSFWQI quality index and its seasonal zoning&lt;/strong&gt;
Using the measured field qualitative parameters and equation, the NSFWQI parameter value was calculated. Next, by calculating the CR value between the input images and this index, optimal regression models based on the maximum CR values were developed to seasonally map the entire region.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Calculating the IRWQIsc and its seasonal zoning&lt;/strong&gt;
Based on the measured qualitative field parameters, the value of the IRWQIsc index was calculated. Next, by calculating the CR value between the input images and this index, optimal regression models based on the maximum CR values were developed to seasonally map the entire region.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Conclusion&lt;/strong&gt;
Comparison of the output maps of NSFWQI and IRWQIsc indices showed that Karoun River&#039;s quality status is inappropriate during most of the year and in most areas and it is best to use it with water treatment. According to the NSFWQI index in the NSFWQI2 map of the spring, the qualitative status of the study area changes from bad to moderate and to bad again considering north to south direction. In the summer NSFWQI2 map, the quality of the Karoun River changes from bad to moderate. In the autumn, based on the NSFWQI1 map, the qualitative status changes from bad to medium and again to bad. The qualitative status of the river in the winter shows moderate status. A survey of the qualitative status of the study area based on the IRWQIsc index also shows that in the spring, the river status changes from bad to relatively bad and again to bad. The qualitative change of the region in summer based on the IRWQI2 map changes from bad and relatively bad to relatively good and finally to relatively bad. In the autumn, the IRWQI1 map shows the change from bad to relatively bad and again to bad. In winter, according to the IRWQI2 map, the quality of the Karoun River changes from relatively good to relatively bad.</OtherAbstract>
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			<Param Name="value">Image fusion</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Karoun River</Param>
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			<Object Type="keyword">
			<Param Name="value">Sentinel-2</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">IRWQIsc</Param>
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			<Object Type="keyword">
			<Param Name="value">NSFWQI</Param>
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</Article>

<Article>
<Journal>
				<PublisherName>University of Isfahan</PublisherName>
				<JournalTitle>Geography and Environmental Planning</JournalTitle>
				<Issn>2008-5362</Issn>
				<Volume>31</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2020</Year>
					<Month>05</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Groundwater Resources Potential Based on Geographic Information System (GIS) and Remote Sensing (RS) Using Analytic Network Process (ANP)
(Case Study: Naz Sari Plain)</ArticleTitle>
<VernacularTitle>Groundwater Resources Potential Based on Geographic Information System (GIS) and Remote Sensing (RS) Using Analytic Network Process (ANP)
(Case Study: Naz Sari Plain)</VernacularTitle>
			<FirstPage>103</FirstPage>
			<LastPage>120</LastPage>
			<ELocationID EIdType="pii">25140</ELocationID>
			
<ELocationID EIdType="doi">10.22108/gep.2020.118887.1197</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Zahra</FirstName>
					<LastName>Kasiri</LastName>
<Affiliation>MSc. Graduate in Water Engineering, Haraz Institute of Higher Education, Amol, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Mahmoud</FirstName>
					<LastName>Habibnejad Roshan</LastName>
<Affiliation>Professor, Department of Watershed Management Engineering, Sari Agricultural Sciences and Natural Resources University, Sari, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Sayed Hussein</FirstName>
					<LastName>Roshun</LastName>
<Affiliation>Ph.D. Candidate, Department of Watershed Management Engineering, Sari Agricultural Sciences and Natural Resources University, Sari, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2019</Year>
					<Month>12</Month>
					<Day>23</Day>
				</PubDate>
			</History>
		<Abstract>&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;1. Introduction&lt;/strong&gt;
Groundwater resources are considered as one of the most important sources of freshwater in the world, which provides an important part of the needs of industry, agriculture, and drinking. Due to the location of Iran in the semi-arid and arid climate of the world, studies on the conservation of water resources are becoming increasingly clear. It is necessary to plan and manage the optimal water resources (surface and subsurface) of their study and exploration, which is possible through academic research. The zoning of underground water potential has become an important issue in the world today, with a lot of research being done on this issue. This issue is now facilitated by the use of new technologies of geographic information systems and remote sensing by combining decision-making models. The purpose of this research is to integrate GIS and remote sensing with decision-making models in order to map the potential of groundwater resources in one of the country&#039;s most important plains. Such research is necessary in view of the farming industry, gardens, and industrial use of groundwater in the area.
 
