Abstract
Abstract. An attempt has been made to compare the multispectral Resourcesat-2 LISS III and Hyperion image for the selected area at sub class level classes of major land use/ land cover. On-screen interpretation of LISS III (resolution 23.5 m) was compared with Spectral Angle Mapping (SAM) classification of Hyperion (resolution 30m). Results of the preliminary interpretation of both images showed that features like fallow, built up and wasteland classes in Hyperion image are clearer than LISS-III and Hyperion is comparable with any high resolution data. Even canopy types of vegetation classes, aquatic vegetation and aquatic systems are distinct in Hyperion data. Accuracy assessment of SAM classification of Hyperion compared with the common classification systems followed for LISS III there was no much significant difference between the two. However, more number of vegetation classes could be classified in SAM. There is a misinterpretation of built up and fallow classes in SAM. The advantages of Hyperion over visual interpretation are the differentiation of the type of crop canopy and also crop stage could be confirmed with the spectral signature. The Red edge phenomenon was found for different canopy type of the study area and it clearly differentiated the stage of vegetation, which was verified with high resolution image. Hyperion image for a specific area is on par with high resolution data along with LISS III data.
Highlights
Hyperspectral remote sensing are characterised by imaging and spectroscopic property, which differentiates the terrestrial features into unique spectral signature
An attempt has been made to compare the multispectral LISS III and Hyperion image at sub class level classification of major land use/ land cover features to understand the potential use of hyperspectral data in Land use study
Among vegetation classes like agriculture, forest, grassland in LISS III, only some classes like plantation, crop and forest type could be identified by virtue of their shape/pattern or density of vegetation type, which is clearer in hyperspectral image
Summary
Hyperspectral remote sensing are characterised by imaging and spectroscopic property, which differentiates the terrestrial features into unique spectral signature. This property is valuable in classifying land use / cover features especially vegetation and water bodies. The advent of hyper spectral remote sensing with continuous narrow band information opens the possibility of identifying even the species level discrimination in vegetation studies. Hyper spectral remote sensing by virtue of its contiguity and narrow bandwidth is increasingly used to characterize, model, classify, and map agricultural crops and natural vegetation. An attempt has been made to compare the multispectral LISS III and Hyperion image at sub class level classification of major land use/ land cover features to understand the potential use of hyperspectral data in Land use study
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