Farideh Taripanah; Abolfazl Ranjbar; Abbasali Vali; Marzieh Mokarram
Abstract
One of the new and unique sections, especially in internal studies, is the quantitative examination of unevenness. The scientific and quantitative study of topographic position has always been one of the topics that have received little attention in domestic research. So, classification and identification ...
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One of the new and unique sections, especially in internal studies, is the quantitative examination of unevenness. The scientific and quantitative study of topographic position has always been one of the topics that have received little attention in domestic research. So, classification and identification of different morphometrically distinct regions are necessary. Thus, the present study aims to classify landforms in the northwest of Fars province, Kharestan region and investigate its factors affecting. In this regard, the Topographic Position Index (TPI) method was used in the first stage to classify landforms, followed by the CORINE method to determine erosion risk classes. Additionally, Landsat 8 satellite images from June 2017 were used to determine the normalized differential vegetation index (NDVI). The next step was to determine the relationship between different types of landforms and terrestrial factors such as height, slope, slope direction, topographic wetness index (TWI), Terrain Ruggedness Index (TRI) and NDVI. Finally, the status of different landforms was determined based on erosion risk classes. Results showed ten different types of landforms existed within the study area. Small plains (1.18%) were the lowest in the study area, while waterways (27.71%) and high peaks (27.48%) were the highest. The TWI was significantly correlated with landform classes at 95% level. Most of the region (91.71%) had NDVI classes of 0.1 to 0.3. Stream and u-shaped valleys were found to have higher NDVI values. Real erosion risk was classified into three classes: low, medium, and high with areas of 31.14, 31.11, and 37.78%. There were 44, 57, and 59% erosion levels in the low, medium, and high erosion classes, respectively.
zohreh hashemi; Hamid Soodaei zadeh; Mohammad Hossein Mokhtari
Abstract
Land surface temperature is considered a key parameter in the physic processes of land surface at all scales of local to global. In this study, the relationship between land surface temperature with vegetation and soil surface moisture in land uses of Zahak plain of Sistan area was investigated. In order ...
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Land surface temperature is considered a key parameter in the physic processes of land surface at all scales of local to global. In this study, the relationship between land surface temperature with vegetation and soil surface moisture in land uses of Zahak plain of Sistan area was investigated. In order to, Landsat TM (1987), TM (2001) and OLI (2018) satellite imagery were used. After the preprocessing and image processing steps, the extraction of land use maps was performed based on the monitored classification method and through maximum probability algorithm for a period of 30 years. Also, land surface temperature was evaluated statistically by separate window method and the relationship between land surface temperature with vegetation and soil moisture. The results showed that the accuracy of classification by maximum probability method through geomorphic facts data, TM and OLI images in terms of kappa coefficient of 0.89, 0.95 and 0.84, respectively, based on the overall accuracy of 91.8, 96.45 and 87.89% was obtained. During 1987, 2001 and 2018, average of the land surface temperature indices were 38.13, 45.73 and 41.14 ° C, the normalized difference vegetation index was -0.11, -0.13 and -0.16, and the normalized difference moisture index was estimated 0.64, 0.63 and 0.58. The relationship between land surface temperature and normalized difference of vegetation index was no correlative. The correlation between land surface temperature and the normalized difference of humidity index was also inverted and negative. Plant regeneration and growth was decreased owing to factors including hydrological drought and Climatic conditions due to reduced rainfall, rising air temperature and Dust storms. Therefore, due to the lack of suitable vegetation, vegetation is not effective in reducing the surface temperature of the study area.
Salman Ahmadi; Reza Soodmand
Abstract
The temperature of the Earth's surface is a very important parameter in environmental studies, climate change, soil moisture content, Evapotranspiration and urban thermal islands at different scales. Currently, there is no perfect method for accurately measuring the temperature of the surface of the ...
