Mrs. Zeinab Zaheri Abdehvand, Dr. Mostafa Kabolizadeh,
Volume 0, Issue 0 (3-1921)
Abstract
In vast areas, the possibility of simultaneous access to satellite images with appropriate spatial resolution, such as Landsat images, is always a challenge. In addition, the temporal resolution of the Landsat satellite does not provide the possibility of examining short-term changes in phenomena such as vegetation. The aim of this research is to use the temporal and spatial fusion techniques of Landsat-8 and MODIS satellite images in preparing the Normalized Vegetation Detection Index (NDVI) map. For this purpose, six image fusion algorithms, including NNDiffuse (Nearest Neighbor Diffusion), PC (Principal Component), Brovey, CN (Color Normalized), Gram-Schmidt, and SFIM, have been used in an experimental area in Khuzestan province. After evaluating the results of the algorithms and choosing the most appropriate fusion algorithm, based on the statistical indicators of the spectral (correlation coefficient) and spatial (Laplacen filter) criteria of each of the algorithms, the spectral and spatial information of the reflection of red and near-infrared of 8 mosaicked Landsat-8 images (30 m) were combined with the red and near-infrared bands of one MODIS image (250 m). In order to investigate the vegetation cover, the NDVI was prepared with the fused satellite image in the Khuzestan province. The results of the research have shown that the NNDiffuse integration fusion algorithm has a very good accuracy among other algorithms in terms of the spatial evaluation index and spectral quality criteria. Therefore, this algorithm was recruited to combine the red and near-infrared bands of Landsat-8 and MODIS images. Compared to the original Landsat-8 image, the NDVI map prepared by this algorithm has the lowest statistical error of RMSE (0.1234) and MAE (0.081), respectively.
Dr. Mostafa Kabolizadeh, Dr. Sajad Zareie, Mr. Mohammad Foroughi Rad,
Volume 0, Issue 0 (3-1921)
Abstract
| There are various indicators to monitor and management of agricultural water resources in arid and semi-arid countries including Iran, some of which can be extracted directly in situ, and some can be retrieved using remote sensing technology and satellite images. Aim of this study is to propose the most appropriate and efficient indicators of agricultural water resource management for achieving maximum production and maximum water efficiency using remote sensing technology, therefore, Crop Water Stress Index (CWSI) and Surface Energy Balance Algorithm (SEBAL) were used to estimate Evapotranspiration (ET). In the first step, ET rate was calculated using SEBAL algorithm for six Landsat 8 satellite images related to the wheat growth period. Then, zoning of this index was done in the range of zero to one, in four categories of very low, low, medium and high, which respectively indicate the lowest to the highest amount of ET. In next step, CWSI was calculated based on Idso equation, and its results show different changes both in cold season and in warm months. Comparison of ET and CWSI shows a significant relationship between these two indices in warm months, while in cold months, no significant relationship can be seen. These findings along with the established relationship between ET and CWSI can inform water management strategies in arid environments for sustainable crop production. |
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Mahrookh Ghazayi, Nazfar Aghazadeh, Ehsan Ghaleh, Elhameh Ebaddyy,
Volume 0, Issue 0 (3-1921)
Abstract
Lack of surface water resources has led to uncontrolled abstraction of groundwater in many parts of the world and severe depletion of groundwater table levels. With the increasing population, the extraction of these resources has increased and these natural reserves are facing a serious threat. The present study was conducted to monitor the groundwater level using satellite images and the relationship that it can have with land use. In order to achieve the desired result, first the relevant satellite images were taken, and the necessary pre-processing was applied on each of them. Among the important tools, the use of object-oriented method, land use classification map was extracted for both years and Land use change map was extracted for a period of 15 years (2000-2015). Finally, in order to monitor the groundwater level map, the groundwater level map of the study area for both years was extracted by Gaussian method, which was the most accurate method. The results showed that there is a strong and significant relationship between land use and groundwater level. Areas of the study area that have higher vegetation have lower groundwater levels than other areas. It follows the earth and also causes water to flow from high potential points to these points. Also, irrigated agricultural use had the highest average drop in water level compared to other uses, which indicates the excessive use of groundwater to irrigate irrigated agricultural products in the study area.The results also showed that the conventional kriging method with Gaussian variance is more accurate than the other methods used to estimate the depth of groundwater water table in both statistical periods. Conveying by conventional kriging method showed that the groundwater level in most parts of the plain has decreased during the study period. The maximum drop is 40 meters and the average is 15 meters.
