Vegetation Stress Detection With Hyperspectral Remote Sensing for A Winning Agribusiness

Abstract

The subject agribusiness has drawn an enormous attention by organized sector in national and multinational level with the recent move of the Government of India to allow Foreign Direct Investment (FDI) in the retailing sector. Technology driven efforts are very much important in this changed scenario to increase market efficiency reducing inventories, waste, and costs. Earth Observation Satellite (EOS) imagery driven Remote Sensing (RS) and Geographical Information System (GIS) technology can be utilized as a high-end Spatial Decision Support System (SDSS) to extract the different aspects of agriculture like land-use land-cover (LULC) condition, soil properties like moisture estimation, moisture conservation, crop identification, identification of suitable farming site for suitable crop, acreage estimation, crop monitoring, damage monitoring, and complete supply chain monitoring includes crop vehicle tracking integrating Global Positioning System (GPS). Increased availability of narrow band hyperspectral imagery from Hyperion sensor has prompted to explore hyeprspectral imagery to estimate the vegetation biophysical parameters and leaf biochemical used to detect nutritional and water stress condition. This paper summarizes the use of hyperspectral remote sensing for vegetation monitoring through biochemical and biophysical parameter estimation, discussing the potential for detecting water stress. Central to this objective is our primary research question: Can remote sensing play a key role to monitor agri-crop health to enhance the agribusiness efficiency?

Keywords: Vegetation Stress, Hyperspectral Remote Sensing, Vegetation Index, Agricultural Monitoring, and Agribusiness

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