Coralline algae from the Aramda Reef Member of the Chaya Formation,Mithapur, Gujarat

The Quaternary sediments of the Aramda Reef Member of the Chaya Formation exposed in the Mojap coast near Mithapur, Gujarat are characterized by well-developed coralline algal build-ups. These algal build-ups are exceptionally rich in coralline algae and corals. In the present paper, thirteen species belonging to eight genera of coralline algae are described. Out of these, seven species (Titanoderma nataliae, Lithophyllum nitorum, Lithophyllum quadratum, Spongites sp. Brandano et al., 2005, Sporolithon lvovicum, Mesophyllum fructiferum and Lithothamnion praefruticulosum) are the new records for India. Four species (Titanoderma pustulatum, Sporolithon intermedium, Mesophyllum commune and Phymatolithon sp.) are first time recorded from the study area. Among the major framework builders of coralline algae of the Aramda Reef Member are Lithophyllum, Titanoderma, Sporolithon, Mesophyllum and Lithothamnion.     

A New Approach to 3D Dense LiDAR Data Classification in Urban Environment

Classification of Mobile Mapping LiDAR (Light Detection and Ranging) data is a challenge in the research community since the day when laser scanner system were integrated and mounted on vehicles for collection of 3D data in urban environment. The approach proposed here for classifying LiDAR data is analogous to the process followed for classifying data from satellite images. Pixel based and segmentation based methods have been employed in past for classifying images obtained from satellites. These methods were based on spectral properties of objects present in the images. But for Mobile mapping LiDAR data this approach has been applied and tested for the first time. The properties of this data are completely different from that of satellite images. So even if the basic approach remains the same, many changes have to be made in the entire classification process. The paper here aims to propose the basic procedure of using pixel-wise classification on dense 3D LiDAR data.     

Influence of Sedimentation on the Geomorphology of the Northwestern Continental Margin of India

Based upon the analysis of about 10,000 line km of echosounding and bathymetric data and variations in mass accumulation rate along the NW continental margin of India (between Kori creek and Mumbai), we have deduced that in the northern region (in the vicinity of the River Indus) the shelf-break occurs at a shallower depth and the slope is shallower, has the steepest gradient (<1:20), is smoother with no major features, and has reduced width (slope edge at 1450 m; width 19 km than off Mumbai). The width and depth of the slope edge gradually increases southwards, and is at maximum off DamanMumbai (slope edge depth 2900 m; width 84 km). The intensity of the occurrence of physiographic features also increases southwards. The shelf edge off Saurashtra is undulating and on the slope, regional notches and benches (the most prominent at 560 m) are observed. Further southwards off Khambhat-Mumbai, the slope is characterized by the presence of bathymetric highs and lows. We have also observed numerous features on the shelf, with a variable depth of the shelf-break. The gradient of the continental slope is also reduced from the northern region to the southern region. The variations in the gradient of the slope and the presence of distinct physiographic features in this area are examined vis-a-vis fluvial supply of the sediments into the region.     

Comparison of ocean color chlorophyll algorithms for IRS-P4 OCM sensor usingin-situ data

In-situ chlorophyll concentration data and remote sensing reflectance (R_rs) measurements collected in six different ship campaigns in the Arabian Sea were used to evaluate the accuracy, precision, and suitability of different ocean color chlorophyll algorithms for the Arabian Sea. The bio-optical data sets represent the typical range of biooptical conditions expected in this region and are composed of 47 stations encompassing chlorophyll concentration, between 0.072 and 5.90 mg m^-3, with 43 observations in case I water and 4 observations in case II water. Six empirical chlorophyll algorithms [i.e. Aiken-C, POLDER-C, OCTS-C, Morel-3, Ocean Chlorophyll-2 (OC2) and Ocean Chlorophyll-4 (OC4)] were selected for analysis on the Arabian Sea data set. Numerous statistical and graphical criterions were used to evaluate the performance of these algorithms. Among these six chlorophyll algorithms two chlorophyll algorithms (i.e. OC2 and OC4) performed well in the case I waters of the Arabian Sea. The OC2 algorithm, a modified cubic polynomial function which uses ratio of R_rs490 nm and R_rs555 nm (where, R_rs is remote sensing reflectance), performed well with r²=0.85; rms =0.15. The OC4 algorithm, a four-band (443, 490, 510, 555 nm), maximum band ratio formulation was found best on the basis of statistical analysis results with r²=0.85 and rms=0.14. Both OC2 and OC4 algorithms failed to estimate chlorophyll inTrichodesmium dominated waters. The OC2 algorithm was preferred over OC4 algorithm for routine processing of the OCM data to generate chlorophyll-a images, as it uses a band ratio of 490/555 nm and atmospheric correction is more accurate in 490 nm compared to 443 nm band, which is used by OC4 algorithm.     

Vegetation and climate change in southeastern Madhya Pradesh during Late Holocene,based on pollen evidence

Pollen analysis of 2 m deep sediment core from Kiktiha swamp, Shahdol district has revealed that between 1600 and 700 yr BP, tropical deciduous Sal forests comprising Shorea robusta (Sal), Madhuca indica, Terminalia, Lagerstroemia, Aegle marmelos flourished in the region under a warm and moist climate. Between 700 and 300 yr BP the deciduous Sal forests were succeeded by mixed deciduous forests, which turned sparse and less diversified, reflecting a relatively less moist climate attributed to the weak SW monsoon. The unfavourable climate also adversely affected the agricultural practice as evidenced from the diminution of Cerealia and other culture taxa. Since 300 yr BP onwards the modern deciduous Sal forests were re-established with the timely arrival of active SW monsoon. The increase in Cerealia and culture taxa indicates agricultural prosperity.     

Landslide susceptibility zonation of the Chamoli region, Garhwal Himalayas, using logistic regression model

A remote sensing and Geographic Information System-based study has been carried out for landslide susceptibility zonation in the Chamoli region, part of Garhwal Himalayas. Logistic regression has been applied to correlate the presence of landslides with independent physical factors including slope, aspect, relative relief, land use/cover, lithology, lineament, and drainage density. Coefficients of the categories of each factor have been obtained and used to assess the landslide probability value to ultimately categorize the area into various landslide susceptibility zones; very low, low, moderate, high, and very high. The results show that 71.13% of observed landslides fall in 21.96% of predicted very high and high susceptibility zone, which in fact should be the case. Furthermore, lineament first buffer category (0–500 m) and the east and south aspects are the most influential in causing landslides in the region.