Dr Fariba Esfandyari, Mr Ehsan Ghale, Ms Maryam Mohamadzadeh Shishegaran,
Volume 0, Issue 0 (3-1921)
Abstract
One of the dangers that has occurred in many areas in recent years is the dangers of subsidence. Iran's geographical location has put many of its regions at risk. High precision radar interferometry technique is one of the most suitable methods for detecting and measuring subsidence. In this study, in order to identify and measure subsidence in Ardabil plain, the Sentinel 1 radar image interference technique of 2015 and 2020 has been used. In order to verify, the data of piezometric wells and land use maps in the area were used. According to the results, the maximum subsidence rate in 5 years in the region is estimated at 17 cm. The results also showed that the highest subsidence rates in the period 2015 to 2020 are in the next categories of rangeland uses with a value of 17 cm, soil value of 14 cm and rainfed agricultural and residential areas with a value of 13 and 12 cm. respectively, 12 cm subsidence for residential use can be due to demolition and construction of large buildings. Also, the relationship between subsidence and changes in groundwater level showed that in a period of 5 years, the groundwater level has decreased by 4 meters. This drop in groundwater level has led to land subsidence in the study area.
Ms Zahra Sharghi, Dr Mostsfs Basiri, Dr Mahsa Faramarzi Asl,
Volume 0, Issue 0 (3-1921)
Abstract
The basic purpose of this research is to reveal the physical development process of the new city of Sahand, as one of the new cities of the country, using Landsat satellite images during the statistical period of 1401-1373. In this regard, satellite images required for 4 statistical periods of 1373, 1383, 1393, and 1401 were obtained from two Landsat 5 and 8 satellites. By running a band calculation function on the images of TM and OLI sensors, the values of the physical changes of the urban fabric during the investigated time steps in Sahand city were calculated and extracted. The results of this research indicated that the physical growth and development of the city of Sahand has started since 2013. This year, the area of the urban fabric has reached 282 hectares, which is a 28-fold increase compared to 2013. But in the next decade, i.e. 2013, the area of the city reached 570 hectares with a 100% growth compared to the previous decade, and finally, in the last decade, the area of the city reached 850 hectares with a growth rate of 50%. District 6 of Sahand city, which accounts for about 35% of the physical fabric of the city, has been one of the fastest growing areas of the city during the decades of 1393-1400. Considering that a significant correlation at the confidence level of 0.95 (P_value=0.05) was revealed between the population growth and the physical development of Sahand during the statistical period of 1380-1400 (R=0.91), therefore, the fitted regression model between the population growth And the growth of the urban fabric, by placing the proposed population density of this city after the implementation of Mehr housing policies (185 thousand people), it showed that the area of the physical fabric of this city will reach 1181 hectares in the next decade and will face a growth of 38%.
