Informatics Publishing Limited

Swapnil S. Vyas ¹, Bimal K. Bhattacharya ¹, Rahul Nigam ¹

Affiliations
1 Earth Ocean Atmosphere Planetary Sciences and Applications Area, Space Applications Centre, ISRO, Ahmedabad 380 015, IN

Abstract

Quantification of assured solar energy potential is essential to select locations for solar photovoltaic, thermal power plants and to quantify solar power potential. The use of remote sensing observations from geostationary satellite sensors is ideal to capture space-time variability of surface insolation. The annual clear solar energy exposure over India was determined using three years' insolation data at 8 km spatial resolution from Kalpana-1 satellite. High density solar energy pockets were diagnosed in western, central and southern India including Gujarat, Rajasthan, Madhya Pradesh, Karnataka, Tamil Nadu and Chhattisgarh states with annual solar energy exposure ranging from 2500 to 3500 kW h m^-2 yr^-1.

Keywords

Geostationary Satellite, Renewable Energy, Remote Sensing.

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Bimal K. Bhattacharya ¹, Robert O. Green ², Sadasiva Rao ³, M. Saxena ¹, Shweta Sharma ¹, K. Ajay Kumar ¹, P. Srinivasulu ³, Shashikant Sharma ¹, D. Dhar ¹, S. Bandyopadhyay ⁴, Shantanu Bhatwadekar ⁴, Raj Kumar ¹

Affiliations
1 Space Applications Centre, Indian Space Research Organisation, Ahmedabad 380 015, IN
2 Jet Propulsion Laboratory, California Institute of Technology, CA 91109, IN
3 National Remote Sensing Centre, Indian Space Research Organisation, Hyderabad 500 625, IN
4 Earth Observation Science Directorate, Indian Space Research Organisation, Bengaluru 560 231, IN

Abstract

The first phase of an airborne science campaign has been carried out with the Airborne Visible/Infrared Imaging Spectrometer Next Generation (AVIRIS-NG) imaging spectrometer over 22,840 sq. km across 57 sites in India during 84 days from 16 December 2015 to 6 March 2016. This campaign was organized under the Indian Space Research Organisation (ISRO) and National Aeronautics and Space Administration (NASA) joint initiative for HYperSpectral Imaging (HYSI) programme. To support the campaign, synchronous field campaigns and ground measurements were also carried out over these sites spanning themes related to crop, soil, forest, geology, coastal, ocean, river water, snow, urban, etc. AVIRIS-NG measures the spectral range from 380 to 2510 nm at 5 nm sampling with a ground sampling distance ranging from 4 to 8 m and flight altitude of 4–8 km. On-board and ground-based calibration and processing were carried out to generate level 0 (L0) and level 1 (L1) products respectively. An atmospheric correction scheme has been developed to convert the measured radiances to surface reflectance (level 2). These spectroscopic signatures are intended to discriminate surface types and retrieve physical and compositional parameters for the study of terrestrial, aquatic and atmospheric properties. The results from this campaign will support a range of objectives, including demonstration of advanced applications for societal benefits, validation of models/techniques, development of state-of-the-art spectral libraries, testing and refinement of automated tools for users, and definition of requirements for future space-based missions that can provide this class of measurements routinely for a range of important applications.

Keywords

Airborne Science Campaign, Hyperspectral Sensing, Imaging Spectrometer, Surface Reflectance.

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Rahul Nigam ¹, Rojalin Tripathy ¹, Sujay Dutta ¹, Nita Bhagia ¹, Rohit Nagori ¹, K. Chandrasekar ², Rajsi Kot ³, Bimal K. Bhattacharya ¹, Susan Ustin ⁴

Affiliations
1 Agriculture and Land Eco-system Division, Earth, Ocean, Atmosphere, Planetary Sciences and Applications Area, Space Applications Centre (ISRO), Ahmedabad 380 015, IN
2 National Remote Sensing Centre (ISRO), Hyderabad 500 037, IN
3 M.G. Science Institute, Ahmedabad 380 009, IN
4 Environmental and Resource Sciences, University of California, Davis, CA 95616, US

Abstract

Advancements in hyperspectral remote sensing technology have opened new avenues to explore innovative ways to map crops in terms of area and health. To study precise mapping of agriculture and horticulture crops along with biophysical and biochemical constituents at field scale, an airborne AVIRIS-NG hyperspectral imaging has been conducted in various agro-climatic regions representing diverse agricultural types of India. Crop classification with available and developed algorithms has been applied over homogeneous and heterogeneous agriculture and horticulture cropped areas. The spectral angle mapper and maximum likelihood algorithms showed classification accuracy of 77%–94% for AVIRI-NG and 42%–55% for LISS IV. The customized deep neural network and maximum noise function (MNF)-based classification schemes showed an accuracy of 93% and 86% for mapping of agriculture and horticulture crops respectively. The forward and inversion of canopy radiative transfer model protocol was developed for retrieval of crop parameters such as leaf area index (LAI) and chlorophyll content (C_ab) using AVIRIS-NG narrow bands. The retrieved LAI and C_ab showed 19%–27% and 23%–29% deviation from measured mean for homogeneous and heterogeneous agricultural areas respectively. Red edge position index-based empirical model and multivariate linear regression of multiple indices showed maximum correlation of 0.62 and 0.93 respectively, to map leaf nitrogen content. Water condition index was developed using vegetation and water indices to distinguish crop water-based abiotic stress. Wheat yellow rust disease has been identified at field scale using absorption band depth analysis at 662–702 and 2155–2175 nm, and further applied to AVIRIS-NG data to detect biotic stress at spatial scale. This study establishes that such missions have the potential to boost accurate mapping of economically valuable minor crops and generate health indicators to distinguish biotic and abiotic stresses at field scale.

Keywords

Assessment, Biotic and Abiotic Stress, Crop Classification, Health, Hyperspectral Imaging.

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