Department of Environmental Sciences and NRM, College of Forestry, SHUATS, Prayagraj-211 007, India
1Department of Agrometeorology, G.B. Pant University of Agriculture & Technology, Pantnagar-263 145, India
2Department of Soil Science, G.B. Pant University of Agriculture & Technology, Pantnagar-263 145, India
3Water Technology Centre, ICAR-Indian Agricultural Research Institute, Pusa Campus, New Delhi-110 012, India
Hyperspectral remote sensing is an advance technology that facilitates the implementation of field soil data into digital soil mapping. It provides easier and effective way in understanding of soil chemical, physical, mineralogical and biological characteristics. In the present study a soil spectral library and fertility maps were developed based on different soil series for the university farm of GBPUA&T, Pantnagar. Twenty-five soil samples were collected from the farm at regular intervals. The samples were analyzed for soil texture, available nitrogen, available phosphorus and available potassium. Various soil-related indices were calculated from Hyperion imagery, which included Brightness Index, Redness Index, Saturation Index, Coloration Index, Hue Index, Normalized Difference Vegetative Index and Ratio Vegetation Index and Carbon Difference Index. The soil spectra of soil series showed different reflectance intensity due to variability of organic matter, sand, silt and clay. Beni silty clay loam soil showed highest reflectance peak among all the soil series due to maximum silt content whereas Phoolbagh clay loam soil comprises highest organic matter that decreases the reflectance peak. Moreover, the multiple regression equation of available nitrogen and available phosphorus was found significant with R2 of 0.66 and 0.61 respectively.
Hyperion, Hyperspectral remote sensing, Soil Spectral library