Dr Mohammad Motamedi Rad, Dr Reza Arjmandzadeh, Dr Ebrahim Amiri, Mr Farzad Amiri,
Volume 0, Issue 0 (3-1921)
Abstract
| The continuation of drought and the simultaneous increase in dependence on underground water sources in the past decades have expanded the range of areas subject to subsidence to many different parts of the country, which results in a lot of damage.In order to reduce the damages caused by land subsidence, it is necessary to have a complete and accurate understanding of this phenomenon. In recent decades, the virtual aperture radar (SAR) interferometric technique has become a common method for measuring subsidence. In this research, field data such as piezometric wells and groundwater drop in the minimum and maximum periods and exploitation wells were used to calculate the amount of discharge in the aquifer using IDW interpolation, aiming at analyzing the time series of the subsidence of the Esfarayen plain. besides, radar data including Sentinel 1 images were used to calculate the subsidence rate in the first 8 months of 2023. The results of the research show that the amount of subsidence in the study basin was from 1 to 12 mm in a period of 8 months and 75.2% of the area of the basin was in the medium critical and very critical zone, which can be recognized based on this. He showed that the Esfrain plain is in a critical state.The most water extraction and subsidence has been related to to south of Sankhasat, south of Kharasha, south of Arg, south of Gazan, Jafarabad Kharaba and Mehdiabad of Kal Beko wells, which are located in the very critical area and require efficient management of groundwater resources in order to control land subsidence. |
Alireza Yousefi, Mahdiyeh Shahabinejad, Amimozafar Mini,
Volume 15, Issue 37 (9-2015)
Abstract
Agricultural sector has an important role in development of countries. One of the obstacles to development in this sector, especially in Iran is significant fragmentation of agricultural lands. The aim of this study is to assess the farmers’ willingness to participate in land consolidation project using structural equation modeling. The population of this study consists of all farmers of Meymeh County and its surrounding cities and villages and Niloofar-Abi cooperative of Vazvan city. Data were collected on a sample of 156 farmers through face-to-face interviews based on a comprehensive structured questionnaire. Before the survey, the reliability and validity of questionnaire was initially evaluated on a pre-test study respectively by using Cronbach’s alpha coefficient, expert’s judgment and Kaiser-Meyer-Olkin (KMO) criteria. The results of this study show that the most important factors on farmers' willingness to participation are crop acreage and number of plots which respectively has the greatest positive and negative effect. The awareness of the farmers about benefit of consolidation project is another factor which has significant and positive impact on farmers' willingness. Furthermore, level of farmers schooling has no significant effect.
Sadegh Asghari, Gharib Fazelniya, Morteza Tavakoly, Marzie Shoghi,
Volume 15, Issue 37 (9-2015)
Abstract
Sustainable development is an environmental concept appropriate to our era that nowadays in all of economic, social, environmental and physical-spatial aspects is considered and focused by everyone. In these times, global organizations that are working around the issues of sustainable development, emphasis on rural sustainable development, which seeks to improve rural living standards and welfare of the inhabitants of the villages, because at present time, the procedure of socio–economic variations accompanied by increasing migration of human groups is led to evacuation of villages. With attention to the importance of the subject and the increasing instability of the villages, present study was done for determining the effective factors on rural instability and measuring the intensity of this instability in Kaki District of Dashti Township. The research method is descriptive - analytical in which whole inhabited villages of Kaki District of Dashti Township were surveyed. In this regard, according to the number of households living in villages and using the Cochran formula, 255 questionnaires were calculated for questioning andthese questionnaires have been completed in the villages in proportion to the population of each village. In these questionnaires, 34 indicators related to the four dimensions of sustainable development (environmental, social, economic and physical-spatial) are considered. In order to determining instability intensity of the villages and their spatial analysis, is used AHP method in Expert Choice and ArcGIS software. Also SPSS software is used for statistical analysis. The results show that at the present time, all villages have various degrees of instability. In this regard, 65.8 percent of these villages have severe or very severe instability.
Mohammad Hajipour, Vahid Riahi, Hadi Gharagozloo,
Volume 15, Issue 37 (9-2015)
Abstract
Housing enjoys a multilateral functioning in the rural system. One of the aspects highlighted by planning system is the renewal and rehabilitation of housing. In our country, Iran, development of rural housing has experienced a growing trend, especially in the physical and structural aspects. However, a large part of the rural population in different areas of the country is living in non-resistant and less durable housing. This article attempts to analyze the spatial distribution and quality of rural housing in the country. In this article it is tried to address and analyze the spatial distribution of quality and construction of rural housing in various provinces in the country. The data was derived from document studies. The quality of rural housing in 9 indices has been measured for each province of the country. Data has been analyzed using VIKOR method for the multi-criteria decision analysis. Finally, the classification of provinces based on the construction and quality of rural housing was conducted using K cluster analysis in SPSS and output was drawn in GIS as a map. The results showed that there is a significant difference and distinction in the types of materials used in the rural settlements. Such that a significant percentage of the houses are made out of bricks, iron and stone that somehow confirms the durability and normal quality. In terms of spatial and local distribution it can also be said that the quality of rural housing in most of the provinces (i.e. 24 provinces) are in low-quality, medium and/or appropriate levels. Meanwhile, only three provinces of Mazandaran, Azerbaijan Sharghi and Kerman enjoy the excellent quality in rural housing construction.
