The Use of Hyperspectral Earth Observation Data for Land Use/Cover ClassificationPresent Status, Challenges, and Future Outlook

Authored by: Prem Chandra Pandey , Kiril Manevski , Prashant K. Srivastava , George P. Petropoulos

Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation

Print publication date:  December  2018
Online publication date:  December  2018

Print ISBN: 9781138364769
eBook ISBN: 9780429431166
Adobe ISBN:

10.1201/9780429431166-8

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Abstract

This chapter focuses on advanced remote sensing technology, discussing the implementation of multispectral, hyperspectral data for land use/land cover (LULC) mapping and classification. The section is divided into a brief introduction including details of satellite datasets currently present and in future initiatives. This chapter discusses different classification schemes, pixel-based, object-based, and spectral mixing techniques for land use/land cover classification using hyperspectral datasets. The field spectroradiometer measurements were studied and libraries developed were utilized in land cover mapping. In order to achieve the land cover mapping, several statistical approaches used in the field for spectral discrimination are discussed. This chapter also provides a brief introduction to unmanned aerial vehicles (UAVs) and hyperspectral remote sensing for its advantages and limitations over LULC mapping and classification.

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