Geographic Data
Foroogh Mohammadi Ravari; Ahmad Mazidi; Zahra Behzadi shahrbabak
Abstract
Extended Abstract
Introduction
Replacing natural vegetation cover with impermeable urban surfaces) stone, cement, metal, etc.) has resulted in increased land surface temperature which is considered to be the most important problem of urban areas. Distinct temperature difference between the city and ...
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Extended Abstract
Introduction
Replacing natural vegetation cover with impermeable urban surfaces) stone, cement, metal, etc.) has resulted in increased land surface temperature which is considered to be the most important problem of urban areas. Distinct temperature difference between the city and the surrounding areas is called heat island (Melkpour et al., 2018). Increased land surface temperature and resulting heat islands in urban areas built without proper preplanning (Khakpour et al., 2016) especially in developing countries such as Iran experiencing a rapid growth rate have resulted in widespread environmental problems. Heat islands mainly occur due to the presence of man-made surfaces which prevent the reflection of sunlight and result in temperature increase. In general, urban heat islands result in increased air and land surface temperature and thermal inversion (Gartland, 2012).
Methodology
The present study applies a statistical-analytical research method based upon statistical data received from meteorological stations and extracted from satellite images. Climatic data recorded from 1976 to 2020 in Yazd Meteorological Station were retrieved from the General Meteorological Department of Yazd Province and used to measure temperature changes. Urban climate studies mainly take advantage of long-term patterns and thus, the present study has applied the common Man-Kendall method to measure the trend of temperature changes in warm season (July, August, and September). Also, satellite images collected by Landsat 4-8 in a 33-year period, including four statistical periods with a time interval of 11 years (the average recorded in July, August and September of 1987, 1998, 2009 and 2020), have been used to extract heat islands of Yazd city in warm seasons. These images collected under clear weather conditions were retrieved from the United States Geological Survey website (http://glovis.usgs.gov/) in the WGS-1984 UTM image system. NDVI index was used to investigate the vegetation cover. Main land uses discussed in the present study included barren lands, urban areas, vegetation cover and roads. Sample land uses were collected from Google Earth and visually interpreted in ArcMap. Maximum likelihood algorithm was used for the classification process. Finally, Land Surface Temperature was extracted from satellite images and compared with air temperature trend using the Mann-Kendall test.
Results & Discussion
Results indicate that due to thicker vegetation cover in summer, there has been a negative relationship between the vegetation cover and land surface temperature. In other words, land surface temperature has increased with decreased vegetation cover and vice versa. Types of land use identified in satellite images collected from Yazd city have showed that the city has experienced a widespread physical expansion during the 33-year statistical period regardless of the season under investigation and thus, built-up urban land use class has expanded significantly. As a result, vegetation cover has experienced a negative trend and decreased. Land surface temperature extracted from thermal images of Yazd city has proved parts of northwest and south of the city to be the core of its heat islands. This is due to the presence of barren lands, lack of evapotranspiration mechanisms, high heat absorption capacity and low conduction capacity. Man-Kendall test has found a significant increasing trend for temperature especially in recent years in which the temperature has increased about 2.3 °C. This is most possibly due to the increasing trend of urban population in recent decades, followed by increased residential structures and resulting heat island phenomenon.
Conclusion
In general, classification of urban land use types in Yazd has shown a significant physical expansion of the city during the statistical period. This physical development has occurred in all directions; beginning from the central and northeast-southeast parts, and moving towards northwest-southwest parts. Maximum NDVI was observed in a strip along the central part of Yazd in which vegetation cover is thicker. Green spaces are also observed in some areas of the city. Color spectrum of the LST map has shown relative changes of the ambient temperature in various parts of the city. High and very high temperature (between 41.5 and 50 °C) show the location of the heat islands on LST maps. Also, areas with a deep red color and a temperature above 50 °C have formed hot clusters formed or strengthened between 2009 and 2020 in the west and southwest parts of the city. Satellite images and related graphs have showed that in 2020, Yazd have witnessed a sharp increase in temperature and a heat island. Temperature data of Yazd Meteorological Station and Man-Kendall test have shown a significant increasing trend (about 2.3°C), especially in recent years. These are related to the urban population growth in recent decades, followed by increased urban structures (residential-commercial) and heat island phenomenon.
