Land use Planning
Azra Moshtagheh Mehr; Asadollah Hejazi; Fariba Karami
Abstract
In the present research, the evaluation of land use changes in Mahabad county in a twenty-year period from 2000 to 2020 and the prediction of its possible trends until 2040 have been discussed. In this research, the images of ETM and OLI sensors of Landsat satellite in three years of 2000, 2010 and 2020 ...
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In the present research, the evaluation of land use changes in Mahabad county in a twenty-year period from 2000 to 2020 and the prediction of its possible trends until 2040 have been discussed. In this research, the images of ETM and OLI sensors of Landsat satellite in three years of 2000, 2010 and 2020 and the supervised classification have been used to detect the changes that have occurred. In addition, in order to simulate land use changes, Markov model and cellular automata have been used. Based on our results, the highest trend of increase was related to the built-up lands and the highest trend of decrease was related to the water bodies of the region. In other words, the area of built-up lands increased from 2367.67 hectares to 71006.08 hectares. Besides, the area of water bodies has reached from 9266.63 hectares to 1164.28 hectares, respectively. In addition, based on the results of the Markov model, it is expected that the trend of land use changes will decrease the area of agricultural lands by 1473.1 hectares, orchards and forests by 810.11 hectares, pasture land by 16455.4 hectares and water bodies by 545.69 hectares. On the other hand, these changes will be accompanied by an increase in the area of barren lands by 11831.72 hectares and built-up lands by 7448.42 hectares. Therefore, the possible trend of changes indicates an increase in the level of barren lands and built-up lands and a decrease in other land uses. The results of the present research highlighted the need to pay attention to the challenge of land use change in Mahabad county and can provide a proper understanding of the dimensions, trends and patterns of land use in the region to officials, researchers and local people.
GIS&RS
keramatollah ziari; hossein iraji
Abstract
Introduction As the center of the province of Fars, the City of Shiraz experienced an endogenic and organic growth until the 1960s and prior to the onset of modernity in Iran, which saw a good balance between the urban population growth rate and its area growth. Following a rise in the urban population ...
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Introduction As the center of the province of Fars, the City of Shiraz experienced an endogenic and organic growth until the 1960s and prior to the onset of modernity in Iran, which saw a good balance between the urban population growth rate and its area growth. Following a rise in the urban population in recent decades, the physical form of the cites also changed.Data and Method To investigate the changes and dynamism of the land cover, land use maps were developed to determine the changes over different time intervals. The maps were derived from Landsat satellite images with OLI, TM and Mss sensors in 1984 and 1994 as well as in 2014 and 2020 by using Remote Sensing techniques on the Earth Explorer Site. TerrSet software was also used to analyze the images. To analyze satellite images, it is required to use TerrSet software.Discussion and conclusionConsistent with regression model analysis, land use changes into urban territories have, over the past 40 years, involved 60% of the total area of the city of Shiraz, indicating sharp change trends in this time interval. The orientation of the changes has mainly been north to south of the city which is due to the proportionate developmental space and presence of open plains.Results Data analysis suggests that land use changes as well as their analysis in the Markov’s model are experiencing a disproportionate expansion under the effect of unsystematic and irregular urban growth. This study determines that districts 9, 10 and 6 saw an irregular (spiral) urban growth in 2018.
Rural Planning
Zahra Arabi; Rezvan Ghorbani salkhord; yosef darvishi
Abstract
IntroductionDrought is one of the environmental disasters that are very common in arid and semi-arid country regions. Rainfall defects have different effects on groundwater, soil moisture, and river flow. Meteorological drought indices are calculated directly from meteorological data such as rainfall ...
