Abstract
Crop type discrimination is still very challenging task for researchers using non-imaging hyperspectral data. It is because of spectral reflectance similarity between crops. In this research work we have discriminated between four crops wheat, jowar, bajara and maize. We have tried to overcome the problems which have been faced my researchers. Initially by visual analysis we have selected 22 reflectance band which shows the absorption property of particular molecules and classification technique is applied, but it has given us very poor result of classification. We observed only 24% classification accuracy. So we considered nine vegetation indices along with spectral bands and achieved better classification accuracy. ASD FieldSpec 4 Spectroradiometer device is used for capturing spectral reflectance data. We calculated nine different vegetation indices and some selective reflectance bands are used for crop classification. We have used Support Vector Machine (SVM) for classification.
Highlights
Remote sensing is being increasingly used in different agricultural applications
Analytical Spectral Device (ASD) FieldSpec 4 Spectroradiometer is a primary tool used for generating hyperspectral signature data
Spectral signature analysis of four crops shows their characterization based on reflectance on particular band
Summary
Remote sensing is being increasingly used in different agricultural applications. Hyper spectral remote sensing in large continuous narrow wavebands provides significant advancement in understanding the subtle changes in biochemical and biophysical attributes of the crop plants and their different physiological processes, which otherwise are indistinct in multispectral remote sensing [1]. Known as imaging and nonimagingspectroscopy is useful for various applications such as the detection and identification of minerals from crops, terrestrial vegetation, and man-made materials [2]. The general reflectance shape and transmission curves for green vegetation is similar for all types of crop species. It is featured by absorption of specific molecules and the cellular arrangement of the leaf tissue. The major absorption bands of water are 1450nm and 1940nm We have used these spectral reflectance properties and some vegetation indices for crop classification purpose which given us satisfactory result.
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