Saeed Varamesh; Sohrab Mohtaram Anbaran; Zahra Rouhnavaz
Abstract
Extended Abstract
Introduction
awareness of the type and percentage of land use and cover types is a fundamental requirement for understanding and management of a region. The growth of urbanization and increasing use of resources due to the development of the required facilities in urban life has changed ...
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Extended Abstract
Introduction
awareness of the type and percentage of land use and cover types is a fundamental requirement for understanding and management of a region. The growth of urbanization and increasing use of resources due to the development of the required facilities in urban life has changed the pattern of demand for resources and lands, changing the nature and quality of agricultural land, Historical and natural landscapes and surrounding urban areas through the transformation of these lands into residential areas. In recent decades, the suburban lands of cities have changed their use due to the urbanization process and the need of citizens for new residential areas and the surrounding lands, which are often high quality agricultural lands and gardens. This, along with things like industrialization and changing rainfall patterns, has destroyed the cover and natural environment of cities, and thus has posed many social and environmental challenges and endangered sustainable urban development, and as a result of this process, a lot of ecological pressure has been imposed on the natural ecosystem of the region. These changes are considered as one of the important and effective factors of social and environmental challenges. Today, remote sensing technology and GIS due to capabilities such as high monitoring power and resolution, frequent images, cost reduction, etc., To effectively identify and quantify land use changes and their effects on the environment and monitoring And rapid management of the growth and development of cities are used. In the present study, the aim is to evaluate the urban development of Ardabil in the last 30 years using remote sensing technology and satellite images.
Materials & Methods
Landsat satellite imagery was used to prepare land use maps for 1987, 2000 and 2017. In order to ensure the quality of data and bands, the images used in this research were first corrected for radiometric errors in ENVI 5.3 software environment. Then RVI, SAVI, NDVI, BI and IPVI indices were extracted. In the next step, maps related to filter texture, vegetation delineation and tasseled cap were prepared. At the end of this step, all the extracted layers were merged with the corrected image bands. Then satellite imagery using support vector machine algorithms, maximum similarity and artificial neural network with acceptable accuracy in six user classes (residential areas, covered agricultural lands, fallow, barren lands, urban forest and water) floor were classified. Then, to evaluate the classification accuracy, the overall accuracy and kappa coefficient were calculated for each of the maps.
Results & Discussion
According to the values of overall accuracy and kappa coefficient, which in 1987 for the support vector machine algorithm were 90% and 0.86, respectively, the maximum likelihood was 84.5% and 0.78, and the neural net was 90.5% and 0.87, respectively, in 2000. Overall accuracy and kappa coefficient for support vector machine algorithm 92% and 0.90, maximum likelihood 92.5% and 0.90 and neural net 92.6% and 0.90, and in 2017 overall accuracy and kappa coefficient for backup vector machine algorithm 90.6% and 0.88, maximum likelihood of 82.8% and 0.78 and for neural net were 88% and 0.85, it was found that the support vector machine algorithm has the highest accuracy compared to the other two algorithms. According to the results obtained from the study of satellite images classified by the support vector machine algorithm, the area of land built in Ardabil has increased from 20.023 square kilometers in 1987 to 41.554 square kilometers in 2017.
Conclusion
In general, it can be concluded that to evaluate the trend of urban sprawl and awareness of land use change patterns for optimal management and planning of cities, the use of satellite images, especially Landsat images is a suitable and low cost option. The results also showed that the rate of land use change to land uses is increasing and since land is the main element in urban development, so control how to use it and also calculate the real need of the city for land, to In order to provide different uses is effective. As a result, according to the findings of this study, in the absence of proper planning for this city due to favorable lands for urban development around the city, in the not too distant future, witness the destruction of agricultural lands around the city of Ardabil and conversion they will be residential areas.
