Trichodesmium erythraeum (Ehrenberg) bloom along the southwest coast of India (Arabian Sea) and its impact on trace metal concentrations in seawater

The incidence of a large scale Trichodesmium erythraeum bloom along the southwest coast of India (Arabian Sea) observed in May 2005 is reported. Around 4802 filaments of T. erythraeum ml⁻¹ seawater was observed and a colony consisted of 3.6 × 10⁵ cells. The bloom was predominant off Suratkal (12° 59′N and 74° 31′E) with a depth of about 47 m, covering an area of 7 km in length and 2 km width. The concentrations of Zinc, Cadmium, Lead, Copper, Nickel and Cobalt were determined in samples collected from the bloom and non-bloom sites using stripping voltammetry. The observed hydrographical and meteorological parameters were found to be favorable for the bloom. The concentrations of Zinc, Cadmium and Nickel were found to be higher at bloom stations, while the concentrations of Lead, Copper and Cobalt were found to be very low at bloom stations. Elevated concentrations of Cadmium and Cobalt were observed at Valappad mainly due to the decomposition of detrital material produced in the bloom. Statistically significant differences (P > 0.01) in metal concentrations between the bloom and non-bloom stations were not observed except for Copper. Metals such as Lead, Copper and Cobalt were removed from the seawater at all places where bloom was observed. Cadmium was found to be slowly released during the decaying process of the bloom.     

3D Reconstrution with Rational Function Model

Rational Function Model (RFM) is the alternate sensor Model to the rigorous sensor model that allows end user to perform sensor-independent photogrammetric processing. Nowadays, commercial off-the-shelf (COTS) digital photogrammetric work stations have incorporated RFM as a method for image restitution. It is technically applicable to all types of airborne and space borne sensors. In this paper, we describe the derivations of the algorithmic procedure for third order inverse and forward RFM method for 3-D reconstruction. Model accuracy is evaluated for aerial image, TK-350 Russian image and IRS-1C PAN image. The results ensure that properly constructed RFM are accurate enough to be used in place of the original rigorous models. The test results are reported and summarised.     

Artificial neural network and liquefaction susceptibility assessment: a case study using the 2001 Bhuj earthquake data,Gujarat, India

This study pertains to prediction of liquefaction susceptibility of unconsolidated sediments using artificial neural network (ANN) as a prediction model. The backpropagation neural network was trained, tested, and validated with 23 datasets comprising parameters such as cyclic resistance ratio (CRR), cyclic stress ratio (CSR), liquefaction severity index (LSI), and liquefaction sensitivity index (LSeI). The network was also trained to predict the CRR values from LSI, LSeI, and CSR values. The predicted results were comparable with the field data on CRR and liquefaction severity. Thus, this study indicates the potentiality of the ANN technique in mapping the liquefaction susceptibility of the area.     

The Tau Model for Data Redundancy and Information Combination in Earth Sciences: Theory and Application

Many decision-making processes in the Earth sciences require the combination of multiple data originating from diverse sources. These data are often indirect and uncertain, and their combination would call for a probabilistic approach. These data are also partially redundant with each other or with all others taken jointly. This overlap in information arises due to a variety of reasons—because the data arises from the same geology, because they originate from the same location or the same measurement device, etc. The proposed tau model combines partially redundant data, each taking the form of a prior probability for the event being assessed to occur given that single datum. The parameters of that tau model measure the additional contribution brought by any single datum over that of all previously considered data; they are data sequence-dependent and also data value-dependent. Data redundancy depends on the sequence in which the data is considered and also on the data values themselves. However, for a given sequence, averaging the tau model parameters over all possible data values leads to exact analytical expressions and corresponding approximations and inference avenues. Information on multiple-point connectivity of permeability arrives from core data, well-test data and seismic data which are defined over varying supports with complex redundancy between these information sources. In order to compute these tau weights for determining connectivity, one needs a model of data redundancy, here expressed as a vectorial training image (Ti) constructed using a prior conceptual knowledge of geology and the physics of data measurement. From such a vectorial Ti, the tau weights can be computed exactly. Neglecting data redundancy leads to an over-compounding of individual data information and the possible risk of making extreme decisions.     

