排序方式: 共有82条查询结果,搜索用时 48 毫秒
81.
R. P. Singh V. N. Sridhar V. K. Dadhwal R. Jaishankar M. Neelkanthan A. K. Srivastava G. D. Bairagi N. K. Sharma S. A. Raza Rajesh Sharma Manoj Yadav F. K. Joshi N. L. Purohit 《Journal of the Indian Society of Remote Sensing》2005,33(1):93-98
This paper presents results of a pilot study in six villages located in the states of Haryana, Rajasthan and Madhya Pradesh, to evaluate accuracy of crop area at village level estimated by IRS - LISS-I1I data with respect to detailed field survey carried out by National Sample Survey Organization. The selected villages were located in Karnal, Kota and Bhopal districts which represented single dominant wheat crop as well as wheat-mustard and wheat-gram situation, respectively. Accuracy assessment of remote sensing based estimate with field survey of NSSO showed relative deviation in wheat estimate ranging from 3.72 percent for Mainmati village in Karnal district in Haryana to 22.65 percent fo Ranpur village in Kota district of Rajasthan. It was found that relative deviation in area estimation is inversely poportional to the crop proportion in that village. Observations of over estimation at low crop proportion and underestimation at higher crop proportion was explained by simple budgeting of relative proportion of ommision and commision errors. The study demonstrates that on the average, 90 percent crop area accuracy is possible with LISS-II1 data and the adopted approach. 相似文献
82.
M. R. Pandya R. P. Singh K. N. Chaudhari K. R. Murali A. S. Kirankumar V. K. Dadhwal J. S. Parihar 《Journal of the Indian Society of Remote Sensing》2007,35(4):333-350
This paper reports the results of a modeling study carried out with two objectives, (1) to estimate and compare effective spectral characteristics (central wavelength, bandwidth and bandpass exo-atmospheric solar irradiance Eo) of various spectral channels of LISS-III, WiFS, LISS-III*, LISS-IV and AWiFS onboard Indian Remote Sensing Satellites IRS-ID and P6 using moment method based on the laboratory measurements of sensor spectral response, and (2) to quantify the influence of varying sensor spectral response on reflectance and Normalized Difference Vegetation Index (NDVI) measurements using surface reflectance spectra corresponding to different leaf area index conditions of crop target obtained through field experiment. Significant deviation of 4 to 14 nm in central wavelength and 1.6 to 14.07 nm in spectral width was observed for the corresponding channel of IRS sensors. Coefficient of variation of the order of 0.1 to 1.11% was noticed in Eo among various IRS sensors, which could induce a difference of 0.72 to 3.35% in the estimation of top of atmosphere reflectance for crop target. The variation in spectral response of IRS sensors implied a relative difference of the order of 0.91 to 3.38% in surface reflectance and NDVI measurements. Polynomial approximations are also provided for spectral correction that can be utilized for normalizing the artifacts introduced due to differences in spectral characteristics among IRS sensors. 相似文献