Behrooz Naroei; Shahindokht Barghjelveh; Hassan Esmaeilzadeh; Lobat Zebardast
Abstract
Extended Abstract
Introduction
The rapid expansion of urbanization along with irregular changes in land use and Landscape System of Tehran has disrupted the composition and distribution pattern of urban green infrastructure. The present study seeks to analyse the spatial-temporal changes of urban green ...
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Extended Abstract
Introduction
The rapid expansion of urbanization along with irregular changes in land use and Landscape System of Tehran has disrupted the composition and distribution pattern of urban green infrastructure. The present study seeks to analyse the spatial-temporal changes of urban green infrastructure in Tehran Landscape System affected by the spatial processes of land use changes in the statistical period (4 decades of 1990 to 2030). To reach this aim, the present study has identified (1) the effect of spatial processes on the changing landscape pattern and (2) the relationship between the spatial pattern and ecological processes of landscape and its influence on the capacities and constraints of green urban infrastructure.
Materials & Methods
The present study has focused on the landscape system of Tehran and its 22 districts as the study area. The descriptive-analytical study consists of following stages: 1) Classifying urban land uses in1990-2000, 2000-2010 and 2010-2020 statistical periods using Landsat satellite images: (in Envi 5.3, Google Earth and Arc GIS 10.2 software), 2) Modelling and forecasting land use changes in 2030 using integrated model of Markov chain, automated cells (CA-MARKOV) and TerrSetsoftware), 3) Determining spatial processes of landscape changes via decision tree algorithm. 4) Quantifying landscape metrics of composition and configuration of landscape pattern (green, open & built patches) at both class and landscape levels in the mentioned periods (in Fragstate 4.2 software).
Results & Discussion
Many environmental decisions presume that some types or composition of land use are preferred to others. It is assumed that the spatial arrangement of elements in a land-space mosaic controls its ecological processes. This proposition is known as the pattern/ process paradigm, and forms the central hypothesis of landscape ecology (a branch of science developed to study ecological processes in their spatial context). Ten spatial landscape processes are considered to reflect changes in various patterns of landscapes (aggregation, attrition, creation, deformation, dissection, enlargement, fragmentation, perforation, shift, and shrinkage). These processes actually change the spatial structure of urban landscape and affect the quality of ecological processes in Tehran Landscape System. To identify the spatial processes responsible for landscape pattern changes during a defined period of time, a decision tree algorithm was developed. Decision tree required the following input: area or size (a), the perimeter or edge length (p), and number of patches (n) in each land-cover class. The decision tree algorithm applied on Tehran Landscape System has indicated that spatial processes of 'attrition' and 'fragmentation' have led to a decrease in the integration of green and open patches in this landscape system. Measuring LSI and IJI metrics in 1990-2030 statistical period at the class level has also proved the previously mentioned finding. Increased ENN-MN and decreased PLAND of open and green patches during two periods of 1990-2000 and 2010-2020 due to the spatial process of 'attrition' have also showed this decreased integrity over time. These conditions have reduced the resilience of Tehran atmosphere and its capability to absorb air pollution and also have resulted in the recent development of thermal islands in different urban areas. Moreover, the COHESION metric has reduced in green and open patches due to the spatial processes of 'attrition' and 'fragmentation' at the class level. At the landscape level, the value of SIDI metric has also decreased from 1990 to 2020 and the same trend will continue according to 2030 forecast. Spatial process of 'aggregation' in constructed patches has resulted in a decrease of NP and PD at landscape level during 1990-2000 and 2010-2020. Findings indicate the effect of spatial process of aggregation on constructed lands (high-rise buildings) in the northern (such as District 1) and western parts of the city (such as District 22) which has interrupted wind movement and air purification in Tehran. The values of LSI and ED has also decreased at the landscape level due to the 'attrition' of open and green patches leading to a reduction in the heterogeneity order of urban landscape system. On the other hand, increased IJI value in 2020 and 2030 indicates increased turbulence in distribution and also increased fineness index of open and green patches in the landscape system of Tehran.