Resourcesat (IRS-P6) value added data products

Remote sensing data products need to meet stringent geodetic and geometric accuracy specifications irrespective of intended user applications. Georeferencing is the basic processing step towards achieving this goal. Having known the imaging geometry and mechanism, the mathematical models built with the use of orbit and attitude information of the spacecraft can correct the remote sensing data for its geometric degradations only up to system level accuracy (IRS-P6 DP Team, 2000). The uncertainties in the orbit and attitude information will not allow the geometric correction model to generate products of accuracy that can meet user requirements unless Ground Control Points (GCP) are used as reference geo-location landmarks. IRS-P6 data processing team has been entrusted with developing a software system to generate data products that will have desired geodetic and geometric accuracies with known limitations. The intended software system is called the Value Added Data Products System (VADS). Precision corrected, Template Registered, Merged and Ortho Rectified products are the value added products planned with VADS.     

An automated seamless mosaicing system of multi-charge coupled devices of panchromatic data

Panchromatic data of pixel resolution 5.8 m obtained from IRS-1C and IRS-1D satellites proved to be very useful for mapping purposes. One of the popular data product is the 70 km swath mosaic which is covered by a combination of 3 CCD line sensors, each with 4096 pixels. Each CCD-line sensor with different imaging times causes geometric problems of mosaicing three strips data together. In this paper, we propose the details of the design elements of system that caters to the need for accurate and automatic multi strip image registration without any second resampling of the data. The systematic geometric correction grid mapping is improved to facilitate accurate mosaicing by automatic image registration task that makes use of the overlap data within image strips and image registration is achieved up to sub-pixel level.     

Political ecology of tiger conservation in India: Adverse effects of banning customary practices in a protected area

Protected areas have had significant impacts on local communities primarily through the physical removal of people. In some instances, people continue to live within protected areas due to the inability of the state to evict them. The restrictions on livelihoods placed on people living inside protected areas lead to in situ displacement. We show how conservation enclosures in the Biligiri Rangaswamy Temple Tiger Reserve have produced a class of people that the state ‘lets die’ by banning customary practices such as fire use, hunting and harvesting of forest produce. Using longitudinal ethnographic, socio‐economic and ecological data, we demonstrate that conservation policy has alienated indigenous forest dwellers from their agricultural and forest‐land. The outcomes of conservation policy include dispossession through increased crop losses, reduced income from agriculture and forest produce, as well as a forest that is dominated by weeds due to fire suppression. The ban on hunting in particular has increased wildlife densities, which has enabled the state to accumulate revenues through the establishment of wildlife tourism facilities. All in all, centralized protected area governance has changed the relationships among people, forest and the state in a way that has produced adverse effects for both livelihoods and the ecosystem.     

Subsidence in the Kathmandu Basin,before and after the 2015 Mw 7.8 Gorkha Earthquake,Nepal Revealed from Small Baseline Subset-DInSAR Analysis

Land subsidence in densely urbanized areas is a global problem that is primarily caused by excessive groundwater withdrawal. The Kathmandu Basin is one such area where subsidence due to groundwater depletion has been a major problem in recent years. Moreover, on 25 April 2015, this basin experienced large crustal movements caused by the Gorkha earthquake (Mw 7.8). Consequently, the effects of earthquake-induced deformation could affect the temporal and spatial nature of anthropogenic subsidence in the basin. However, this effect has not yet been fully studied. In this paper, we applied the SBAS-DInSAR technique to estimate the spatiotemporal displacement of land subsidence in the Kathmandu Basin before and after the Gorkha earthquake, using 16 ALOS-1 Phased Array L-band Synthetic Aperture Radar (PALSAR) images during the pre-seismic period and 26 Sentinel-1 A/B SAR images during the pre- and post-seismic periods. The results showed that the mean subsidence rate in the central part of the basin was about ?8.2 cm/year before the earthquake. The spatial extents of the subsiding areas were well-correlated with the spatial distributions of the compressible clay layers in the basin. We infer from time-series InSAR analysis that subsidence in the Kathmandu basin could be associated with fluvio-lacustrine (clay) deposits and local hydrogeological conditions. However, after the mainshock, the subsidence rate significantly increased to ?15 and ?12 cm/year during early post-seismic (108 days) and post-seismic (2015–2016) period, respectively. Based on a spatial analysis of the subsidence rate map, the entire basin uplifted during the co-seismic period has started to subside and become stable during the early-post-seismic period. This is because of the elastic rebound of co-seismic deformation. However, interestingly, the localized areas show increased subsidence rates during both the early-post- and post-seismic periods. Therefore, we believe that the large co-seismic deformation experienced in this basin might induce the local subsidence to increase in rate, caused by oscillations of the water table level in the clay layer.