&lt;strong&gt;2. Methodology&lt;/strong&gt;
In order to provide the potential groundwater resources map, 13 factors influencing water permeability in the soil and its storage were considered including geological layers, vegetation, slope, slope direction, rainfall, temperature, elevation, distance from the fault, fault density, distance from the waterways and the congestion, and the distance from the road. These layers were prepared in ArcGIS and Envi software. Then, based on the ANP method, each of the factors was multiplied by its weight vector, and finally, by combining the layers, a groundwater potential mapping map was obtained for the area. In order to assess the accuracy and validation of the final map, the statistics of fountains, qanats, and wells in the area, as well as the ROC curve method, were used.
 
&lt;strong&gt;3. Discussion&lt;/strong&gt;
The groundwater potential mapping potential in the study area was obtained based on the combination of GIS, remote sensing technology, and network analysis methodology, which indicates that about 955.35 sq. Km of the potential area is 2549.76 square kilometers of potentials and very small and 642.16 square kilometers have a moderate potential. High potential areas are more consistent with low altitudes due to lower slopes, alluvial terraces, conifers, and plain areas, where more surface water penetration is possible. Areas with low and very low potentials, which are very steep. Also, according to the ROC curve, the 87 percent result of this curve also indicates the high accuracy of the Antenna Process Analysis (ANP) method for the preparation of groundwater potential maps in the study area.
 
&lt;strong&gt;4. Conclusion&lt;/strong&gt;
Application of ANP model in water resources planning in catchment areas, considering flexibility, taking into account feedback and relation between criteria, using quantitative and qualitative criteria simultaneously and the ability to review compatibility in judgments in order to study the issues related to the planning of catchment areas is a suitable method. The present research is consistent with the results of studies such as Rahman Moghadam et al. (2016), Faraji Solebar et al. (2011), and Itishiri et al. (2013). They suggested the method of analytical network process (ANP) as a suitable method for the potential of groundwater resources. The results of this study also confirm the results of these investigators.</Abstract>
			<OtherAbstract Language="FA">&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;1. Introduction&lt;/strong&gt;
Groundwater resources are considered as one of the most important sources of freshwater in the world, which provides an important part of the needs of industry, agriculture, and drinking. Due to the location of Iran in the semi-arid and arid climate of the world, studies on the conservation of water resources are becoming increasingly clear. It is necessary to plan and manage the optimal water resources (surface and subsurface) of their study and exploration, which is possible through academic research. The zoning of underground water potential has become an important issue in the world today, with a lot of research being done on this issue. This issue is now facilitated by the use of new technologies of geographic information systems and remote sensing by combining decision-making models. The purpose of this research is to integrate GIS and remote sensing with decision-making models in order to map the potential of groundwater resources in one of the country&#039;s most important plains. Such research is necessary in view of the farming industry, gardens, and industrial use of groundwater in the area.
 
&lt;strong&gt;2. Methodology&lt;/strong&gt;
In order to provide the potential groundwater resources map, 13 factors influencing water permeability in the soil and its storage were considered including geological layers, vegetation, slope, slope direction, rainfall, temperature, elevation, distance from the fault, fault density, distance from the waterways and the congestion, and the distance from the road. These layers were prepared in ArcGIS and Envi software. Then, based on the ANP method, each of the factors was multiplied by its weight vector, and finally, by combining the layers, a groundwater potential mapping map was obtained for the area. In order to assess the accuracy and validation of the final map, the statistics of fountains, qanats, and wells in the area, as well as the ROC curve method, were used.
 
&lt;strong&gt;3. Discussion&lt;/strong&gt;
The groundwater potential mapping potential in the study area was obtained based on the combination of GIS, remote sensing technology, and network analysis methodology, which indicates that about 955.35 sq. Km of the potential area is 2549.76 square kilometers of potentials and very small and 642.16 square kilometers have a moderate potential. High potential areas are more consistent with low altitudes due to lower slopes, alluvial terraces, conifers, and plain areas, where more surface water penetration is possible. Areas with low and very low potentials, which are very steep. Also, according to the ROC curve, the 87 percent result of this curve also indicates the high accuracy of the Antenna Process Analysis (ANP) method for the preparation of groundwater potential maps in the study area.
 