Conclusion
Findings indicate that spatial processes of 'attrition' and 'fragmentation' have resulted in a reduction in the number and area of green and open patches in the composition pattern and also decreased coherence at class level from 1990 to 2020. This has resulted in an unbalanced distribution of the patches in the configuration pattern of green urban infrastructure in Tehran. The spatial process of 'aggregation' has been repeated during the statistical period in the constructed patches. Data forecasted for 2030 shows the impact of 'attrition' on changes occurring in both green and open land use. The landscape is also getting more simplified due to the dominance of constructed land uses. Findings can be applied to determine a roadmap and plan the spatial pattern of urban green infrastructure.
Aliakbar Anabestani; Zahra Anabestani; Ebrahim Akbari
Abstract
Extended Abstract
Introduction
Determining landscape changes and the impact of urban development requires analyzing land surface changes and identifying appropriate algorithms. And it cannot be ignored that traditional methods for examining land use change and land cover, such as land surveying, are ...
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Extended Abstract
Introduction
Determining landscape changes and the impact of urban development requires analyzing land surface changes and identifying appropriate algorithms. And it cannot be ignored that traditional methods for examining land use change and land cover, such as land surveying, are generally time-consuming and costly and require special skills. In this regard, the advent of remote sensing techniques, GIS has enabled researchers, planners and city managers to have a comprehensive view of land and land use change over time at a lower cost. However, these tools alone cannot describe the main trends and patterns of the city and urban development; Therefore, a combination of land use metrics and development index was proposed, which, along with remote sensing and GIS, lead to more desirable and accurate results. As a result of the present study, with the aim of analyzing the structural changes of the landscape and urban development patterns of Mashhad city using multi-time satellite images during the years 2000, 2010 and 2020 has been done. Also, in this regard, the main research questions are as follows: 1- Which direction will the growth and development of Mashhad city from 2000 to the horizon of 2040? 2- What kind of growth has followed the expansion of Mashhad from 2000 to 2040?
Materials & Methods
The present study is descriptive-analytical in nature. Information was prepared and adjusted through Landsat TM satellite images of 2000 and 2010, OLI sensor for 2020. Before performing the operations related to image processing, radiometric and atmospheric corrections were used using ENVI5.3 software and the FLAASH method was used for atmospheric correction. The images were then categorized using the maximum probability algorithm. In this method, educational samples were used to classify the pixels. Markov chain model in TERSET software was used for prediction on horizons 2030 and 2040. Then the generated maps were entered into FRAHSTATS4.2 software to measure the metrics of the landscape. Also, the Urban Growth Type Outlook Development Index (LEI) was evaluated using GIS software.
Results & Discussion
According to the land use map prepared for a period of 20 years, land related to the city in this period for the city of Mashhad due to population growth and demand for land as a result of urbanization growth in recent decades has the most area changes. So that the area of these lands has increased from 7% in 2000 to 12% in 2020 and this shows a 5% growth in the land area of this land use during this period. Agriculture and gardens from 2000 to 2020 has had an increasing trend 1. Therefore, the area of this user has increased from 11% in 2000 to 17% in 2010 and this shows a 6% growth in the area of this user. But from 2010 to 2020, the area of agricultural use and gardens has been drastically reduced. As a result, the area of this user in 2010 is equal to 17% and for 2020 is equal to 8%, which indicates a 9% decrease in the area of this user. Desert land use has been declining over the period, with a 4% reduction in area. The use of rangelands has not changed much during this period.
The analysis of metrics on the surface of the land for the horizon of 2030 Mashhad showed that the area of this city will not change. The number of spots will decrease, indicating that the shape of the city will become more cohesive over time. The index of the largest spot and the density of the margin will have a decreasing trend, and this indicates that the city will become more cohesive on the horizon of 2030. Landscape shape index will have a decreasing trend. Also, the analysis of metrics on the surface of the land for the horizon of 2040 Mashhad showed that the area of this city will not change. The number of spots will decrease, indicating that the shape of the city will become more cohesive over time. The index of the largest spot and the density of the margin will have a decreasing trend, and this indicates that the city will become more cohesive on the horizon of 2030. Landscape shape index will have a decreasing trend.