Bakhtiar Feizizadeh, Ali Khedmat Zadeh, Mohammad Reza Nikjoo,,
Volume 18, Issue 48 (3-2018)
Abstract
Remote sensing technology is one of the most efficient and innovative technologies for agricultural land use/cover mapping. In this regard, the object-based Image Analysis (OBIA) is known as a new method of satellite image processing which integrates spatial and spectral information for satellite image process. This approach make use of spectral, environmental, physical and geometrical characteristics (e.g. texture, shape) together images contexts for modeling of land use/cover classes. The main objective of this study is to classify micro land use/cover of Meyandoab County by applying appropriate and effective algorithms and parameters in the object based approach. For this goal, Quick Bird and Aster satellite images were used within the integrated approach for processing and land use modeling. Accordingly, the land use map was classified in 9 class based on spectral and spatial characteristics. In order to perform OBIA, the segmentation was applied in the scale of 10, shape parameter of 0.7 as well as the compactness of 0.3. In terms of the classification task, fuzzy based algorithm and operators (AND, OR) was applied to detriment the membership functionality of segments for each class as well as classifying the related objects. We also applied textures, geometric, NDVI, GLCM, brightness algorithms based on fuzzy operators and assign class algorithm. In order to applying the validation of results, the accuracy assessment step was performed and the finally overall accuracy of 93.6 was obtained for the derived map. The Kappa coefficient was also detriment to be 0.92. The area under cultivation included respectively for lands of wheat and barley, prunes and plums, apples, vineyards and alfalfa hay2622.42, 4505, 4354.55, 4457.85, 14110.58 hectares.
Adel Nabi Zadeh Balkhanloo, Zahra Hejazizadeh, Parviz Zeaiean Firoozabadi,
Volume 18, Issue 50 (3-2018)
Abstract
Continuous decline in Lake Urmia water levels In recent years, the decline of rainfall and river flows and constant droughts has become the main concern of the people and the people. To study climate change and increase of temperature in the catchment area of Lake Urmia, two factors for measuring the temperature and properties of satellite images were used which indicate the importance of land surface temperature changes (LST) and normalized vegetation differences (NDVI). This study was carried out using the satellite data of the periodic watershed (2008-2008) to investigate the spatial relationship between NDVI-Ts and NDVI-ΔT to investigate the actual agricultural drought occurrence. The goal is to extract the VTCI (vegetation temperature index) index, which is capable of identifying drought stress at regional scale. The results showed that the slope is negative for the warm edge, where it is positive for the cold edge. The gradient gradient shows that the maximum temperature is reduced when the NDVI value increases for any interval. The slope on the cold edge indicates that the minimum temperature rises when the NDVI value rises. Overall, at the warm and cold edges, it has been observed that the drought trend over 2009-2008 is higher than in 2010. In the days of Julius Day 257, the slope of the cold edge from 2008 to 2010 is decreasing. But at the hot edge, intercept pixels for 2008 is more than 323 degrees Kelvin, where in 2009-2010 it is less than 323 degrees Kelvin. In general, the correlation coefficient (R2) is different in the TS-NDVI spacing between (0.90-0.99). The present study showed that with the integration of satellite satellite data with meteorological data, the VTCI threshold for drought stress varies from year to year depending on the data conditions.