&lt;strong&gt;4. Conclusion&lt;/strong&gt;
Application of ANP model in water resources planning in catchment areas, considering flexibility, taking into account feedback and relation between criteria, using quantitative and qualitative criteria simultaneously and the ability to review compatibility in judgments in order to study the issues related to the planning of catchment areas is a suitable method. The present research is consistent with the results of studies such as Rahman Moghadam et al. (2016), Faraji Solebar et al. (2011), and Itishiri et al. (2013). They suggested the method of analytical network process (ANP) as a suitable method for the potential of groundwater resources. The results of this study also confirm the results of these investigators.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Potential</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Aquifer</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">ANP</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">ROC Curve</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Tajan Watershed</Param>
			</Object>
		</ObjectList>
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</Article>

<Article>
<Journal>
				<PublisherName>University of Isfahan</PublisherName>
				<JournalTitle>Geography and Environmental Planning</JournalTitle>
				<Issn>2008-5362</Issn>
				<Volume>31</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2020</Year>
					<Month>05</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Assessing the Quality of Life in the Historic District Neighborhoods and Factors affecting it Case Study: Historic District of Yazd City</ArticleTitle>
<VernacularTitle>Assessing the Quality of Life in the Historic District Neighborhoods and Factors affecting it Case Study: Historic District of Yazd City</VernacularTitle>
			<FirstPage>121</FirstPage>
			<LastPage>142</LastPage>
			<ELocationID EIdType="pii">24737</ELocationID>
			
<ELocationID EIdType="doi">10.22108/gep.2020.119018.1201</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Mahsa</FirstName>
					<LastName>Zareian</LastName>
<Affiliation>Master of Urban Planning, Faculty of Art and Architecture, Yazd University, Yazd, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Najma</FirstName>
					<LastName>Esmaeilpoor</LastName>
<Affiliation>Faculty Member of Urbanism Department, Faculty of Art and Architecture, Yazd University, Yazd, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Reza</FirstName>
					<LastName>Akbari</LastName>
<Affiliation>Faculty Member of Urbanism Department, Faculty of Art and Architecture, Yazd University, Yazd, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2019</Year>
					<Month>09</Month>
					<Day>04</Day>
				</PubDate>
			</History>
		<Abstract>&lt;strong&gt;Introduction&lt;/strong&gt;
&lt;strong&gt;1.‌1. Problem Statement&lt;/strong&gt;
One of the new trends that has had a tremendous impact on the process of changing the views and methods of urban planning in the second half of the twentieth century is the social and qualitative theories of development.
Accordingly, the main purpose of this study is to assess the quality of life in the historical context of Yazd by using indicators appropriate to the nature of life and culture of its inhabitants. The historical fabric of Yazd was once dynamic and solid with a structure and function appropriate to the needs of its inhabitants. But today it faces many problems including the departure of the indigenous population and its replacement with non-indigenous people (Vaziri, 2017, p. 34; Sarai &amp; Alyan, 2015, p. 82), various behavioral disorders and insecurity, low-income residents (Zangiabadi et al., 2015: 133), high unemployment, pettiness land plots (ibid., 145), the existence of incompatible uses in the vicinity of residential structures, low environmental quality, and the multiplicity of unsanitary space.
The neighborhoods of the historical fabric of Yazd are not in a favorable situation in terms of stability (Sarai &amp; Alian, 2015, p. 79; Zangiabadi et al., 2015, p. 154). However, life in this context- which shows the cultural identity of different periods of Yazd history- is ongoing and its body is largely responsible for urban life (Razeghi &amp; Horandi, 2018, p. ‌‌70). Still, the goal of 73% of Yazd tourists is to visit historical places (Dehghanapour Farashah, 2016, p. 17). Therefore, the development of a development framework or any appropriate intervention that guarantees its sustainable survival depends on the awareness of the many quality of life in this fabric.
Given the above issues, the research question is as follows:
- What is the quality of life in the historical fabric of Yazd and which neighborhood has the highest quality of life?
 