Conclusion
In examining the first question based on the growth and development of the city of Mashhad from 2000 to 2040, which direction will it be? According to the maps classified in a period of 20 years and the projected maps for the horizons of 2030 and 2040 for the city of Mashhad, it was determined that the most change is related to the city limits, so that in this period, the constructions and physical growth of the city have been in the northwest direction, and on the other hand, because the constructions are usually done on lands related to gardens and agriculture. In this part of the city, we are witnessing a decrease in agricultural lands and gardens, followed by an increase in urban areas. According to the map of 2020, agricultural lands and gardens in the southeast side still remain and one of the reasons could be the lack of development of the city in this direction. Also, in reviewing the second research question, what kind of growth has followed the expansion of Mashhad from 2000 to 2040? Findings showed that according to the urban development index and based on the numerical value given to the buffer, it was found that the development of Mashhad in the period between 2000 to 2040 is of the type of development from the edge of the city (edge-expansion).
Maryam Mombeni; Hamidreza Asgari
Abstract
Extended Abstract
Introduction
In recent years, the growth of urbanization in Iran and the increase of migration to the major cities have led to the sudden and abnormal expansion of these cities, degradation of fertile lands and natural resources, and irreparable damages to the nature. As the population ...
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Extended Abstract
Introduction
In recent years, the growth of urbanization in Iran and the increase of migration to the major cities have led to the sudden and abnormal expansion of these cities, degradation of fertile lands and natural resources, and irreparable damages to the nature. As the population of the city of Shushtar has increased, there has been a lot of growth in the built lands in the region, causing a large change in the use of the lands around the city and the degradation of the fertile lands in the suburbs; so that, the continuation of this process could cause irreparable damages to the environmental resources of the region. Land-use prediction models are essential in planning for sustainable use of the lands (Kamusoko et al., 2009: 435, Mas et al., 2004: 94, Sohl and Claggett, 2013: 235). In addition, predicting land use changes and creating a relation between these changes and their socio-economic consequences is very important for sustainable land management (Whitford et al., 2008: 340). So far, the Markov-genetic model has been used in several studies. Wu et al. (2006) studied the monitoring and forecasting of the Beijing region of China over a 16-year period and used the Markov chain model and regression to predict the land use. Therefore, the purpose of this study was to investigate the trend of land use changes over the past years and predicting the land use and land use changes using the Markov chain model in the city of Shushtar in Khuzestan province. By predicting land use variations, the development and degradation of the resources can be identified and it can be led to managing the changes in the appropriate pathways (Brown et al. 2000: 247, Hathout, 2002: 229 and Jenerette et al., 2001).
Materials & Methods
The study area of this research is Shushtar city with an area of 340645.2 hectares located in the North of Khuzestan province. The software packages used in this research include ArcGIS 10.2, ENVI 4.8 and IDRISI Selva 17.0. The images used to extract ground cover classes include Landsat series satellite images; these images were used in this research due to having a long time series, having an appropriate spatiotemporal resolution to study the land cover changes, and being free. Regarding the existing land uses in the region, the research objectives, and the capabilities of the images used to extract useful information, especially the land use mapping, four land uses including rangeland, irrigated agricultural lands, rainfed agricultural lands and residential lands were considered. In the analysis of the Markov chain, the cover classes are used as the states of the chain. To determine the possibility of a change, the chain needs two land use maps (model inputs), which are usually obtained by processing the satellite images (Mitsova et al., 2011: 141). Markov chain analysis was performed using Markov chain order in the Idrisi Selva software. Markov chain analysis is provided for two purposes, the first matrix is used for calibration and the second one is used to simulate the possible changes occurring in the future. The output of the model also includes the possibility of transforming the state, transition area matrix for each class, and at the end of the conditional probability images for converting different uses (Gilks et al., 1996: 19 and Weng, 2002: 273).