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IntroductionDrought is one of the environmental disasters that are very common in arid and semi-arid country regions. Rainfall defects have different effects on groundwater, soil moisture, and river flow. Meteorological drought indices are calculated directly from meteorological data such as rainfall and will not be useful in monitoring drought in the absence of data. Therefore, remote sensing techniques can be a useful tool in measuring drought. Drought is a known environmental disaster and has social, economic, and environmental impacts. Lack of rainfall in an area for long periods is known as drought. Drought and rainfall affect the water and agricultural resources of each region. Materials & MethodsDue to the nature of the problem and the subject under study, the present study is descriptive-analytical with emphasis on quantitative methods. In this study, satellite images of Tera Sensor Modis in 2000 and 2017 were used to verify the existence of wet and drought phenomena. In the next step, by examining the rain gauge and synoptic data of the existing stations and using the standardized precipitation index model of three months (May, June, and April), the sample was selected. Next, we compared temperature status indices (TCI) and vegetation health indices (VHI) in these three months to determine the difference between these indices over the three months. Modira Terra satellite was used to study the vegetation status in the study area. Subsequently, vegetation-free areas were isolated from vegetation areas using the conditions set for the NDVI layer, the experimental method was used to determine the threshold value of this index. For this purpose, different thresholds were tested, with the optimum value of 1 being positive. NDVI is less than 1 free of positive plants and more than free of vegetation. MODIS spectral sensor images for surface temperature variables with a spatial resolution of 1 km, including 31 bands (1080/1180 bandwidth, central bandwidth / 11.017 spatial resolution of 1000 m) and 32 bands - 770/11Central Wavelength Band 032/12 Spatial Resolution Power (1000 m) Selected for months that are almost cloudless. All images are downloaded from the SearchEarthData site and edited. Total rainfall in June, April, and May for 20 years has been provided by the Meteorological Organization of Iran. ARC GIS software and geostatistical methods were used to process Excel data. Pearson correlation coefficient was also used to estimate the correlation between the data. Results & DiscussionA standard precipitation index is a powerful tool in analyzing rainfall data. This study aimed to compare the relationship between remote sensing indices and meteorological drought indices and to determine the effectiveness of remote sensing indices in drought monitoring. The correlation between the variables with the SPI index was evaluated and calculated. The results of the indicators are different, so a criterion should be used to evaluate the performance of these indicators. SPI index on a quarterly time scale (correlation with vegetation) was selected as the preferred criterion. According to the results of correlations, the TCI index with the SPI index had a strong correlation with other indices. In the short run, this index has the highest correlation with thermal indices at the level of 1%. The correlation between meteorological drought index and plant water content and thermal indices increases with increasing time intervals. The positive correlation between vegetation indices and plant water content with meteorological drought indices shows that the trend of changes is in line. Therefore, the TCI index makes the drought more accurate and is a better method to estimate drought.ConclusionThe results showed that among the surveyed fish, the most drought trend was observed in the eastern provinces and covers more than 50% of the region. The trend of changes in this slope was statistically significant. According to the results of correlations, the TCI index had a strong correlation with the SPI index with other indices. It can also be concluded that Modis images and processed indices along with climatic indices have the potential to monitor drought. The use of maps derived from drought indices can help improve drought management programs and play a significant role in reducing the effects of drought.
Climatology
Mohammad Hossein Aalinejad; Saeed jahanbakhsh; Ali Mohammad Khorshiddoust
Abstract
Introduction
Determining the temporal change of snowmelt or agriculture water equivalent of snow, predicting flood, and managing the reservoirs of a region is of utmost importance. Some major parts of the western sections of the country are located in the mountainous region and most of the precipitations ...
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Introduction
Determining the temporal change of snowmelt or agriculture water equivalent of snow, predicting flood, and managing the reservoirs of a region is of utmost importance. Some major parts of the western sections of the country are located in the mountainous region and most of the precipitations of this region occur in the form of snow in winter. The runoff resulting from snowmelt has an important role in feeding the rivers of this region and it has a significant share in developing agriculture and the economy.
Scientific studies have shown that climate change phenomena have significant effects on precipitations, evaporation, perspiration, runoff, and finally water supply. As the demand increases, climate changes, greatness, frequency, and the damage resulting from extreme weather events, as well as the costs of having access to water increase, as well. Therefore, evaluating the runoff resulting from snowmelt and the effect of climate change seems necessary for managing water resources.