Dr. Ali Bayat, Mr. Saeed Mashhadizadeh Maleki,
Volume 19, Issue 53 (6-2019)
Abstract
Precipitable Water Vapor (PWV) is one of the most important quantities in meteorology and climate studies. PWV in Earth's atmosphere can be measured by Sun-photometer, the Atmospheric Infrared Sounder (AIRS), and radiosonde from surface, atmosphere and space-based systems, respectively. In this paper, we use PWV measured by Sun-photometer located in Institute for Advanced Studies in Basic Sciences (IASBS), AIRS and 29 Iranian synoptic stations data include temperature, dew-point temperature, pressure and relative humidity. For validation of AIRS data, the correlation coefficient between AIRS and Sun-photometer data calculated. The correlation is 90%. Average of PWV measured with sun-photometer and AIRS are 9.8 and 10.8 mm, respectively. Pearson's correlation coefficients between PWV of AIRS data set and temperature, dew-point temperature, pressure and relative humidity for synoptic stations are calculated. Correlation between PWV and temperature, dew-point temperature, pressure, and humidity are 73%, 74%, -40% and -30%, respectively. PWV and temperature correlation coefficient map shows a positive trend between latitude and correlation coefficient. Rising a degree in latitude lead to increasing 2.8 percent in the correlation coefficient.
Dr Sayyad Asghari, Hadi Emami,
Volume 19, Issue 53 (6-2019)
Abstract
Earth surface temperature is an important indicator in the study of energy equilibrium models at the ground level on a regional and global scale. Due to the limitation of meteorological stations, remote sensing can be an appropriate alternative to the Earth's surface temperature. The main objective of this study is to monitor the surface temperature and its relationship with land use, which is monitored using satellite imagery. For this purpose, the images were first obtained and the necessary pre-processing was applied to each one. Then it was compared to modeling and classification of images. Firstly, in order to investigate the changes in user-orientation, a user-defined classification map for each object was extracted using the object-oriented method. Then, to investigate the land use change, a map of user-landing changes map was extracted in an 18-year time period (2000-2017). Finally, in order to monitor the surface temperature, the surface temperature map of Ardebil was extracted. The results showed that there is a strong relationship between land use and surface temperature. As a user, urban users have a temperature of about 41 ° C (2017), which is also due to heat-absorbing urban temperatures. This is despite the fact that the use of hydrocarbons is due to a lower heat absorption of 34 ° C (2017). This shows the role of different uses in determining surface temperatures. Also, the relationship between surface temperature and vegetation cover was investigated in this study. The results showed that areas such as soil and urban areas with a lower coverage than areas such as agriculture and pasture, have a higher temperature. Because the coating is always an obstacle to the entry of heat, it has an inverse relationship with superficial heat.
Dr Mohammad Ebrahim Afifi,
Volume 20, Issue 56 (3-2020)
Abstract
Land use maps are considered as the most important sources of information in natural resource management. The purpose of this research is to review, model, and predict landslide changes in the 30-year period by LCM model in Shiraz. In this research, TM Landsat 4, 5 and OLI Landsat 8 images were used for 1985, 2000 and 2015 respectively, as well as topographic maps and area coverage. Subsequent validation and detection of changes were made using the prediction model of variation The use of LCM markov and the model of user change approach. The images were classified into four classes of Bayer, garden, urban lands, and arable land for each of the three periods. According to the results, aquaculture is the most dynamic user in the area, which has led to an upward trend during 1985-2015, so that the amount (4337 ha, 12.7%) has been added to this area. The Bayer user change trend was also a downward trend during 1985 to 2015, reducing the 99.1995 hectares of this class. The results of the change in the 1985 changes with a kappa coefficient of 0.88, in the 2000 period with a CAAP of 0.77, and in the period 2015 with a Kappa coefficient of 0.92. The results of the change detection in 2030 are such that if the current trend continues in the region, 20.33% will be added to the crop category, so that in 2030, agricultural cropping will be 95.60% of the area of the area Gets In the Bayer and Garden uses 21.22% and 0.21% of the total area of each user has been reduced and has been added to the urban area. The prediction map derived from the Markov chain model is very important for providing a general view for better management of natural resources.