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The temperature of the Earth's surface is a very important parameter in environmental studies, climate change, soil moisture content, Evapotranspiration and urban thermal islands at different scales. Currently, there is no perfect method for accurately measuring the temperature of the surface of the earth, but since high spectral resolution sensors prevent the vapor spectral absorption in the infrared bands, this Increases computational accuracy in determining vegetation index. The purpose of this paper is to calculate the surface temperature using satellite images of OLI and TIRS sensors of Landsat 8. In this research, the separate window algorithm has been used to calculate ground temperature. The algorithm uses spectral radiance and emissivity to calculate the surface temperature. To estimate the spectral radiance in Landsat 8, the bands of 10 and 11 have been used. Emissivity is also obtained by using the NDVI threshold technique by using the OLI bands 2, 3, 4 and 5. Also, In this paper the temperature is calculated by The algorithm has been calibrated and corrected by a two-dimensional projective mathematical model, which tried to bring the calculated temperature closer to the actual ground temperature. In the present paper, the RMSE value is equal to 0.3678°C and the correlation between Meteorological data and temperature estimated by the model is equal to 0.9791. Also, the performance of the model that used to estimate the Earth's surface temperature is equal to 0.9751.
Mahshid karimi; Kaka Shahedi; Tayebe Raziei; Mirhassan Miryaghoobzadeh
Abstract
Drought is one of the natural disasters that may occur in any climate. In recent decades, Iran has been affected by severe droughts and its harmful effects in various sectors, such as agriculture, environment and water resources of the country. Today, vegetation indices, which are obtained through remote ...
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Drought is one of the natural disasters that may occur in any climate. In recent decades, Iran has been affected by severe droughts and its harmful effects in various sectors, such as agriculture, environment and water resources of the country. Today, vegetation indices, which are obtained through remote sensing technology, are used to identify and analyze agricultural droughts. Accordingly, the aim of this study was to investigate the effectiveness of NDVI, EVI and VCI vegetation indices in agricultural drought identification and analysis in Karkheh basin. In order to calculate these indices, MODIS sensor Images (Terra satellite, MOD13A2 product) were used during the 2000-2017 statistical period. The accuracy of these profiles was evaluated with the ZSI index calculated at 11 meteorological stations located in Karkheh basin for the statistical period of 2000-2017. The results showed that the changes of NDVI, EVI and VCI in the studied stations were approximately the same during the statistical period. Based on NDVI, EVI and VCI values, the lowest and highest vegetation cover was observed in 2000, dehno station and 2001, helilan-seymareh station, respectively. The ZSI survey showed that most stations Faced with droughts from 2000 to 2008, and the most severe drought occurred in 2008, nazarabad station. Then, in order to validation of the results, the vegetation indices with ZSI index were evaluated. Pearson correlation between mean vegetation indices of NDVI, EVI and VCI with mean ZSI was 0.766, 0.725 and 0.776, respectively, and all vegetation indices with ZSI index are significant at 0.99% confidence level. As seen, according to the results, the ZSI index confirms the results of NDVI, EVI, and VCI. So, according to the results, there is no conformity of meteorological and agricultural droughts in all years, Therefore, in addition to other precipitation, climate variables should also be considered.
Abolfazl Ranjbar; Abbasali Valia; Marzieh Mokarramb; Farideh Taripanahc
Abstract
Vegetation is one of the essential factors in structure and function of terrestrial ecosystem and it is one of the principal loops in water-soil-plant-atmosphere continuum. Several studies have demonstrated that vegetation covers are sensitive to alteration of climatic, edaphic, topographic and human ...