Methodology
Gamasiab basin is located in the northeast part of the Karkheh basin originating from the springs in the vicinity of Nahavand. Its basin has an area almost equal to 11040 square kilometers that have been located in the east part having 47 degrees and 7 minutes to 49 degrees and 10 minutes geographical longitude and from the north part, it has 33 degrees and 48 minutes to 34 degrees and 54 minutes geographical latitude. This basin has an altitude between 1275 to 3680 meters.
In this study, snow-related data required for simulation were derived from the daily images of the MODIS sensor. To this end, first, the snow-covered area of the Gamasiab basin was measured during the 2016-2017 water years using the process of satellite images obtained from the MODIS sensor in the google earth engine system. All geometric justifications and calibration processes of images were applied precisely in the mentioned system. In the next step, the output of the GCM model scenarios was utilized for calculating temperature and precipitation changes in future periods. These CMIP5 kind models were under the control of two RCP45 and RCP85 scenarios and were downscaled with LARS-WG statistical model.
Moreover, to investigate the uncertainty of models and scenarios, the best models and scenarios were selected for producing temperature and precipitation data of future periods; accordingly, the outputs of the models for future periods (2021-2040) having the basis period of (1980-2010) were compared using statistical indexes of coefficient of determination (R2) and Root Mean Square Error (RMSE). The results were entered into the SRM model as the inputs. In addition, temperature and precipitation data of meteorological station of the studied region as well as the daily discharge of the river flow of hydrometric station of Chehr Bridge (as located in the output part of Gamasiab basin) were used during the statistical period of October 2016 to May 2018.
Discussion
Using Digital Elevation Model (DEM) of the region and the appendage of Hec-GeoHMS in GIS software, firstly, flow direction map, flow accumulation map, and stream maps were drawn and the output point (hydrometric station of Chehr Bridge) was introduced to the border program of the identified basin and the basin was classified based on the three elevation regions.
Producing temperature and precipitation data of future periods requires a long-term statistical period; accordingly, the meteorological station of Kermanshahd was selected since it was in the vicinity of the studied region. To be confident in the ability of the model in producing data in future periods, the calculated data had to be compared with the observed model and data in the studied stations. The capabilities of the LARS-WG model in modeling the mentioned parameters of this station confirmed the observed data. Moreover, the ability of the model in modeling precipitation was very good and acceptable; however, the most modeling error was related to the precipitation in Mars.
In the next phase and compared to the basic periods, the mean of changes in average precipitation and temperature was measured in the studied stations during January and Juan of 2015 to 2017(for which simulation had occurred); as an index of changing the climate, this was entered into the SRM model under climate change conditions. During the simulation period (January to Juan), it had been predicted that the precipitation parameter would decrease and the temperature parameter would increase.
Conclusion
The results of this study indicated that using the MODIS sensor could provide an acceptable estimation of the snow cover level of the Gamasiab basin, which lacked snow gauge data. Moreover, the results of simulation with the SRM model showed that the model could simulate the snow runoff in the studied region. As the main purpose of the study, the effect of temperature and precipitation in future periods was well stated considering the uncertainty of CMP15 series models and scenarios. The results of temperature changes indicated an average increase of 1.8 C. the results of precipitation also indicated an average decrease of more than 5%. However, decreasing precipitation in the cold months of the years had been predicted severely so that the reduction of precipitation in February was of utmost importance for feeding the snow cover and rivers, which had been estimated to be 20%. This happened while increasing precipitation was mainly related to the hot months of the year whose amount was insignificant and didn`t have that much effect on the runoff. Accordingly, due to the increases in temperature and decreases in precipitation in cold seasons, the results of runoff simulation have indicated a 24% reduction for 2016-2017 and a 29% reduction for 2017-2018 water years.
Climatology
Zeynab Jawanshir; Khalil Valizadeh Kamran; Ali Akbar Rasuly; Hashem Rostamzadeh
Abstract
Introduction Water management has always emphasized the need to abandon water storage in reservoirs and pursue a policy of limiting water consumption. Spatial-spatial information on evapotranspiration helps users understand the evacuation and depletion of water due to evaporation and establish the relationship ...