Dr Sayyad Asghari, Roholah Jalilyan, Dr Noshin Pirozineghad, Dr Aghil Madadi, Milad Yadeghari,
Volume 20, Issue 58 (9-2020)
Abstract
Water is one of most important human needs for life. According to importance of subject, discussion of management and utilization of water resources has become one of the most important global issues. Remote sensing data are often used in water body extraction studies and type of remote sensing data used plays an important role in water body extraction. In this study, ability of Landsat satellite with application of water indices, to extraction of Gamasiab River in Kermanshah and comparing these indices have been investigated. Specific feature of Low width and shallow rivers has increased the complexity of studies of such rivers using available data. Water body extraction from remote sensing images has been over the past two decades. Water indices were first developed using Landsat TM and Landsat ETM. But its better performance in Landsat 8 is well documented by the researchers. In this study, NDWI, MNDWI, AWEI_nsh, AWEI_sh and WRI indices were used. With extracting optimal threshold from histogram of indices and applying this threshold, the study area was classified into two classes of water and non-water. Then overall accuracy and kappa coefficient values were taken from each of the indices. Finally, AWEI index with overall accuracy of 99.09% and a Kappa coefficient of 0.98 was the best response among the indices in the study area. The results this study showed that approach can easily extract water from satellite imagery.
Mrs. Atefeh Shahmohammadi, Dr. Ali Bayat, Mr. Saeed Mashhadizadeh Maleki,
Volume 20, Issue 58 (9-2020)
Abstract
Urban development and air pollution are among the most important issues related to climate. The expansion of urbanization and urban development, population growth, industrial development and excessive use of fossil fuels significantly increased air pollution and it is more than the capacity of the environment. In our country, the emissions of air pollutants in some metropolitan areas have reached a dangerous level, Mashhad is considered to be the most polluted cities of the country in some days of the year. Nitrogen dioxide is one of the indicators of air pollution. In this study, the OMI data and atmospheric parameters such as wind, surface temperature, and horizontal visibility data for the period from 2004 to May 2016 were used to investigate the air pollution in Mashhad. The results show that the maximum (minimum) nitrogen dioxide levels occur in the cold (hot) season. The highest amount of nitrogen dioxide in January is equal to 5.56 × 1015 molec/cm2 and its lowest value in September is 4.18 × 1015 molec/cm2. Standard deviation of nitrogen dioxide also indicates that the greatest changes occur in cold seasons. Also, the results showed that the dominant wind in the city of Mashhad is from the south, and most of the winds are slow. Correlation coefficient of nitrogen dioxide with wind and surface temperature is -0.36 and -0.57, respectively, which shows the higher importance of temperature in nitrogen dioxide changes in Mashhad city. The correlation coefficient of nitrogen dioxide with horizontal visibility is -0.15, which indicates that with increasing nitrogen dioxide contamination, horizontal visibility decreases. Spectral analysis of least squares of the six and twelve-month periods of rotation was observed, they were also statistically significant. After eliminating the significant components of the time series of the average monthly nitrogen dioxide, the trend was calculated. The amount of nitrogen dioxide in each year for Mashhad was 2.41 × 1013 molec/cm2.
Mehdi Asadi, Khalil Valizadeh Khamran, Mohammad Baaghdeh, Hamed Adab,
Volume 20, Issue 59 (12-2020)
Abstract
Using Landsat satellite images taken in 2015/08/10 and also SEBAL and metric methods, surface albedo amounts for various land uses in the northern half of the Ardabil province was estimated. ENVI4.8 and ArcGIS10.3 softwares were also used. To determine the type of usage of different levels, the maximum likelihood algorithm classification method was used with Kappa coefficient of 86.14% and overall accuracy of 92.63%. The results indicated that the water levels with the mean value of 0.93 and 0.414, respectively, had the least amount of albedo in SEBAL and METRIC methods. Also, based on the results obtained from SEBAL and METRIC methods the city albedo is about 0.313 and 0.278 respectively. These values are the highest levels of albedo among Land use levels. In this study, the amount of albedo in rangelands was determined to be between 0.183 to 0.266 in the SEBAL method and between 0.237 and 0.265 in METRIC method. The amount of albedo was also examined in agricultural (0.240 based on SEBAL method and 0.247 based on METRIC method) and forest lands (0.149 based on SEBAL method and 0.225 based on METRIC method). Finally, according to the results of Albedo values based on SEBAL and METRIC methods, it was concluded that due to the difference in net energy received at different levels, it is possible to estimate the level of albedo levels, which is very effective in estimating evapotranspiration by remote sensing methods.