Regarding the trend of changes during these three periods, the irrigated and residential lands classes had an increasing state, but on the contrary, rainfed lands and rangelands classes had been decreasing. The accuracy of classifications is generally more than 77%, and suitable for use in the Markov model. The results of the detection of changes in 2030 are such that if the current trend continues in the region, 20.33% will be added to the area of the irrigated agricultural land use, so that irrigated agricultural land use constitutes 60.95% of the area in 2030. This increase is due to the changes of the land uses of rangeland and rainfed to the irrigated agriculture. The decrease in the rangeland and rainfed classes will be 21.12% and 0/21% respectively which will be added to the area of the irrigated agricultural lands. These changes are more pronounced around the rural areas in the region.
Results & Discussion
During the research period, irrigated agriculture has been the most dynamic land use in the region. The area of these lands has increased from 1989 to 2015, so that, 1350131.69 ha has been added to the area of this land use during the three study periods. In the first period, the annual rate of increase was 3650 hectares and in the second period the annual rate increase was 3998 hectares. Considering the lack of change in regional governance and planning, the trend is such, that more than 60 percent of the plain area will be covered by this class in 2030 which can be led to changes in the ecosystem conditions. This result is consistent with the results of Gholamali Fard et al. (2014) in the middle coasts of Bushehr province and is not consistent with the results of Ali Mohammadi et al (2010), Dejkam et al. (2015), and Ramezani and Jafari (2014).
Conclusion
In general, the results of this study indicate an increase in the area of irrigated agriculture, as well as development of the Shushtar, which has occurred through the disappearance of rangelands and rainfed lands. As it is well known, if the current strategy of land use in this area continues to reduce natural lands and increase urban lands, regardless of sustainable development considerations until 2030, significant environmental problems, including degradation of rangeland, decline in production of the major agricultural products of the region, decrease in the fertility, and increase in the deserts, will be a serious threat to the future ecosystem of the region. Also, considering the current productivity status, the region's economy which is based on the agricultural and livestock production will face a serious threat in 2030. Therefore, this research recommends the use of resulting maps to identify the sensitive areas for better planning and management of the executive organizations.
Mohammad Nasrollahi; Maryam Mombeni; Sara Valizadeh; Hasan Khosravi
Abstract
Oneof the direct methods of land use impacts on thehydrological conditions of each region is the relation between landuse changes and the groundwater table fluctuations that can assistmanagers in optimal management of natural resources. In thisstudy, to evaluate the impacts of land use changes on thegroundwater ...
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Oneof the direct methods of land use impacts on thehydrological conditions of each region is the relation between landuse changes and the groundwater table fluctuations that can assistmanagers in optimal management of natural resources. In thisstudy, to evaluate the impacts of land use changes on thegroundwater level drops in Gilan-E gharb plain, satellite imagesfrom MSS, TM and ETM sensors in 1985, 2000, 2010 were used. Afterprocessing and analysis of images, the region were classified intosix classes in terms of land use including forest, pasture, dry and water farming, farming, and residential areas. Quantitative statistics of piezometric wells in the plain during1999 -2010was used to examinethe aquifer changes and the resulting layerswere also classified. The results showed that pasture land useholds the largest area with more than 50% of the maximum area, so thatit formed 61.8% (9927 ha) and 67.15% (10782 ha) of the area in1985and 2000 respectively. Its area has decreased during the period from2000 -2010,so thatit has covered 50.23% (8066 ha) of the region in 2010. Evaluation of dry andwater farming also showed that it has facedan area reduction of 0.84% (130 ha) during1985-2000,but these changes in the period of 2000 to 2010 has increased to 1429ha which formed 8.9% of the region. Investigating the rate of groundwater dropsshowed that ground water drop has increased by replacing the pasture land use class with water and dry farming classes.These changes have caused 83.93% ofthe area to have a groundwater drop of more than 50 cmper year in 2010, so that the area of this region has been43.85% of the regionin 2000. Human intervention is undoubtedly one of the most important factors ofthe region destruction.