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Introduction Water management has always emphasized the need to abandon water storage in reservoirs and pursue a policy of limiting water consumption. Spatial-spatial information on evapotranspiration helps users understand the evacuation and depletion of water due to evaporation and establish the relationship between land use, water allocation, and water consumption. Evapotranspiration is the second element of the water cycle (after precipitation) and its accurate estimation on a regional scale is necessary to design appropriate management strategies. Evapotranspiration is a function of the amount of energy available for vegetation and its exchange. Because of this dependence, it can be estimated using the principle of energy conservation. Due to the limited number of meteorological stations in the country and the high cost of collecting ground data, the cost-effectiveness of the use of satellite data is one of its advantages, and the possibility of retrieving data from all levels of the region at one time is its next advantage. Having timely information makes horizontal monitoring of meteorological and environmental parameters possible. The ability of remote sensing to measure some terrestrial parameters has had an important effect on estimating actual evapotranspiration. The SEBAL model is one of the remote sensing algorithms that calculate plant evapotranspiration based on the momentary energy balance at the level of each pixel of a satellite image. The study area of the current research was the eastern cities of Lake Urmia. The reason for studying this section was the impact of recent droughts on these areas and the reduction of surface and groundwater, which has increased the need to manage water resources in these areas. Methodology In the first step of radiometric corrections, the amount of spectral radiance in the thermal band and at the next step, the reflectance in the visible bands, near-infrared, and short-wavelength infrared bands were calculated. As mentioned above, in the SEBAL model, actual evapotranspiration is calculated through satellite imagery and meteorological data is calculated using the surface energy balance. When satellite imagery provides information for its transit time, SEBAL calculates the instantaneous evapotranspiration flux for that time. Landsat 8 images for 2017-2016-2014-2013 years and meteorological data such as Minimum temperature, maximum temperature, dew point temperature, evaporation pan data, sunny hours, and wind speed were analyzed using ENVI 4.8 - Excel 2013- Arc GIS 10.3 software. Results and Discussion SEBAL is an image processing model that measures evapotranspiration and other energy conversions on the Earth's surface using digital data measured by remote sensing satellites that emit visible, near-infrared, and thermal infrared radiation. This method uses surface temperature, surface reflection, and normalized plant differential index (NDVI) and their internal relationships to estimate surface fluxes for different types of land cover. In this section, using the values obtained from latent heat flux and evaporation heat flux, first, the amount of instantaneous evapotranspiration for each pixel was calculated. Then, using Ref_ET software, the total 24-hour evapotranspiration was calculated and the daily evapotranspiration rate was obtained for the whole image. Conclusion The results showed that there was a good correlation between the values estimated by the remote sensing algorithm (SEBAL) and the FAO-Penman-Monteith method as well as the evaporation pan method. The difference between the amount of SEBAL and the FAO-Penman-Monteith method in the reference plant was less than 4.21 mm/day; the largest difference was related to the 22nd of October. In total, SEBAL and Penman-Monteith methods had an average absolute difference of 4.28 mm/day. According to the results of this study, it can be observed that using the SEBAL model, the actual evapotranspiration and water needs of crops and even orchards and rangelands can be calculated on a large scale. This case could prove the suitability of this model for estimating actual evapotranspiration at different levels of the farm and irrigation networks. Therefore, remote sensing has a very high potential to improve the management of irrigation resources in very large areas using various algorithms and providing an estimate of the amount of ET with minimal use of ground data. Using remote sensing technology and GIS, acceptable results can be obtained in estimating the actual evapotranspiration rate, especially in large areas. If the parameters of the energy balance equations and Penman-Monteith could be calculated from satellite images spatially, with a suitable plant coefficient, the two methods would have similar results in estimating the rate of evapotranspiration. Using this method, the plant coefficient, which is one of the important factors in calculating the evapotranspiration of plants, can be accurately determined.