&lt;strong&gt;2. Research Methodology&lt;/strong&gt;
&lt;strong&gt;2.‌1. Research Method&lt;/strong&gt;
In addition to the four dimensions of the type of index, the degree of specificity of the indicators (localization of indicators), scale, and time, the fifth dimension is dedicated to the importance of quality of life of different social groups in the city. The urban population may be distinguished from a large number of certain levels including class, age, lifestyle, gender, and ethnicity (ibid., 22). Therefore, the prevailing approach to examine the quality of life in the scale of Yazd historical context in this article is a combined approach (using objective and subjective indicators). In the first stage, after reviewing the existing theoretical foundations and previous researches, especially in Iran, a list of objective and subjective criteria was prepared. By referring to the neighborhoods and in-depth and exploratory interviews, the type of criteria and sub-criteria were reviewed and corrected in accordance with the &quot;social and cultural conditions of the residents&quot; and the &quot;accessibility of the required data&quot;. The social group selected as the statistical population is the heads of households living in the neighborhoods in 2018 (time of data collection).
The second stage was dedicated to empirical studies in which the quality of life in 9 neighborhoods of the historical context of Yazd was measured from both mental and objective perspectives. At this stage and in the first step, to understand the level of residents&#039; satisfaction with their living environment (measuring the quality of mental life) according to the research criteria, a questionnaire was developed and distributed among households living in neighborhoods and completed in a face-to-face interview. The total sample size was determined by Cochran&#039;s method, 371 households. The basis for determining the share of samples in neighborhoods is the relative share of the number of households living in each neighborhood out of a total of 10,795 households living in the historical context in the last official census of the Statistics Center of Iran in 2016. Cronbach&#039;s alpha coefficient was used to determine the reliability of the questionnaires and according to the value of Cronbach&#039;s alpha coefficient (0.768), it was concluded that the research tool has good reliability.
In the second step of the second stage, based on the results obtained from completing the questionnaires and using the technique of &quot;exploratory factor analysis&quot;, the factors affecting the quality of life and the role and importance of each in the quality of life in certain neighborhoods were determined.
In the third step, the quality of the objective and mental life of the residents was measured in parallel. For subjective assessment, after processing the data obtained from the questionnaires, during the overlapping process of the layers related to each questionnaire and according to the scores obtained using the ANP technique, a zoning map of residents&#039; satisfaction with the quality of life in the historical context was produced separately for each neighborhood. In parallel, to measure the objective quality of life of 9 neighborhoods, in a GIS environment, a one-by-one map of criteria and sub-criteria and finally a zoning map of the objective quality of life of the historical context of Yazd by each neighborhood from the overlap of layers (according to AN produced.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Table 1. Dimensions, Criteria, and Sub-criteria of the Research&lt;/strong&gt;





&lt;strong&gt;Dimensions&lt;/strong&gt;


&lt;strong&gt;Criterion&lt;/strong&gt;


&lt;strong&gt;under the criteria&lt;/strong&gt;




&lt;strong&gt;Economic&lt;/strong&gt;


investment


Owners&#039; willingness to invest in improving their property




How to seize property


Housing ownership




&lt;strong&gt;social&lt;/strong&gt;


Sense of belonging


Not wanting to immigrate




The degree of intimacy between the residents of the neighborhood and happiness




The extent of cooperation to solve neighborhood problems




Security


The rate of theft of money, gold, and property




The traffic of evil and delinquent people




Pedestrian traffic safety at night




Security of women and children




Ruined places and wrong places




The lighting of passages and alleys




&lt;strong&gt;Physical-spatial&lt;/strong&gt;


Transportation


Access to public transport




Public transport safety




Access to parking




Services and infrastructure
 
 
 


Condition of sidewalks and sidewalks




Access to health centers




Access to commercial use




Access to cultural-sports centers




Access to educational use




Access to green space and park




 
Physical characteristics


Area of ​​buildings




Quality of buildings




Old buildings




Building resistance




Inactive applications




&lt;strong&gt;environmental&lt;/strong&gt;


 


The crowd and crowded environment




(Noise pollution caused by motorcycle traffic)



 

Graffiti, ruined places, etc. (visual pollution)



 

