Asia's largest brackish water ecosystem, Chilika lagoon, supports livelihood of millions of inhabitants and also known to be bio-geo-chemically dynamic. This demands continuous monitoring of lagoon for which optical remote sensing may be crucial. The <i>in situ </i>bio-optical parameters were analyzed in two sectors (Outer Channel: OC and Southern Sector: SS) of Asia's largest brackish water ecosystem, Chilika lagoon. The spectral Remote Sensing Reflectance (R<sub>rs</sub>) ranged from 0.003 to 0.02sr<sup>-1</sup> in OC whereas in SS it was between 0.003 and 0.028sr<sup>-1</sup>. The minimum R<sub>rs</sub> was at 400nm that gradually increased with a peak at 580nm and subsequently decreased towards longer wavelength. R<sub>rs</sub> exhibited similar pattern in both the sectors from 400 to 600nm. Beyond this wavelength, R<sub>rs</sub> was relatively higher in SS. The shifting of peak towards longer wavelength could be attributed to high absorption due to chlorophyll-<i>a</i> (chl-<i>a</i>) and chromophoric dissolved organic matter (CDOM) that varied largely between sectors with relatively higher concentration of chl-<i>a</i> in OC and CDOM in SS. Further, we modelled chl-<i>a</i> by seven ocean colour algorithms (OC4, OC4E, OC4O, OC3M, OC3V, OC3C and OCMO2) using<i> in situ </i>R<sub>rs</sub>. The modelled chl-<i>a</i> was overestimating in situ at all stations due to high concentration of CDOM contaminating chl-<i>a</i> signals. However in OC, in situ and modelled chl-<i>a</i> followed the same trend (R<sup>2</sup>=0.88 to 0.90) probably due to strong co-variance of chl-<i>a</i> with CDOM. The analysis of this study points out towards the requirement for sector specific bio-optical algorithm for accurate chl-<i>a</i> retrieval for synoptic monitoring of lagoon health.
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 R<sub>rs</sub>(488) and R<sub>rs</sub>(443) with R<sub>rs</sub>(488) and R<sub>rs</sub>(531). The major clusters representing Noctiluca falls within the range of 0.0004 to 0.0015 (R<sub>rs</sub>488-R<sub>rs</sub>443) and -0.0012 to -0.0004 (R<sub>rs</sub>488-R<sub>rs</sub>531). 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.
Selection of central wavelengths, bandwidths and the number of spectral bands of any sensor to be flown on a remote sensing satellite is important to ensure discriminability of targets and adequate signal-to-noise ratio for the retrieval of parameters. In recent years, a large number of spectral measurements over a wide variety of water types in the Arabian Sea and the Bay of Bengal have been carried out through various ship cruises. It was felt pertinent to use this precious data set to arrive at meaningful selection of spectral bands and their bandwidths of the ocean colour sensor to be flown on the forthcoming Oceansat-3 of ISRO. According to IOOCG reports and studies by Lee and Carder (2002) it is better for a sensor to have ~15 bands in the 400-800 nm range for adequate derivation of major properties (phytoplankton biomass, colored dissolved organic matter, suspended sediments, and bottom properties) in both oceanic and coastal environments from observation of water color. <p> </p>In this study, ~417 hyper-spectral remote-sensing reflectance spectra (spectral range varies from ~380-800 nm) covering different water types like open, coastal, mid coastal and near coastal waters have been used to identify the suitable spectral bands for OCM-3. Central wavelengths were identified based on the results obtained from hyper-spectral underwater radiometer measurements of Rrs, HPLC pigments and spectrometer analyzed absorption spectra for all the above water types. Derivative analysis has been carried out from 1st to 5th order to identify the inflection and null points for better discrimination / identification of spectral peaks from the <i>in situ R<sub>rs</sub></i> spectra. The results showed that open ocean and coastal ocean waters has spectra peaks mostly in the blue, green region; turbid coastal waters has maximum spectral peaks in the red region. Apart from this, the spectral peaks were identified in the red region for the chlorophyll fluorescence in the open ocean and coastal waters. Based on these results 13 spectral bands were proposed in the VNIR region for the upcoming OCM-3 sensor. In order to obtain water leaving radiances from the measurements at spacecraft platform, it is necessary to do atmospheric correction we need to have spectral bands in the NIR and above regions. Hence, a set of bands 3 bands in the NIR and SWIR region were proposed for OCM-3 to address the atmospheric correction related issues.