Urban Planning
Hassan Mahmoudzadeh; Mostafa Mahdavifard; Majid Azizmoradi; zanjani zanjani sani
Abstract
Introduction
Urbanization as a revolution in human culture has transformed human interactions with one another. As the urbanization population grows, the use of the environment is intensified. Studies have shown that increasing population and expanding urbanization are turning urban green spaces into ...
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Introduction
Urbanization as a revolution in human culture has transformed human interactions with one another. As the urbanization population grows, the use of the environment is intensified. Studies have shown that increasing population and expanding urbanization are turning urban green spaces into rough and impermeable concrete surfaces, and this trend is especially serious in developing countries and the Third World. Since urban growth is a complex phenomenon in which a number of variables interact nonlinearly, the use of ANNs to model urban development and growth is perfectly reasonable. Artificial neural networks with nonlinear mapping structure have been developed for modeling interconnected systems such as the brain consisting of neurons. The artificial neural network is independent of the statistical distribution of data and does not require any specific statistical variables, so this feature facilitates the combination of remote sensing data and GIS. Currently, remote sensing science is changing a fundamental paradigm in which one- or two-image interpretation approaches pave the way for a wide array of data-rich applications. These improvements are facilitated by the GEE Satellite Image Processing System. The purpose of this research is to introduce a new system (GEE), to investigate and analyze this web portal, its application in monitoring and evaluation of human habitat changes (GHSL) and to map the relationship created using MLP model to predict physical development changes in Tabriz.
Materials and Methods
In this study, the Google Earth Engine (GEE) satellite image processing online system was used to process and extract the global GHSL product, and then the MLP model of Terset was used to predict changes.
Results and Discussion
In this study, it was attempted to analyze and analyze Landsat satellite images in a few minutes in order to prepare physical development map of Tabriz city without using hard data and to predict future development changes using the data available in Google Inheritance Satellite Image Processing System. Physically measure the city using the MLP model. GEE online processor has been able to map the growth of urbanization in the Tabriz city over the past six years. With the increase in urbanization over the past 40 years in the city of Tabriz, we have seen the destruction of about 38% of gardens and agriculture in the city, and even this system of rapid population growth in recent years (2014) on the outskirts of Tabriz as the main center of recent earthquakes.
Conclusion
It has shown the city of Tabriz and is also witnessing a growing trend towards physical development of the city in this part of Tabriz. The results of the MLP model show that the physical development of Tabriz in the future is northeastward and on the outskirts of Mount Aoun bin Ali.
Geomorphology
Shabnam Mahmoudi; Davod Mokhtari; Mohamad Hossein Rezai moghadam; Abbas Moradi
Abstract
Introduction Erosion involves the retreat or advancement of the coastline, is the one of the recent problems of communities along the coast and the existing infrastructure located near the estuary system. Environmentally, coastal areas are of great importance and value due to their sensitive and productive ...
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Introduction Erosion involves the retreat or advancement of the coastline, is the one of the recent problems of communities along the coast and the existing infrastructure located near the estuary system. Environmentally, coastal areas are of great importance and value due to their sensitive and productive ecosystems. Short-term or long-term coastline changes are important in the situation and geometry of coastlines and coastal management. Awareness of coastline behavior helps to manage beaches when designing and constructing coastal facilities and determining the safe margin of the coast. This article tries to modeling the changes in the coastline of East and West Bandar jask(southern Iran) in a timespan, a step towards coastal management for the planning and operation of facilities of Jask Port, which can be follow the future development of the area. Methodology The study area is part of the coast of Jask city located in Jask county in southern Iran. For this purpose, the extent of coastline changes to determine the boundary line between land and water was examined. To be more precise, spectral operators were used in the Arc map environment and Landsat satellite imagery; the next step was to polygonize the shoreline according to the fixed landline on land. In addition, Google Earth satellite imagery was used to examine and mark some case-by-case changes, such as cape changes in the western part of the port of Jask and so on. Results and Discussion The dynamics of coastlines and their variability (affected by lithology and wave activity), the shape of coastlines and their effect on erosion and location of coastal sediments, resources and location of sediment accumulation and hydrodynamics of areas close to coastlines, the intensity of seasonal winds and its role in transmission Sediment transfer and erosion mechanisms, and ultimately, human activities, are among the factors influencing coastline changes. The shape of the shores was examined using the Hausdorff-Pesikovtch method. Accordingly, the rate of change in the area of polygons on the east coast (progress) is higher than on the west coast (retrograde). The reason for the progress on the East Coast could be the construction of new piers, tidal performance, the shape of the beach and how it is positioned against the waves. Overall, Oman's beaches are uplifted, which could be the reason for the retrograde; however, the drying up of the coast in order to build piers and breakwaters has led to the advance of the coast. conclusion Prove the existence of progress on the east coast due to the construction of three new piers (after 2006) and the presence of retrograde on the west coast due to the existing natural mechanisms of the region such as the uplift of Oman coast, is the most important finding of this study. The shape of the beach and the way it escapes from the waves due to the prevailing wind direction (from the southeast) on the east coast has intensified the effect of the human factor.