Green space quality




How to collect garbage





&lt;strong&gt;Source: Authors&lt;/strong&gt;
&lt;strong&gt;3. Conclusion&lt;/strong&gt;
Today, the quality of urban life is one of the new concerns of urban management and planning institutions, and accordingly, planners are trying to show the quality of life at different geographical levels. Meanwhile, the evaluation of the quality of life in the historical context and the value of our country&#039;s cities, which show the cultural identity of different periods of this country&#039;s history, is effective in identifying the current situation, awareness of their strengths, shortcomings and possible shortcomings. In this regard, one of the best models of evaluation is the simultaneous use of objective and subjective indicators, and ignoring each of these indicators creates problems in urban planning; Therefore, in this article, the quality of life of the historical context of Yazd in relation to economic, social, environmental and physical-spatial dimensions and developed criteria related to each dimension and in accordance with the local characteristics of the region were measured.
The results of measuring the quality of life in the historical context of Yazd showed that security, quality of the environment, neighborhood relations, transportation, sense of belonging, physical characteristics of buildings and services and infrastructure are seven major factors affecting the quality of life in the historical context of Yazd; Of course, the importance of these factors in the current quality of life of people living in this context is not the same. Environmental quality factor has been far more important than other factors affecting the quality of life of the inhabitants of the historical context of Yazd (to see all the identified influencing factors, please refer to tables 5 and 6).
Residents of the historical context of Yazd city have expressed dissatisfaction with the status of most of the quality of life indicators selected by the research, and the highest level of dissatisfaction has been with the lighting and asphalt of roads and alleys and noise and visual pollution in the area. Satisfaction surveys from 33 selected research indicators indicate that the level of satisfaction with security and neighborhood relations is at the highest level and satisfaction with the quality of the environment and services and infrastructure is at the lowest level.
The results obtained from the quality of life zoning map of the historical context of Yazd also indicate that the Zoroastrian neighborhood has a better quality of life than other neighborhoods in the research area and the neighborhoods of Shash Badgiri and Fahadan have the lowest quality of life.</Abstract>
			<OtherAbstract Language="FA">&lt;strong&gt;Introduction&lt;/strong&gt;
&lt;strong&gt;1.‌1. Problem Statement&lt;/strong&gt;
One of the new trends that has had a tremendous impact on the process of changing the views and methods of urban planning in the second half of the twentieth century is the social and qualitative theories of development.
Accordingly, the main purpose of this study is to assess the quality of life in the historical context of Yazd by using indicators appropriate to the nature of life and culture of its inhabitants. The historical fabric of Yazd was once dynamic and solid with a structure and function appropriate to the needs of its inhabitants. But today it faces many problems including the departure of the indigenous population and its replacement with non-indigenous people (Vaziri, 2017, p. 34; Sarai &amp; Alyan, 2015, p. 82), various behavioral disorders and insecurity, low-income residents (Zangiabadi et al., 2015: 133), high unemployment, pettiness land plots (ibid., 145), the existence of incompatible uses in the vicinity of residential structures, low environmental quality, and the multiplicity of unsanitary space.
The neighborhoods of the historical fabric of Yazd are not in a favorable situation in terms of stability (Sarai &amp; Alian, 2015, p. 79; Zangiabadi et al., 2015, p. 154). However, life in this context- which shows the cultural identity of different periods of Yazd history- is ongoing and its body is largely responsible for urban life (Razeghi &amp; Horandi, 2018, p. ‌‌70). Still, the goal of 73% of Yazd tourists is to visit historical places (Dehghanapour Farashah, 2016, p. 17). Therefore, the development of a development framework or any appropriate intervention that guarantees its sustainable survival depends on the awareness of the many quality of life in this fabric.
Given the above issues, the research question is as follows:
- What is the quality of life in the historical fabric of Yazd and which neighborhood has the highest quality of life?
 
&lt;strong&gt;2. Research Methodology&lt;/strong&gt;
&lt;strong&gt;2.‌1. Research Method&lt;/strong&gt;
In addition to the four dimensions of the type of index, the degree of specificity of the indicators (localization of indicators), scale, and time, the fifth dimension is dedicated to the importance of quality of life of different social groups in the city. The urban population may be distinguished from a large number of certain levels including class, age, lifestyle, gender, and ethnicity (ibid., 22). Therefore, the prevailing approach to examine the quality of life in the scale of Yazd historical context in this article is a combined approach (using objective and subjective indicators). In the first stage, after reviewing the existing theoretical foundations and previous researches, especially in Iran, a list of objective and subjective criteria was prepared. By referring to the neighborhoods and in-depth and exploratory interviews, the type of criteria and sub-criteria were reviewed and corrected in accordance with the &quot;social and cultural conditions of the residents&quot; and the &quot;accessibility of the required data&quot;. The social group selected as the statistical population is the heads of households living in the neighborhoods in 2018 (time of data collection).
The second stage was dedicated to empirical studies in which the quality of life in 9 neighborhoods of the historical context of Yazd was measured from both mental and objective perspectives. At this stage and in the first step, to understand the level of residents&#039; satisfaction with their living environment (measuring the quality of mental life) according to the research criteria, a questionnaire was developed and distributed among households living in neighborhoods and completed in a face-to-face interview. The total sample size was determined by Cochran&#039;s method, 371 households. The basis for determining the share of samples in neighborhoods is the relative share of the number of households living in each neighborhood out of a total of 10,795 households living in the historical context in the last official census of the Statistics Center of Iran in 2016. Cronbach&#039;s alpha coefficient was used to determine the reliability of the questionnaires and according to the value of Cronbach&#039;s alpha coefficient (0.768), it was concluded that the research tool has good reliability.
In the second step of the second stage, based on the results obtained from completing the questionnaires and using the technique of &quot;exploratory factor analysis&quot;, the factors affecting the quality of life and the role and importance of each in the quality of life in certain neighborhoods were determined.
In the third step, the quality of the objective and mental life of the residents was measured in parallel. For subjective assessment, after processing the data obtained from the questionnaires, during the overlapping process of the layers related to each questionnaire and according to the scores obtained using the ANP technique, a zoning map of residents&#039; satisfaction with the quality of life in the historical context was produced separately for each neighborhood. In parallel, to measure the objective quality of life of 9 neighborhoods, in a GIS environment, a one-by-one map of criteria and sub-criteria and finally a zoning map of the objective quality of life of the historical context of Yazd by each neighborhood from the overlap of layers (according to AN produced.
&lt;strong&gt; &lt;/strong&gt;
&lt;strong&gt;Table 1. Dimensions, Criteria, and Sub-criteria of the Research&lt;/strong&gt;





