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Maity, S.
- Characterization of Species Diversity and Forest Health using AVIRIS-NG Hyperspectral Remote Sensing Data
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PDF Views:80
Authors
C. S. Jha
1,
Rakesh
1,
J. Singhal
1,
C. S. Reddy
1,
G. Rajashekar
1,
S. Maity
2,
C. Patnaik
2,
Anup Das
2,
Arundhati Misra
2,
C. P. Singh
2,
Jakesh Mohapatra
2,
N. S. R. Krishnayya
3,
Sandhya Kiran
3,
Phil Townsend
4,
Margarita Huesca Martinez
5
Affiliations
1 National Remote Sensing Centre, Indian Space Research Organisation, Hyderabad 500 037, IN
2 Space Applications Centre, Indian Space Research Organisation, Ahmedabad 380 015, IN
3 MS University of Baroda, Vadodara 390 002, IN
4 University of Wisconsin, Madison 53706, US
5 University of California, Davis 95616, US
1 National Remote Sensing Centre, Indian Space Research Organisation, Hyderabad 500 037, IN
2 Space Applications Centre, Indian Space Research Organisation, Ahmedabad 380 015, IN
3 MS University of Baroda, Vadodara 390 002, IN
4 University of Wisconsin, Madison 53706, US
5 University of California, Davis 95616, US
Source
Current Science, Vol 116, No 7 (2019), Pagination: 1124-1135Abstract
Species diversity and vegetation health are two critical components to be monitored for sustainable forest management and conservation of biodiversity. The present study characterizes species dominance and α -diversity of a forest for the selected region in Mudumalai Wildlife Sanctuary (MWS), Western Ghats, which represents one of the most economically important forest types in India – the tropical dry deciduous forest. NASA’s Next-Generation Airborne Visible and Infrared Imaging Spectrometer (AVIRIS-NG) data at spectral resolution of 5 nm and spatial resolution of 5 m were used to analyse the forest matrix. Biodiversity (α -diversity) map thus generated from airborne platform over 14.5 sq. km area mostly represents the forest tree species diversity. Dominant tree species in the study area were also mapped using AVIRIS data for 21.7 sq. km. Canopy emergent dominant species, viz. Anogeissus latifolia, Tectona grandis, Terminalia alata, Grewia tiliifolia, Syzygium cumini and Shorea roxburghii were classified using spectral angle mapper technique and image-based spectra in the MWS study site. The study shows that nearly 40% area is dominated by A. latifolia and 27.5% by T. grandis in the study site. This study concludes that AVIRIS data can be used in the delineation of species and α -diversity mapping at community level; however, the accuracy achieved for species classification is moderate (60%) due to intermixing of species in the study area. For the Shimoga study site in Karnataka, the field spectra were collected using a spectroradiometer and used for the classification for the three dominant tree species using absorption peak decomposition technique. Fieldcollected pure spectra were analysed and species-wise absorption peaks (Gaussian) with central wavelength, peak amplitude and dispersion were used as the endmembers for classification. AVIRIS-NG data over Shoolpaneshwar Wildlife Sanctuary (SWS) study site used for fuel load estimation with narrow band indices calculated from AVIRIS-NG datasets. AVIRIS-NG data for MWS and Shimoga study site were collected during 2 and 5 January 2016, while for SWS site data were collected on 8 February 2016.Keywords
Airborne Sensors, Forest Health, Hyperspectral Imaging, Species Diversity.Full Text
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