Dr Parviz Zeaiean Firoozabadi,
Volume 20, Issue 59 (12-2020)
Abstract
Various satellite remote sensing data, images and products have proven their place in drought, drought and agriculture studies since the production of this type of information resource. Visible, near-infrared and thermal bands are among the most widely used in the production of products such as vegetation and surface temperature. In this study, from MODIS sensor data to investigate and find the coefficients of spatial relationship between vegetation-surface temperature index (NDVI-TS) and NDVI-ΔTS to extract the time of agricultural drought from June to October 2007 to 2010 in the catchment Siminehrood has been extracted from the Temperature-Vegetation Condition Index (VTCI) and the Water Lack Index (WDI), which are able to detect drought stress on a regional scale. The results of this study showed that in both indicators, the drought stress situation was higher in 2007 and 2008. Also based on the NDVI-TS space relationship in all the years 2007 to 2010 the high slope of the triangular space for the hot edge is negative. This means that with increasing NDVI, the LST level decreases while for the cold edge the slope is positive. In addition, the slope obtained from the NDVI-ΔTS space relationship is negative for the dry line, ie the dry line or the minimum transpiration-sweat line (ETR) shows a negative correlation with NDVI. While for the wet line, especially in 2010, the slope is positive and in other years, no significant change is seen. The present study showed that the VTCI threshold for drought stress was severe in 2007 and 2008.
Dr. Ali Bayat, Mr. Ahmad Assar Enayati , Mrs. Azimeh Toshani,
Volume 21, Issue 62 (9-2021)
Abstract
In this paper, aerosol optical depth measured by Caliop, MODIS, MISR, and OMI satellite sensors is compared with Sun-photometer data located in the Institute for Advanced Studies in Basic Sciences (IASBS) from December 2009 to December 2013 over Zanjan city. We computed figures for root mean square error (RMSE), mean absolute error (MAE) and root mean bias (RMB) between space-born and ground-based sensor measurements. The results show that the Caliop and MISR sensors have the highest correlation (0.61 and 0.54), respectively, with Sun-photometer measurements over Zanjan area. MISR, Caliop, and OMI sensors have the closest aerosol optical depth data to the Sun-photometer measurements (the fitted line slope is 0.68, 0.61 and 0.59, respectively) which represents the appropriate model used in the sensors to extract the aerosol optical depth. The variable monthly AOD figures obtained with different sensors indicate underestimation by MODIS and Caliop instruments (0.32 and 0.83 respectively) over Zanjan city relative to the Sun-photometer data, and overestimation by OMI and MISR instruments (1. 23 and 1.08 respectively).
Hooshang Seifi,
Volume 21, Issue 63 (12-2021)
Abstract
It is very matter to study and measure snow covers as one of the important sources of water supply. Due to the hard physical conditions of mountainous environments, there is no possibility of snow measurement. the use of remote sensing with regard to low costs, up-to-date and extensive coverage in this field can be proven to be a good way to identify in snowflake areas. the main objective of this research is to estimate the surface coverage of Sabalan mountains using satellite images of OLI and TIRS sensors and using the object-oriented classification method. The classification of satellite digital images is one of the most important methods for extracting information, which is currently done with two pixel-based and object-oriented processing methods. The base pixel method is based on the classification of numerical values of images, and the new object-oriented method, which, in addition to numerical values, uses content, Texture, and Background information also in the image classification process. Therefore, in the present study based on the precision of the object-oriented classification, the object-oriented techniques were used to extract the surface of snow cover. In this study, due to the use of high resolution spatial resolution (Landsat 8) and the new method of classification of images, the snow surface was characterized by Normalized Difference Snow Index (NDSI), Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), Brightness with a total accuracy of 91 percent, to 2142.62 square kilometers for the range Sabalan mountains have been extracted and the results can be used as alternatives to snowflake stations.
