Showing 9 results for Remote Sensing
Moslem Seydi, Kamal Omidvar, Gholamali Mozafari, Ahmad Mazidi,
Volume 0, Issue 0 (3-1921)
Abstract
Abstract
Climate change is an important environmental issue because the melting processes of glaciers and snow density are sensitive to climate change. Today, a variety of satellite sensors such as AVHRR, MODIS, GEOS, MERIS are available for snow monitoring and are widely used to investigate and investigate the fluctuations and changes in snow cover globally. Modis sensor has been considered more because of its global spatial coverage with suitable spatial accuracy and frequent temporal coverage on different scales , Therefore, in the present study, snow products of this sensor were used. In this study, after collecting statistics and data on snow-related days during the statistical period (1989-2018) in three provinces of Kermanshah, Ilam and Lorestan, they were processed using Modis snow cover data in middle Zagros as well as remote sensing techniques, Finally, the snow cover changes in the study area were studied in detail. NDSI index was used in MODIS sensor products to detect snow cover. Consequently, in order to differentiate pixels and identify different phenomena, the received images were processed in GIS environment. . Investigation of snow cover changes in different seasons using Modis sensor images shows that most of the studied area has a significant decreasing trend, especially in the elevated areas of the study area And only in the western and southwestern regions of the study area, there is no specific decreasing trend. Also, the study of snow covered days during the study period indicates a decrease in middle Zagros snow cover and these changes have been intensified in recent years, especially in snow-covered areas of the region. Also, changes in winter and snow-capped and elevated areas were more and more severe than other seasons and other regions in the study area.
Tahereh Karimi, Amir Karam, Parviz Zeaiean Firuzabadi, Seyyed Mohammad Tavakkoli Sabour,
Volume 0, Issue 0 (3-1921)
Abstract
Abstract
The catchment area of Alamut River in Qazvin province is witnessing numerous landslide hazards and landslides every year, which cause significant economic and sometimes life-threatening losses. Diagnosing the unstable areas of slopes through soil texture characteristics is a difficult task due to the difficulties of obtaining soil samples in mountainous areas. For this reason, in the present study, by using Sentinel A1 radar data, by determining the percentage of clay and sand in the soil, the soil texture map at the depths of 10, 60, 100 and 200 cm with two random forest (RF) and support vector machine (SVM) algorithms was produced in the eastern Alamut region, which was verified with soil profile samples. The results indicated that the Kappa index was more accurate in the RF model at three depths of 10, 60 and 100 cm. Then, by extracting the soil moisture map from Sentinel 2 data, at the same time as examining the internal friction angle of the types of soils in the region, comparing the slope and profile of the slopes and the shape of the convex (divergent) and concave (convergent) slopes, the unstable areas of slope movements, RF and SVM models were specified and validated with GPS data, field visits and Google Earth. Research findings show that the instability map resulting from the RF model has a higher accuracy (AUC=0.93) than the instability map resulting from the SVM model (AUC=0.90) and there is more instability in areas with medium to high slope and with soil texture of sandy clay loam and sandy loam. . This method has many advantages in preparing the soil texture map, determining the unstable areas of the slopes against mass movements and landslides, determining the vulnerable areas in mountainous areas and reducing financial and human losses.
Mohamad Reza Mobasheri:, Samira Ranjbar,
Volume 17, Issue 44 (6-2017)
Abstract
The goal of this study is to identify farms which are affected by wheat rust disease. For this, the sensor data of Landsat 7 satellites in growing season of 2013 and 2014 along with some laboratorial data containing reflectance spectrum of leaf and leaf health degree in different levels of disease are used. The reflectance values of leaf are collected by an ASD spectroradiometer in the range of red and near infrared spectrum. The spectral are simulated for Landsat sensor bands using their spectral response functions. Then with the index of DVI and data obtained for leaf health, the Wheat Health Index was introduced. The correlation coefficient obtained is 0.82 and the relevant RMSE is 0.089 which is really good result for diagnosing highly advanced disease. The results show that, this index has a good performance in wheat high growing season when the greenness is high. It can diagnose regions that are healthy from those whom are blighted. Because the WHI index is a spectral index and is sensitive to leaf color, if the acquired images are close to the harvesting time, its performance will be weakened. The selected region in this survey is located in Fars, province, Saadatshahr city.
