About one third of the water needed for agriculture in the world is generated by melting snow. Snow cover, surface and ground water recharge are considered as sustainable and renewable resources. It is therefore neces...About one third of the water needed for agriculture in the world is generated by melting snow. Snow cover, surface and ground water recharge are considered as sustainable and renewable resources. It is therefore necessary to identify and study these criteria. The aim of this study is to determine the spatial and temporal distribution of snow cover in the district of the Sheshpir basin in Fars province (in south of Iran). Ground-based observation of snow covers, especially in mountainous areas, is associated with many problems due to the insufficient accuracy of optical observation, as opposed to digital observation. Therefore, GIS and remote sensing technology can be partially effective in solving this problem. Images of Landsat 5<sup>TM</sup> and Landsat 7<sup>TM</sup> satellites were used to derive snow cover maps. The images in ENVI 4.8 software were classified by using the maximum likelihood algorithm. Other spatial analyses were performed in ARC-GIS 9.3 software. The maximum likelihood method was accuracy assessed by operation points of testing. The least and the average of overall accuracy of produced maps were found to be 91% and 98%, respectively. This demonstrates that the maximum likelihood method has high performance in the classification of images. Overall snow cover and the review of terrain through the years 2008-2009 and 2009-2010 showed that snow cover begins to accumulate in November and reaches its highest magnitude in February. Finally, no trace of snow can be observed on the surface of the basin in the month of May. By average, 34% of the basin is covered in snow from November through to May.展开更多
Fractional snow cover （FSC） is that fraction of the surface covered with snow in a remotely sensed image pixel. This subpixel snow fraction is useful for atmospheric correction and to retrieve various satellite pro...Fractional snow cover （FSC） is that fraction of the surface covered with snow in a remotely sensed image pixel. This subpixel snow fraction is useful for atmospheric correction and to retrieve various satellite products characterizing the land surface, including albedo, temperature, soil moisture, heat fluxes, and vegetation parameters.展开更多
In this paper, the significance and history of studying snow grain size is introduced. Based on the assumption that high reflectivity in the visible band and significant decreasing reflectivity of snow surface in the ...In this paper, the significance and history of studying snow grain size is introduced. Based on the assumption that high reflectivity in the visible band and significant decreasing reflectivity of snow surface in the infrared band, the grain size of snow, spherical and non-spherical, is sensitive to changes in remote sensing retrieval foundation. Also, models and algorithms applied in current studies are reviewed, together with their advantages and disadvantages. In addition, in order to obtain retrieval accuracy, some factors that may affect grain size are also discussed, such as temperature, wavelength, arid particle shape, as well as method authentication.展开更多
文摘About one third of the water needed for agriculture in the world is generated by melting snow. Snow cover, surface and ground water recharge are considered as sustainable and renewable resources. It is therefore necessary to identify and study these criteria. The aim of this study is to determine the spatial and temporal distribution of snow cover in the district of the Sheshpir basin in Fars province (in south of Iran). Ground-based observation of snow covers, especially in mountainous areas, is associated with many problems due to the insufficient accuracy of optical observation, as opposed to digital observation. Therefore, GIS and remote sensing technology can be partially effective in solving this problem. Images of Landsat 5<sup>TM</sup> and Landsat 7<sup>TM</sup> satellites were used to derive snow cover maps. The images in ENVI 4.8 software were classified by using the maximum likelihood algorithm. Other spatial analyses were performed in ARC-GIS 9.3 software. The maximum likelihood method was accuracy assessed by operation points of testing. The least and the average of overall accuracy of produced maps were found to be 91% and 98%, respectively. This demonstrates that the maximum likelihood method has high performance in the classification of images. Overall snow cover and the review of terrain through the years 2008-2009 and 2009-2010 showed that snow cover begins to accumulate in November and reaches its highest magnitude in February. Finally, no trace of snow can be observed on the surface of the basin in the month of May. By average, 34% of the basin is covered in snow from November through to May.
文摘Fractional snow cover （FSC） is that fraction of the surface covered with snow in a remotely sensed image pixel. This subpixel snow fraction is useful for atmospheric correction and to retrieve various satellite products characterizing the land surface, including albedo, temperature, soil moisture, heat fluxes, and vegetation parameters.
基金provided by National Science Fundamental Key Project(40930526,40901041)Science Research Program of Global Change Research of China(Grant No.2010CB951404)
文摘In this paper, the significance and history of studying snow grain size is introduced. Based on the assumption that high reflectivity in the visible band and significant decreasing reflectivity of snow surface in the infrared band, the grain size of snow, spherical and non-spherical, is sensitive to changes in remote sensing retrieval foundation. Also, models and algorithms applied in current studies are reviewed, together with their advantages and disadvantages. In addition, in order to obtain retrieval accuracy, some factors that may affect grain size are also discussed, such as temperature, wavelength, arid particle shape, as well as method authentication.
