R. S. Mahendra

Coastal Vulnerability Assessment for Orissa State, East Coast of India

Abstract Coastal areas of Orissa State in the northeastern part of the Indian peninsula are potentially vulnerable to accelerated erosion hazard. Along the 480-km coastline, most of the coastal areas, including tourist resorts, hotels, fishing villages, and towns, are already threatened by recurring storm flood events and severe coastal erosion. The coastal habitats, namely the largest rookeries in the world for olive Ridley sea turtles (the extensive sandy beaches of Gahirmatha and Rushikulya), Asias largest brackish water lagoon (the “Chilika”), extensive mangrove cover of Bhitarkanika (the wildlife sanctuary), the estuarine systems, and deltaic plains are no exception. .The present study therefore is an attempt to develop a coastal vulnerability index (CVI) for the maritime state of Orissa using eight relative risk variables. Most of these parameters are dynamic in nature and require a large amount of data from different sources. In some cases, the base data is from remote sensing satellites; for others it is either from long-term in situ measurements or from numerical models. Zones of vulnerability to coastal natural hazards of different magnitude (high, medium, and low) are identified and shown on a map. In earlier studies, tidal range was assumed to include both permanent and episodic inundation hazards. However, the mean of the long-term tidal records tends to dampen the effect of episodic inundation hazards such as tsunamis. For this reason, in the present study, tsunami run-up has been considered as an additional physical process parameter to calculate the CVI. Coastal regional elevation has also been considered as an additional important variable. This is the first such study that has been undertaken for a part of the Indian coastline. The map prepared for the Orissa coast under this study can be used by the state and district administration involved in the disaster mitigation and management plan.

Assessment of the coral bleaching during 2005 to decipher the thermal stress in the coral environs of the Andaman Islands using remote sensing

Abstract Sea Surface Temperature (SST) derived from the NOAA AVHRR satellite data were used to generate the Degree of Heating Weeks (DHW) and Hot Spot (HS) products. Combination of the cumulative temperature anomalies and the thermal stress studies were yielded to synoptically identify the probable areas of bleaching. The bleaching status of the Andaman region was assessed based on the DHW and HS for the bleaching event occurred in the Andaman region in April/May 2005. The bleaching status up to Alert Level-1 was recorded with the maximum HS of 3°C and DHW 6°C-week. Simultaneous in-situ reef observations conducted in the Andaman Sea confirmed the coral bleaching event. The maximum mortality in the region due to coral bleaching was shown by the Acropora species (43%) followed by Montipora species (22%) and Porites species (14%). This study focused on detection of coral bleaching warning based on the SST in compliment with the in-situ observations.

Algal species dynamics in North Arabian Sea using long term ocean colour satellite data

North Arabian Sea experiences massive proliferation of variable algal species. The study presents variability of Noctiluca and its association with hydrographic parameters such as sea surface temperature (SST) and water column stability using ten years of satellite data. The area was categorized into three regions, North (23 to 26°N and 56 to 70°E), West (18 to 23°N and 56 to 62°E) and East (18 to 23°N and 62 to 74°E). The Noctiluca dominated area was extracted following approach of Dwivedi et. al. (2015) based on slope of Remote Sensing Reflectance (Rrs) between 488 to 443nm and 488 to 531nm. The data used in the present study depicted two distinct clusters based on regression between difference of Rrs(488) and Rrs(443) with Rrs(488) and Rrs(531). The major clusters representing Noctiluca falls within the range of 0.0004 to 0.0015 (Rrs488-Rrs443) and -0.0012 to -0.0004 (Rrs488-Rrs531). The occurrence of Noctiluca showed bi-modal distribution at an annual scale with the dominance in the northern region during winter monsoon (February- March). In western and eastern region higher frequency of Nuctiluca was during post monsoon having lag of one month from western (September) to eastern (October) region. The periodicity of Noctiluca, carried out using Fourier analysis, showed predominance at annual scale in Northern and semi-annual scale in Western and Eastern region. This indicates that the Noctiluca bloom in the northern region is primarily triggered by winter mixing whereas in western and eastern part of northern Arabian Sea it has combined effect of summer upwelling as well as winter mixing.

Identification of coral reef feature using hyperspectral remote sensing

Present study employs reef-up approach to map coral reef zones along the Sentinel Island of Andaman using high spectral resolution offered by hyper spectral imagery by Hyperion mission of NASA. This data consisting of 242 spectral bands, provide a unique ability to identify Coral substrate based on their spectral properties. We applied atmospheric correction with the help of Fast Line-of-sight Atmospheric Analysis of Hypercubes (FLAASH) module of ENVI software. This atmospherically corrected was used to extract Coral Reef Zones (CRZ) based on specific threshold limits after subtracting data of 782.95nm band from 579.45nm band of Hyperion imagery. Both of these bands were chosen due to their property of exhibiting maximum spectral contrast that determines threshold limits to distinguish a coral area from its non-coral counterpart. These CRZs were compared with the coral reef zones base map developed using LISS-III data by INCOIS, Hyderabad and SAC, Ahmadabad under CZS project. We observed that extracted CRZ area was 85.25 m2 and 110.1 m2 using LISS-III and Hyperion Data respectively. Despite the overestimation of CRZ by Hyperion data as compared to LISS-III, the spatial distribution of CRZ showed reasonable similarity in both.