IRS-P6 LISS-IV dataIn the present study, an attempt has been made to describe the technique for large-scale soil mapping using remote sensing data. Based on erosional and depositional processes, seven major landforms namely plateau top, scarp slopes, plateau spurs, pediment, undulating plain, ...
IRS-P6 LISS-IV dataIn the present study, an attempt has been made to describe the technique for large-scale soil mapping using remote sensing data. Based on erosional and depositional processes, seven major landforms nadoi:10.1007/s12524-015-0540-7Nisha Sahu...
the result indicates that IRS-P6 can be used to make a map of 1∶25 000 or 1∶50 000 and update or assistantly update 1∶25 000 or(1∶50 000) land use actuality map.In the landuse dynamic monitoring project,IRS-P6 image can be used as another data set with LANDSAT and SPOT.So...
The ResourceSat-1 Satellite (also called as IRS-P6) was launched into the polar sunsynchronous orbit on Oct 17, 2003. It carries three remote sensing sensors: the High Resolution Linear Imaging Self-Scanner (LISS-IV), Medium Resolution Linear Imaging Self-Scanner (LISS-III), and the Advanced...
文 中使用 的数据有 :① 遥感影 像。IRS —P6 LISS3 影像 ; 轨道号/航号 :117/54 ;成 像时间 :2006 年 1 月 28 日;影像分辨 率:25 m ×25 m;成像 时太 阳高度 角为 41.3。;太 阳天顶 角为 48.7。;太阳方位角为 151.0 。;② 研究 区 1:50 000 的地形 图。
In order to investigate the capability of satellite images for Pistachio forests density mapping, IRS-P6-LISS IV data were analyzed in an area of 500 ha in Iran. After geometric correction, suitable training areas were determined based on fieldwork. Suitable spectral transformations like NDVI, PVI...
This work is an attempt to document and identify landslide areas by five spectral indices using temporal multi-spectral images from IRS-P6 LISS-IV images. To improve the spectral properties of spectral indices for specific class identification (in this case landslide) a Class Based Sensor ...
Investigation of the capability of IRS-P6-LISS IV data for density mapping of Pistachio forests (Case study: Khaje kalat forest in Khorasan)Ali Darvishsefat
This study attempts to document and identify built-up damaged (BD) areas using spectral indices taking temporal multispectral images from IRS-P6 LISS-IV. Five spectral indices have been used to identify BD areas using supervised possibilistic c-means (PCM) and noise cluster (NC) classifiers, to...
High-resolution Cartosat-1 satellite data were used to outline the terrain and structural elements, while IRS P6 LISS-IV Mono data were used to outline the terrain changes. Results of the study describes how an earthquake can trigger landslides and the role of the fault system in their spatial...