&lt;strong&gt;Dimensions&lt;/strong&gt;


&lt;strong&gt;Criterion&lt;/strong&gt;


&lt;strong&gt;under the criteria&lt;/strong&gt;




&lt;strong&gt;Economic&lt;/strong&gt;


investment


Owners&#039; willingness to invest in improving their property




How to seize property


Housing ownership




&lt;strong&gt;social&lt;/strong&gt;


Sense of belonging


Not wanting to immigrate




The degree of intimacy between the residents of the neighborhood and happiness




The extent of cooperation to solve neighborhood problems




Security


The rate of theft of money, gold, and property




The traffic of evil and delinquent people




Pedestrian traffic safety at night




Security of women and children




Ruined places and wrong places




The lighting of passages and alleys




&lt;strong&gt;Physical-spatial&lt;/strong&gt;


Transportation


Access to public transport




Public transport safety




Access to parking




Services and infrastructure
 
 
 


Condition of sidewalks and sidewalks




Access to health centers




Access to commercial use




Access to cultural-sports centers




Access to educational use




Access to green space and park




 
Physical characteristics


Area of ​​buildings




Quality of buildings




Old buildings




Building resistance




Inactive applications




&lt;strong&gt;environmental&lt;/strong&gt;


 


The crowd and crowded environment




(Noise pollution caused by motorcycle traffic)



 

Graffiti, ruined places, etc. (visual pollution)



 

Green space quality




How to collect garbage





&lt;strong&gt;Source: Authors&lt;/strong&gt;
&lt;strong&gt;3. Conclusion&lt;/strong&gt;
Today, the quality of urban life is one of the new concerns of urban management and planning institutions, and accordingly, planners are trying to show the quality of life at different geographical levels. Meanwhile, the evaluation of the quality of life in the historical context and the value of our country&#039;s cities, which show the cultural identity of different periods of this country&#039;s history, is effective in identifying the current situation, awareness of their strengths, shortcomings and possible shortcomings. In this regard, one of the best models of evaluation is the simultaneous use of objective and subjective indicators, and ignoring each of these indicators creates problems in urban planning; Therefore, in this article, the quality of life of the historical context of Yazd in relation to economic, social, environmental and physical-spatial dimensions and developed criteria related to each dimension and in accordance with the local characteristics of the region were measured.
The results of measuring the quality of life in the historical context of Yazd showed that security, quality of the environment, neighborhood relations, transportation, sense of belonging, physical characteristics of buildings and services and infrastructure are seven major factors affecting the quality of life in the historical context of Yazd; Of course, the importance of these factors in the current quality of life of people living in this context is not the same. Environmental quality factor has been far more important than other factors affecting the quality of life of the inhabitants of the historical context of Yazd (to see all the identified influencing factors, please refer to tables 5 and 6).
Residents of the historical context of Yazd city have expressed dissatisfaction with the status of most of the quality of life indicators selected by the research, and the highest level of dissatisfaction has been with the lighting and asphalt of roads and alleys and noise and visual pollution in the area. Satisfaction surveys from 33 selected research indicators indicate that the level of satisfaction with security and neighborhood relations is at the highest level and satisfaction with the quality of the environment and services and infrastructure is at the lowest level.
The results obtained from the quality of life zoning map of the historical context of Yazd also indicate that the Zoroastrian neighborhood has a better quality of life than other neighborhoods in the research area and the neighborhoods of Shash Badgiri and Fahadan have the lowest quality of life.</OtherAbstract>
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