Abstract
This study consist of experiments on Hyperspectral remote sensing data for monitoring field stress using remote sensing tools. We have segmented Hyperspectral image and then calculated stress level using ENVI tool. EO-I hyperspectral remote sensing data from hyperion space born sensor has been used as the key input. QUACK (Quick Atmospheric Correction) algorithm has been used for atmospheric correction of hyperspectral data. EO-1, hyperion sensors data It has been observed that stress level depends on chlorophyll contents of a leaf. It has been observed that green field is with less stress and rock where no chlorophyll contents have most stress. We have also shown stress level in the scale of 1 to 9.
Highlights
Remote sensing data has great useful data which can be used for different field applications
QUACK (Quick Atmospheric Correction) algorithm has been used for atmospheric correction of hyperspectral data
We have extracted image that we want to analysis using segmentation feature of ENVI. We have provided this segment for vegetation analysis
Summary
Remote sensing data has great useful data which can be used for different field applications. Popular application of remote sensing is land cover land use. Role of vegetation analysis is more useful for sustainable development [1]. There are mono spectral, multispectral and hyperspectral remote sensing data available which has different significance and has different number of bands. Thenkabail found best wavebands for vegetation analysis to assess the vegetation and agricultural crop classification [5]. Vegetation Change may be Detected using remote sensing data and vegetation analysis method [6]. Vegetation identification using hyperspectral remote sensing data has been implemented by Erin et al.[7]. Modeling and vegetation analysis using remote sensing data for has been used by Goodchild [8]
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