An algorithm to determine the spectral total absorption coefficient of water is presented. The algorithm is based on the Gershun’s equation of α = μ<i>K</i><sub>E</sub>. The spectral underwater average cosine, μ and vertical attenuation coefficient of net irradiance, <i>K</i><sub>E</sub> were obtained from radiative transfer simulations using Hydrolight with large in-situ measured data from the coastal and estuarine waters of Goa. A refined algorithm of spectral μ as in Ref.  is used to determine the spectral underwater average cosine. The spectral <i>K</i><sub>E</sub> was related to the diffuse attenuation coefficient, <i>K</i><sub>d</sub>. The algorithms to derive absorption were validated using an independent NOMAD optical data at wavelengths 412, 440, 488, 510, 532, 555, 650 and 676 nm. The performance of the algorithm was evident from the high R<sup>2</sup>, low bias and low RMSE. The values of R<sup>2</sup> at wavelengths 412, 440, 488, 510, 532, 555, 650 and 676 nm were 0.95, 0.95, 0.93, 0.93, 0.88, 0.82, 0.62, and 0.65 respectively. The corresponding bias were -0.0064, 0.0076, 0.0038, 0.0044, 0.0122, 0.0124, 0.0362, and 0.0093 respectively. The algorithms for μ and <i>K</i><sub>E</sub> provide the spectral weighted average within Z<sub>90</sub> and have the advantage of deriving the absorption coefficients from the satellite data.
The MODIS - Aqua high-resolution imagery were exploited to detect and monitor oil spills. An evaluation
criterion has been established to study its potential. The study focused on two oil spill events: Lake Maracaibo,
Venezuela (January 18-20, 2003) and Jiyeh power station oil spill, Lebanon (July 15-31, 2006). The images were
examined at level-1B (only geometrically corrected) and level-2 (geometrically and atmospherically corrected) data
processing levels. The level-2 data lacked the sufficient contrast range, because of the rigorous atmospheric correction,
while the level-1B data were found to be suitable. The 250-m data at 645 and 859 nm and 500-m, interpolated to 250-m,
at 469, 555, 1240, and 2130 nm were analyzed. The methodology included examination of individual bands and
evaluation of 30 band ratioing combinations to improve the contrast of oil spills in the images. The evaluation criteria
were based on both visual and parametric. The metrics involved are: mean contrast function and feature matching. In
addition, bi-directional reflectance distribution function (BRDF) at 469, 555, and 645 nm wavelengths, were also
evaluated using the same criteria. The study found that at appropriate view-angle, MODIS-Aqua high-resolution is
suitable for oil spill detection at 250-m band. When the view-angle is not appropriate, the combination of mid-IR bands
with shorter wavelengths improved the feature matching.
A workshop on fisheries was held in Noumea on November 21, 2008 to address remote-sensing applications to fisheries adapted to the particular needs and problems of Western and Central Pacific Island countries. During the workshop, presentations and discussions covered various topics related to remote sensing of coastal and open ocean waters and its applications to fisheries. Participants were introduced to remote sensing of ocean colour and its significance vis-à-vis the marine food web. Applications to fisheries included improvements of fisheries operations to increase efficiency of fishing effort, assessment of fish stocks health, growth and recruitment, and ecosystem dynamics. A project on the Societal Applications in Fisheries & Aquaculture using Remote Sensing Imagery (SAFARI) and a global Network for marine ecosystem management (ChloroGIN) were also presented. The particular issues arising in the use of remote sensing for fisheries in the tropical island regimes were reviewed and recommendations on the use of remote sensing in the context of fisheries were presented.