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2019

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Samal, R. N.

Mangrove Species Discrimination and Health Assessment using AVIRIS-NG Hyperspectral Data

Abstract Views :210 | PDF Views:90

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

Source

Current Science, Vol 116, No 7 (2019), Pagination: 1136-1142

Abstract

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.

Full Text

References

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Coastal Sediment Dynamics, Ecology and Detection of Coral Reef Macroalgae from AVIRIS-NG

Abstract Views :214 | PDF Views:75

Authors

R. Ratheesh ¹, Nandini Ray Chaudhury ¹, Preeti Rajput ¹, Mohit Arora ¹, Ashwin Gujrati ¹, S. V. V. Arunkumar ¹, Ateeth Shetty ², Rakesh Baral ³, Rakesh Patel ⁴, Devanshi Joshi ⁴, Harshad Patel ⁴, Bharat Pathak ⁴, K. S. Jayappa ², R. N. Samal ³, A. S. Rajawat ¹

Affiliations
1 Space Applications Centre, Indian Space Research Organisation, Ahmedabad 380 015, IN
2 Mangalore University, Mangalagangorti, Mangaluru 574 199, IN
3 Chilika Development Authority, Bhubaneswar 751 014, IN
4 Gujarat Ecological Education and Research Foundation, Gandhinagar 382 007, IN

Source

Current Science, Vol 116, No 7 (2019), Pagination: 1157-1165

Abstract

This article highlights major scientific outcomes of the studies carried out using Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) airborne data over the coastal regions of Mangaluru, Gulf of Kachchh (GoK) and Chilika lagoon. Various hyperspectral remote sensing techniques involving bio-optical models and spectral classification algorithms are used to achieve different objectives related to coastal ecosystem monitoring. AVIRIS-NG airborne data are used to estimate particle size of suspended solids along the coastal waters of Mangaluru using an analytical optical model. The spatial distribution of particle size of the suspended solids in the coastal waters is brought out, while along the coastal land of Mangaluru, the beaches are classified based on uniform sediment characteristics using spectral matching algorithm. AVIRIS-NG data for Pirotan reef in GoK is analysed and species-level identification of the dominant brown macroalgae is carried out. Species-level distribution of brown macroalgae is mapped and used to study the microhabitat preference of different species. At Chilika lagoon, the AVIRIS-NG data are analysed to map the abundance of submerged seagrass using bio-optical model, which provides vital information to the coastal management community. The study asserts the importance of hyperspectral data and various advanced data analysis techniques related to the estimation of geophysical parameters of the coastal waters and monitoring the vital coastal ecosystems.

Keywords

Brown Macroalgae, Coastal Regions, Suspended Sediment Properties, Submerged Seagrass.

Full Text

References

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Distribution of Coloured Dissolved and Detrital Organic Matter in Optically Complex Waters of Chilika Lagoon, Odisha, India, using Hyperspectral Data of AVIRIS-NG

Abstract Views :212 | PDF Views:74

Authors

Arvind Sahay ¹, Anurag Gupta ¹, Gunjan Motwani ¹, Mini Raman ¹, Syed Moosa Ali ¹, Meghal Shah ², Shard Chander ¹, Pradipta R. Muduli ³, R. N. Samal ³

Affiliations
1 Marine Ecosystem Division, Biological and Planetary Sciences and Applications Group, Earth, Ocean, Atmosphere, Planetary Sciences and Applications Area, Space Applications Centre, Ahmedabad 380 015, IN
2 Department of Botany, University of Gujarat, Ahmedabad 380 009, IN
3 Wetland Research and Training Centre, Chilika Development Authority, Department of Forest and Environment, Government of Odisha, Balugaon 752 030, IN

Source

Current Science, Vol 116, No 7 (2019), Pagination: 1166-1171

Abstract

Coloured dissolved and detrital matter (CDM) forms a significant fraction of the total dissolved organic matter (DOM) in water bodies. It absorbs light strongly in the ultraviolet and blue domains of the electromagnetic spectrum. The present study maps CDM absorption of the entire Chilika lagoon, Odisha, India (an optically complex water body) using hyperspectral data of AVIRIS-NG. This study takes advantage of hyperspectral data which use SWIR bands for the estimation of remote sensing reflectance in highly turbid waters of Chilika lagoon (northern sector, which otherwise is masked using standard atmospheric correction schemes). During 24–27 December 2015, we have collected in situ bio-optical data over waters of Chilika lagoon, for studying the distribution of CDM. AVIRIS-NG data have also been acquired synchronous to in situ measurements over the study area. CDM absorption coefficient is retrieved using quasi analytical algorithm and the distribution of CDM is discussed in detail in three different sectors of Chilika lagoon (southern, central, northern) and at the outer channel. The variability of CDM absorption at 412 nm shows that in the north sector of Chilika lagoon, CDM absorption is quite high compared to other sectors (5.5 m^–1 with a standard deviation of 0.06 m^–1). In the southern sector and at the outer channel it is 1.8 m^–1 with a standard deviation of 0.02 m^–1 and in the central sector it is 3.76 m^–1 with a standard deviation of 0.22 m^–1. High CDM in the northern sector is attributed to the inflow of terrestrial organic matter. The advantage of hyperspectral data is that it gives CDM absorption contiguous in the range of 375–425 nm, where the absorption by CDM is strong and away from chlorophyll-a absorption.

Keywords

Dissolved Organic Matter, Hyperspectral Data, Lagoon, Optically Complex Waters.

Full Text

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