Climatology
Saeed jahanbakhsh; yagob din pazhoh; mohammad hossein aalinejhad
Volume 23, Issue 67 , April 2019, , Pages 91-107
Abstract
According to the importance of snowfall in supplying water of different regions especially mountainous areas, accurate estimation of snow water equvallent and changes of its coverage would be effective in agriculture, energy, management of reservoir and flood warnings. In this study runoff orginated ...
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According to the importance of snowfall in supplying water of different regions especially mountainous areas, accurate estimation of snow water equvallent and changes of its coverage would be effective in agriculture, energy, management of reservoir and flood warnings. In this study runoff orginated from snow melting in ShahrChay basin under the terms of climate change calculated. For this purpose, snow cover for water year of 2012-2013 were extracted in ENVI software by using daily images of Modis satellite.Then, GIS software the physiographic specification of the basin was obtained. In the next step, data of snow cover, meteorological variables and other necessary parameters to SRM model provided as an input of model and run_off from snow melt was simulated. Then output of the 6 models of atmospheric general circulation with title of 3 scenarios nomely A1B , A2 and B1 converted to a downscaleing by using LARS-WG model. By comparing the output of 6 models in the future period to period based on monthly statistical, the best model and scenario for generation of air temperature and precipitation data in the period 2030-2011 were selected. As a result the HADCM3 model under the scenario A1B was used for generation of precipitation and the MPEH5 under scenarios A2 was used for generation of temperature data. In order to estimate the rate of change of runoff orginated from snowmelt rate of change of monthly data of air temperature and precipitation of the base time period as well as future time period under selected model and scenarios was entered to SRM model in simulation time period. Results for all of the scenarios show that runoff orginated from snowmelt in late spring will be reduced. The peak flow appeared earlier in comparison with base time period and its value would be larger than base time period.
Climatology
Khalil Valizadeh Kamran; maryam longbaf
Volume 22, Issue 65 , November 2018, , Pages 287-299
Abstract
The agriculture is the sector that uses most of fresh water resources. Since the water resources are always subjected to severe depletion, the agriculture sector requires using the water with high efficiency and more effective ways One of the procedures leading to improvement of water management productivity ...
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The agriculture is the sector that uses most of fresh water resources. Since the water resources are always subjected to severe depletion, the agriculture sector requires using the water with high efficiency and more effective ways One of the procedures leading to improvement of water management productivity and ultimately to increase of water efficiency is the accurate estimation of the evapo-transpiration or estimation of water use efficiency of the crops. The remote sensing by giving an estimation of the degree of evapotranspiration (with little use of ground data) has a high potential for modification of cultivation patterns and management of water resources This research aims to determine the actual evapo-transpiration (need of water) of maize, which is an indigenous plant in the northern Khuzestan province, using the image processing of Landsat 8 in four passes include: 13 Aug, 14 Sep, 16 Oct and 17 Nov 2013 and also using the required metrological data based on Surface Energy Balance Algorithm for Land (SEBAL). The results showed that the amounts of needed water estimated by SEBAL model for maize in the initial growth stage, development stage, middle stage and the end stage are 5.04, 8.23, 5.55, and 1.46 mm per day respectively. The values from remote sensing were compared for values assessed by FAO- Penman-Monteith and evaporation pan methods and it was observed that MAE and RMSE are 0.45 and 0.18 mm per day compared to FAO- Penman - Montieth method. In sum, the results indicated that the SEBAL model is able to give answers with high accuracy and in short time and can be used as a beneficial and efficient tool in organizing water resources and meeting the plant water needs.