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Vegetation is one of the essential factors in structure and function of terrestrial ecosystem and it is one of the principal loops in water-soil-plant-atmosphere continuum. Several studies have demonstrated that vegetation covers are sensitive to alteration of climatic, edaphic, topographic and human activities. Thus, alteration in vegetation and its relation with the mentioned factors are important of high importance. In order to investigation of vegetation changes and its effective factors, the current study was conducted in Kharestan region placed in Fars province, Iran. In this regard, the images obtained from ETM Landsat 7 (2000-2017) and meteorological data gained from local and 17 regional meteorological stations were used. Using these images, temporal and spatial changes NDVI and NDVI anomaly were studied. A supervised classification method was used to extract land use map. Finally, the relationship of NDVI with climatic, topographic and anthropogenic factors was investigated. Relationship between NDVI and climatic and topographic factors was estimated using GWR and OLS methods, respectively. Generally, temporal variations showed a slow increasing trend in NDVI value. NDVI anomaly was mostly negative before 2008 but it turned to positive after 2009. NDVI spatial distribution showed an increasing tendency from north toward center and continued to south-west of the study area. The study shows that the vegetation cover change was caused by both natural factors and human activities. NDVI increased in agricultural and pasture lands. Also, natural vegetation has been affected by climatic factors more than irrigated vegetation (agricultural and gardens). Furthermore, vegetation variation influenced by topographic factors likes height, slope and aspect. Also, with an altitude over than 2500 m, NDVI showed a decreasing trend, on slopes lower than 5° it increased. NDVI values in north and east directions were higher than in southern aspects. The overall trend indicates an increase in temperature and a decrease in precipitation during the study period. The maximum positive and negative correlation between mean annual precipitation and NDVI using ordinary least squares method were 0.93 and 0.83, respectively. Also the maximum negative and positive correlation between NDVI and temperature were 0.65 and 0.5, respectively. The highest local R2 values between NDVI with precipitation and temperature were 0.45 and 0.44, respectively, which was observed in the central parts of the region. According to the obtained results through the present study, it can be stated that environmental factors like precipitation, altitude, slope and aspect are the Influential factors controlling vegetation in Kharestan (Fars province, Iran).
hossein Nikpey; Mehdi Momeni
Abstract
Drought is an important phenomenon which can be monitored based on weather data obtained from weather stations and remote sensing data. Remote sensing methods have offered significant relative advantages compared to the other methods for monitoring drought . Also , several drought indicators have provided ...
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Drought is an important phenomenon which can be monitored based on weather data obtained from weather stations and remote sensing data. Remote sensing methods have offered significant relative advantages compared to the other methods for monitoring drought . Also , several drought indicators have provided in remote sensing for monitoring drought , but none of the common indicators in remote sensing did not have generalizability of time , climate and altitude and it is necessary the performance quality of these indexes 1) in climates, 2) in altitudinal zoning examined .This study also proved this hypothesis , to identify appropriate indicators in every altitudinal zone , and in every region the index considered the appropriate season to evaluate indexes . In this study , drought indices ,VCI ,VDI ,TCI and TVDI by LST parameter , NDVI and EVI have been evaluated. To evaluate climate and altitudinal indicators , first in the whole country and then in Hamadan province , climate and altitudinal zoning done and drought indexes for different climates and altitude was determined in two forms pixel-based and object-based (polygons) and compared to precipitation data TRMM sensors . The operation of drought indexes were analyzed to drought evaluation by taking account climate type , data acquisition season , altitude and area . The results of this research shows lack of generalizability of all indictors in terms of climate , altitude and time indicators and for example , in pixel evaluating of hot and dry climate , the highest correlation between VCI index and precipitation data was in June and the lowest correlation is in December.
Ehsan Tamassoki1; Asadollah Khoorani; Ali Dervishi Bolorany; Ahmad noheghar
Volume 7, Issue 4 , November 2015, , Pages 27-44
Abstract
Wind erosion and dust storms are of major environmental hazards all around the world. Because of The extent of arid and semiarid regions in South and South- East of Iran and the successive incidence of this phenomenon in this region, it is important to study these phenomena. The aim of this study is ...
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Wind erosion and dust storms are of major environmental hazards all around the world. Because of The extent of arid and semiarid regions in South and South- East of Iran and the successive incidence of this phenomenon in this region, it is important to study these phenomena. The aim of this study is monitoring and predicting dust storms in south and south-east of Iran. For this purpose 92 Images of MODIS sensor as well as weather data of 18 stations are used. Dusty days (originating in outside and around the station) were extracted. After monthly and annually monitoring of storms, in order to predicting the frequency of dust storms based on spatial regression, climatic factors and NDVI are used. The results show that the number of storm are high in the beginning year and is decreasing in Jun and July. More than 78 percent of dust storms are of near station type. Spatial regression equations could predict amount of storms. Based on the origin of dust storms in this study combating desertification and wind erosion program could reduce frequency of this storms.