Mr Soleiman Pirouzzadeh, Mahmood Khosravi, Samad Fotohi,
Volume 19, Issue 52 (3-2019)
Abstract
Studies show that 14 provinces are impacted by wind erosion and the movement of sand dunes. The sand originated from the shores of Oman Sea is the most important environmental hazards that threaten the already large number of rural settlements. Sands of marine origin are available on the beach and away from the sea of dunes in addition of marine origin, Predictive models for planning sustainable use of land use and land cover in a country like Iran that land use is changing rapidly, there is an urgent need; To detect and predict changes in land cover changes overview to better manage natural resources and protect marginal lands beaches and is very effective long-term policy measures. The aim of this paper is modeling and prediction of changes in land-use in 2035 by using CA Markov model and Landsat satellite images in the West of Zarabad,( The coasts of Makran). Then to determine the changes in the movement of sand dunes in the study area ranged from twenty-three years (1991-2014), satellite imageries from Landsat 7 and 8(ETM+ sensor) with 15 and 30 meters spatial resolution , was used. The 1991, 2001and 2014 month August images were used, this images from website of the US Geological Survey (USGS) have been prepared. Finally, these images by using Geographic Information System (GIS), ENVI and IDRISI softwares were analyzed. The results showed that the changes in the region the largest increase in the interest of sand dunes in the year 1991 (25.561) km², in 2001 (10 . 568) km², and in 2014 (45.578), and the increase of (17.198) km², has experienced. The results also estimated that in future (2035) sand dunes area increase to 592.45 km².This increase in area of sand dunes occur in the absence of proper and efficient management is done in order to stabilize the sand. This increase resulted from changed moorland 162 km²of land area (27%) and 12 kilometers of vegetation (2%) and 23 km² of fluvial (3.4%). These changes makes heavily exposed about 6 villages (Karti,Gnjk, Sohroki, Pyvshk, Vanak and Kalirak) to the movement of running sands.
Mehdi Asadi, Khalil Valizadeh Khamran, Mohammad Baaghdeh, Hamed Adab,
Volume 20, Issue 59 (1-2021)
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.
Hooshang Seifi,
Volume 21, Issue 63 (2-2022)
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.
Bhroz Sobhani, Fatemeh Nasiri,
Volume 22, Issue 65 (6-2022)
Abstract
Recognition and determination of ecological susceptible regions for proper bedding is importance and vital affair for regional planning and specially agriculture part. Climate and topography are main environmental components which altitude and cultivation product generation capability are depend their in every region. So , studying of effective climate factors and elements on agriculture have special importance. In current study , in order to agriculture ecological homogeneous geographical regions determination ; satellite images of Geographical Information Bases (GIS) were used which they are provider of new horizon and dimensions for effective discovering and fields resources management and we try to show Rapeseed cultivation ecological zoning usage development by combining modern tools , instruments and methods at Ardebil plain region. In order to recognition of mentioned susceptible regions in studied case climate data statistics were used that they include ; temperature degree , precipitation, relative humidity and environmental capability data such as ; inclination, height and multi-criteria decision making based on Analysis of Networks Process(ANP). Then layers were prepared by weighting and according to criteria and they were combined and also layers overlapping were done on GIS environment and ultimate layer of fields proportion was prepared for Rapeseed cultivation. Based on results analysis , studied region fields for Rapeseed cultivation include 33/38% without limitation ; 02/10% of fields with low limitation; 96/33% with medium limitation ; 71/17% of fields with high limitation
Mohsen Pourkhosravani, Ali Mehrabi, Behnaz Shaikhshariati,
Volume 23, Issue 68 (4-2023)
Abstract
Solar energy is receiving lots of attention because it is one of the cleanest, cheapest and most available energies in the world.but solar radiation in different parts is changing, thus, identifying appropriate locations for implementation of solar energy is necessary. Accordingly the aim of this study was to analyze the potential of solar radiation and land surface temperature on the Loot desert using remote sensing and geo statistical technique. Results show that Earth's surface temperature fluctuates between 29 and 79 degrees Celsius in the Lut Plain. So that Earth's temperature increases to the east and north-east of the region. Also, the radiation energy reaching the surface in the Lut plain varies from 232.77 to 237.61w/m² in different parts of the Lut plain. So that the maximum amount of energy is related to the south of the plain, and the further we move to the north reduces the amount of energy.
Nasrinalsadat Bazmi, Zahra Hejazizadeh, Parviz Zeaiea Firoabadi, Qholamreza Janbazghobadi,
Volume 23, Issue 70 (10-2023)
Abstract
This article was written with the aim of revealing land use changes in Urmia city using remote sensing of Landsat satellite images for 4 periods of 8 years between 1990 and 2019. For this purpose, two categories of data will be used in this research. The first category includes data obtained from satellite images and the second category includes ground data taken from Urmia ground station, which includes temperature and other parameters used in this research. The results showed that urban land use in Urmia city has faced significant changes during the statistical period of 30 years. This user has had an increasing trend during all the studied periods, so that during the study period, it has faced a 5-fold increase. Swampy areas and sludge fields east of Lake Urmia have undergone a significant decline during 1990-2019 and has reached less than 6,000 hectares. The citychr('39')s barren lands, which cover a small percentage of the citychr('39')s area, have been declining over the 30-year period under review. The use of gardens has increased during all periods, so that in 2019, its area has reached more than 20,000 hectares. The use of irrigated agriculture has increased during all the studied periods and its area has reached more than 80,000 hectares by 2019. The area of rainfed agricultural lands, after the rangelands, is the widest land use in Urmia, but with a relatively gentle slope has a decreasing trend. Water areas have also been declining, so that in 2019, it has decreased by about 26% compared to 2012. Rangelands, which is the largest land cover in Urmia city, has gone through three different processes during the study period. From 1990 to 1998, these lands did not change significantly, but from 1998 to 2005, the increasing trend and in 2019, with a 10% decrease compared to 2012, reached its lowest area during the statistical period under study, ie less than 20,000 hectares.