Urban Planning
Mir Sattar Sadr Mousavi; Rasul Yazdani Chaharborj*
Abstract
The rapid urban growth of recent decades in Iran has resulted in extensive changes in urban fringe land-use patterns.It has also had considerable environmental and socio-economic impacts on these areas.Assessing changes of the past land-use patterns and simulation of their future changes are of vital ...
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The rapid urban growth of recent decades in Iran has resulted in extensive changes in urban fringe land-use patterns.It has also had considerable environmental and socio-economic impacts on these areas.Assessing changes of the past land-use patterns and simulation of their future changes are of vital importance inpolicy making and planning processes. Combination of geographic information system (GIS) and remote sensing (RS) may producea suitable tool for gathering and analyzingdata regarding land use changes. This articleuses the CA-Markov model to assess and simulate changes in land use patterns in Miandoab city.In the first stage, by using the multi-temporal satellite imagery for the years 1984, 1997 and 2010, the urban and urban fringe cover/land-use maps was created and changes was evaluated. Results indicate thatin the period of 27 years, urban and urban fringe land area increased to 1013 hectares and farm land-use area decreased to 1114 hectares. Then, by using Markov model, matrix of transition area of land-uses for the period of 1984-2010was calculated. In the next stage, the suitability maps of land-uses by using of mulicriteria evaluation methods were created. Finally, for forecasting the future changes of land-uses until the 2025 year, we used the CA-Markov model. Simulation results, indicatethat thedecline trend in farm lands and the trend increase in urban lands will continue. Therefore, if the current trend of changes continues without a sustainable development policy, it will have to a serious downfall in environmental and socio– economic conditions.
Urban Planning
Ahmad Pourahmad; Heydar Salehi Mishani; Leyla Vothoogi; Ahmad Roomiani
Volume 19, Issue 54 , February 2016, , Pages 83-103
Abstract
Increase in urban population changes agricultural lands to residential, commercial and industrial uses. These changes have unfavorable consequences including loss of vegetation cover on the urban environment. Ambient temperature and high-quality agricultural lands have been destroyed. In In this regard ...
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Increase in urban population changes agricultural lands to residential, commercial and industrial uses. These changes have unfavorable consequences including loss of vegetation cover on the urban environment. Ambient temperature and high-quality agricultural lands have been destroyed. In In this regard one of the strategies that optimizes the physical fabric of urban and reduces environmental damage is the use of modern techniques of remote sensing which plays an effective role in the management and the improvement of urban land use. This paper aimed to evaluate and optimize physical growth of Urmia to maintain vegetation and agricultural lands developed. Therefore, changes in land use Urmia, between 1985 and 2011 were calculated. Reviews indicate a sharp decline in agricultural lands and orchards in the area. So as using AHP descriptive model we found that in order to satisfy the requirements of urban development five categories should be considered: From very suitable to very poor groups. The results showed that over 21.5ha of the area, (i.e. 5.08%) have suitable conditions for the intended purpose.
Abolfasl Ranjbar; Mohammad Saadi Mesgari
Volume 16, Issue 42 , March 2013, , Pages 155-171
Abstract
The population growth, industrial development, bio-climate changes and scarcity of land resources are the main reasons and causes of forest degradation in developing countries. To control and decrease forest degradation, the governments need to know where, when, how fast, and why (with what causes) such ...
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The population growth, industrial development, bio-climate changes and scarcity of land resources are the main reasons and causes of forest degradation in developing countries. To control and decrease forest degradation, the governments need to know where, when, how fast, and why (with what causes) such degradations happen. On the basis of such knowledge, a general and sustainable management of these resources will be possible.
