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Chaube, Nilima R.
- Crop Phenology and Soil Moisture Applications of SCATSAT-1
Abstract Views :266 |
PDF Views:81
Authors
Nilima R. Chaube
1,
Sasmita Chaurasia
1,
Rojalin Tripathy
1,
Dharmendra Kumar Pandey
1,
Arundhati Misra
1,
B. K. Bhattacharya
1,
Prakash Chauhan
2,
Kiran Yarakulla
3,
G. D. Bairagi
4,
Prashant Kumar Srivastava
5,
Preeti Teheliani
6,
S. S. Ray
6
Affiliations
1 Space Applications Centre, ISRO, Ahmedabad 380 015, IN
2 Indian Institute of Remote Sensing, Dehradun 248 001, IN
3 Vellore Institute of Technology, Vellore 632 014, IN
4 M.P. Council of Science and Technology, Bhopal 462 003, IN
5 Banaras Hindu University, Varanasi 221 005, IN
6 Mahalanobis National Crop Forecast Centre, Delhi 110 012, IN
1 Space Applications Centre, ISRO, Ahmedabad 380 015, IN
2 Indian Institute of Remote Sensing, Dehradun 248 001, IN
3 Vellore Institute of Technology, Vellore 632 014, IN
4 M.P. Council of Science and Technology, Bhopal 462 003, IN
5 Banaras Hindu University, Varanasi 221 005, IN
6 Mahalanobis National Crop Forecast Centre, Delhi 110 012, IN
Source
Current Science, Vol 117, No 6 (2019), Pagination: 1022-1031Abstract
SCATSAT-1 measures the backscattering coefficient over land surfaces, which is a function of vegetation structure, surface roughness, soil moisture content, incidence angle and dielectric properties of vegetation. Scatterometer image reconstruction techniques provide fine resolution data to explore the emerging applications over land by using ambiguous backscatter from land. In this paper, 2 km resolution products of ISRO’s scatterometer SCATSAT-1 are exploited for land target detection, rice crop phenology stages detection for kharif and rabi seasons and estimation of relative soil moisture over parts of India. Temporal and spatial backscatter changes are due to seasonal and changes in Land Use Land Cover. Crop phenology stages such as transplanting, maximum tillering, panicle emergence and physiological maturity stages are identified by analysing SCATSAT-1 time series along with NDVI and findings are supported by appropriate ground truth observations and crop cutting experiment (CCE) data. The relative soil moisture change detection is validated with in situ ground truth measurements using Hydraprobe, carried for SCATSAT-1 ascending and descending passes.Keywords
Crop Phenology, Gamma-0, Rice, Sigma-0, Soil Moisture, Vegetation Dynamics.References
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- Mangrove Species Discrimination and Health Assessment using AVIRIS-NG Hyperspectral Data
Abstract Views :214 |
PDF Views:92
Authors
Nilima R. Chaube
1,
Nikhil Lele
1,
Arundhati Misra
1,
T. V. R. Murthy
1,
Sudip Manna
2,
Sugata Hazra
3,
Muktipada Panda
4,
R. N. Samal
4
Affiliations
1 Space Applications Centre, Ahmedabad 380 015, IN
2 Department of Physics, Presidency University, Kolkata 700 073, IN
3 School of Oceanographic Studies, Jadavpur University, Kolkata 700 032, IN
4 Chilika Development Authority, Bhubaneshwar 751 014, IN
1 Space Applications Centre, Ahmedabad 380 015, IN
2 Department of Physics, Presidency University, Kolkata 700 073, IN
3 School of Oceanographic Studies, Jadavpur University, Kolkata 700 032, IN
4 Chilika Development Authority, Bhubaneshwar 751 014, IN
Source
Current Science, Vol 116, No 7 (2019), Pagination: 1136-1142Abstract
Mangroves play a major role in supporting biodiversity, providing economic and ecological security to the coastal communities, mitigating the effects of climate change and global warming. Species level classification of mangrove forest, understanding physical as well as chemical properties of mangrove vegetation, mangrove health, pigments, and levels of stress are some of the key issues for making scientific and management decisions. Hyperspectral remote sensing owing to its narrow bands, yield information on structural details and canopy parameters. Hyperspectral data over Sundarban and Bhitarkanika mangrove forests are analyzed for species discrimination and forest health assessment. In all, 15 mangrove species in Sundarban and 7 mangrove species in Bhitarkanika have been identified and classified using Spectral Angle Mapper technique. In-situ spectro-radiometer data has been used along with AVIRIS-NG hyperspectral data. Based on response of vegetation in blue, red and near-infrared regions, combination of vegetation indices are used to assess mangrove forest’s health. Reduction in NIR reflectance with shift towards lower wavelength has been observed in less healthy groups.Keywords
Coastal Forest Management, Health Assessment, Hyperspectral Data, Mangrove Species.References
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