The science and technologies of GIS and remote sensing could be a perfect tool for answering the above questions. Remote sensing can be the basis of fast and inexpensive data collection and the analytical capabilities of a GIS can be used for analyzing the types, location and rates of changes.
In this research, the Landsat TM and ETM+ images of years 1987 and 2001 are used for land use classification and analysis of changes at the forest area of Arasbaran in north-west of Iran. The classification is mainly aimed at the separation of forest from non-forest areas.
A few methods have been studied to calculate and show the occurred changes. These include methods that only describe the change areas (such as subtraction and division methods) and those that describe the area, amount and type of the changes (such as comparison after classification).
By classifying the forest and non-forest areas of years 1987 and 2001 and overlaying them, a map was extracted representing the stable forest area and deforested area. From the topographic data of the study area, some other raster maps were created showing elevation, slope, aspect and distance from population areas.
Information of these maps were entered into a statistical model (a logistic regression model) having the above-mentioned classified map as the dependent parameter and all other maps as the independent parameters. It was resulted that the parameters of distance from populated areas, elevation and aspect have a meaningful relation with the deforestation phenomenon. From such an analysis, the importance of each factor in the phenomenon was defined and the areas that are in higher risk of deforestation and need an urgent protection were defined.
Saeed Jahanbakhsh; Majid Zahedi; Khalil Valizadeh Kamran
Volume 16, Issue 38 , February 2012, , Pages 19-42
Abstract
In a wide variety of scientific climatology studies earth surface temperature, is important, Astronomy, meteorology hydrology, ecology, geology, medical science, design and optimization of transportation network and site selection of fire extinction and particularly cases required. In the calculation ...
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In a wide variety of scientific climatology studies earth surface temperature, is important, Astronomy, meteorology hydrology, ecology, geology, medical science, design and optimization of transportation network and site selection of fire extinction and particularly cases required. In the calculation of the actual evapotranspiration also we consider these.. Considering the earth's surface temperature monitoring in a limited number of meteorological stations to the distribution point and the need to place the surface temperature in a wide area and at the same time the surface temperature were estimated. To access the earth's surface temperature and classification SEBAL algorithm and decision tree were used. Using ETM + image dated 31 August 2000 and pre- process, files became ready for implementation. For processing of SEBAL method. the above mentioned software Envi4.5 and ArcGIS9.3 were used. This paper estimates the difference less than 5.57° C, temperature difference between a satisfactory level was estimated through remote sensing and statistics. Temperature measured from ground level 12 years (1993 - 2005) in Maragheh meteorological station was achieved. Temperature was estimated through remote sensing and studies applicable in earth sciences research and the environment.
Reza Valizade
Volume 16, Issue 38 , February 2012, , Pages 179-202
Abstract
Earth surface temperature has been used in a wide variety of scientific studies including climatology, astronomy, meteorology, hydrology, ecology, geology, and medical sciences. The design and optimization of transportation network and site selection of conflagration and particularly in the calculation ...
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Earth surface temperature has been used in a wide variety of scientific studies including climatology, astronomy, meteorology, hydrology, ecology, geology, and medical sciences. The design and optimization of transportation network and site selection of conflagration and particularly in the calculation of the actual evapo-transpiration we require such data. Considering the earth's surface temperature monitoring in a limited number of meteorological stations to the distribution point we need to place and estimate the surface temperature in a wide area, and at the same time the surface temperature. To access the earth's surface temperature and classification the SEBAL and decision tree algorithm was used. Using ETM+ images dated 31 August 2000 and pre-process, files were ready for implementation of SEBAL method. Processing of the above mentioned software was through Envi4.5 and ArcGIS 9.3. This paper estimates the temperature differences if less than 5.57°C between a satisfactory level through remote sensing and statistics, while we estimated temperature measured from ground level for a period of 12 years (1993-2005) at Maragheh meteorological station. Results indicate that temperature estimates through remote sensing and such studies are applicable for earth science research and the environment.
