A geo-information system approach for forest fire likelihood based on causative and anti-causative factors

Innumerable forest fire spread models exist for taking a decision, but far less focus is on the real causative factors which initiate/ignite fire in an area. It has been observed that the majority of the forest fires in India are initiated due to anthropogenic factors. In this study, we develop a geo-information system approach for management of forest fire in Mudumalai Wildlife Sanctuary, Tamil Nadu, India, with the objective to develop a forest fire likelihood model, integrating GIS and knowledge-based approach for predicting fire-sensitive initiation areas considering major causative and anti-causative factors. Amongst the various causative factors investigated, it was found that wildlife-dependent factor (antler collection and poaching) contributed significantly to fire occurrence followed by management-dependent factors (uncontrolled tourism and grazing), with much less influence of demographic factors. Similarly, anti-causative factor (stationing of anti-poaching/ fire camps) was considered as quite significant.

The likelihood model so developed, envisaging various factors and flammability, accounted for different scenarios as a result of pair-wise comparison on an ordinal scale in a knowledge matrix. The inferential statistics computed indicated the robustness of the model and its insensitivity to moderate changes. It makes it possible for this forest fire likelihood model to predict and prevent a forest fire in an effective and scientific manner because it can assume forest fire likelihood in real time and present in proper time.     

Winter fog over the Indo-Gangetic Plains: mapping and modelling using remote sensing and GIS

Almost every year in the winter months (December–February), the vast Indo-Gangetic Plain south of the Himalaya is affected by dense fog. This fog is considered as radiational fog, and sometime it becomes smog (when it mixes with smoke). The typical meteorological, topographic and increasing pollution conditions over the Indo-Gangetic Plain are perhaps the common contributing factors for fog formation. In the present study, the North Indian fog has been successfully mapped and analysed using NOAA-AVHRR satellite data. In the winter seasons of 2005–06, 2006–07 and 2007–08, the fog-affected area has been found to cover about 575,800 km², 594,100 km² and 478,000 km², respectively. Less fog in 2007–08 may be the consequence of high fluctuations in the meteorological parameters like temperature, relative humidity and wind speed as related to the prevailing synoptic regime for that season. The dissipation and migration pattern of fog in the study area has also been interpreted on the basis of the analysis of both meteorological and satellite data. Further analysis of the fog-affected area allowed identifying more fog-prone regions. Analysis of past fog-affected days and corresponding meteorological conditions enabled us to identify favourable conditions for fog formation viz. air temperature 3–13°C, relative humidity >87%, wind speed <2 m/s and elevation <300 m. Based on the observations of past fog formation and corresponding governing parameters, fog for few selected days could be predicted in hind-sight and later verified with NOAA images.     

Two-Fluid Bianchi Type II Cosmological Models

In this paper we present a class of solutions of Einstein's field equations describing two-fluid models of the universe in a locally rotationally symmetric Bianchi type II space-time. In these models one fluid is the radiation distribution which represents the cosmic microwave background and the other fluid is the perfect fluid representing the matter content of the universe. It is found that both the fluids are comoving in the locally rotationally symmetric Bianchi type II space-time. The behaviour of the radiation density, matter density, the ratio of the matter density to the radiation density and the pressure has been discussed. A subclass of solutions is found to describe models of a spatially homogeneous and partially isotropic universe evolving from a radiation dominated era to a pressure free matter dominated era. This revised version was published online in July 2006 with corrections to the Cover Date.     

HI fluctuations at large redshifts: II — the signal expected for the GMRT

For the GMRT, we calculate the expected signal from red-shifted HI emission at two frequency bands centered at 610 and 325 MHz. The study focuses on the visibility-visibility cross-correlations, proposed earlier as the optimal statistical estimator for detecting and analyzing this signal. These correlations directly probe the power spectrum of density fluctuations at the redshift where the radiation originated, and thereby provide a method for studying the large scale structures at large redshifts. We present detailed estimates of the correlations expected between the visibilities measured at different baselines and frequencies. Analytic fitting formulas representing the salient features of the expected signal are also provided. These will be useful in planning observations and deciding an optimal strategy for detecting this signal.     

Geochemical alterations in surface waters of Govind Ballabh Pant Sagar,Northern Coalfield,India

Major ions showed high concentrations, ionic strength and chemical activity in the surface waters of Govind Ballabh Pant Sagar reservoir. Various geochemical ratios showed the dominance of silicate over carbonate weathering and major ions such as Na⁺ + K⁺ account for about 52 % of the cation budget. The high Na⁺ and K⁺ showed sedimentation of rock/coal particles consisting of highly weathered silicate minerals contributed by the discharge of mine water, fly ash mixing during transportation, etc. Further, Ca²⁺ + Mg²⁺/Na⁺ + K⁺ ratio was <1 (0.92) indicating the occurrence of silicate weathering in the reservoir catchment. The comparative assessment showed that the proportion of Ca²⁺ + Mg²⁺/Na⁺ + K⁺ tends to be lower along the coal mining belts compared to non-coal mining regions in the world. The Ca²⁺/SO₄ ^2? ratio <1 revealed not only H₂CO₃ but H₂SO₄ also acting as a source of protons for rock weathering. The cause underlying these differences can be related directly to geological substrate and anthropogenic activities.     

Earthquake damage identification: a case study using soft classification approach

The October 8, 2005, Kashmir earthquake (M _w 7.6) affected the rough mountainous regions of India and Pakistan with poor accessibility, and thus, no proper comprehensive ground survey was possible. However, due to the ability of remote sensing technology to acquire spectral measurements of damaged areas at various spatial and temporal scales, extraction of damaged areas can be carried out quickly and with great reliability. The fuzzy-based classifiers [Possibilistic c-Means (PCM), noise cluster (NC), and NC with entropy (NCE)] were applied to identify 2005 Kashmir earthquake, induced landslides, as well as built-up damage (BD) areas, as soft computing approaches using supervised classification. Results indicate that for the identification of landslides and BD areas, NCE classifier generated the best outputs, while for the identification of built-up undamaged areas, NC classifier generated the best output. Further, it was found that the proposed Class Based Sensor Independent (CBSI) technique can improve spectral information of specific class for better identification.     

Leaching behavior of lignite fly ash with shake and column tests

The maximum concentration of the majority of the trace metals in the leachates from shake and column test of lignite fly ash (LFA) was within the prescribed limits; however, total dissolved solids, total hardness, cations and anions (except K⁺), being above the prescribed limits, may lead to the increase in the hardness and salinity in the soil on the disposal of LFA. Present generation of huge amount of fly ash from thermal power plants (TPPs) is a big challenge concerning contamination of soil, crop produce and surface and ground water bodies due to the presence of some of the toxic trace metals in it. The leaching behavior of alkaline LFA (pH, 10.94), from TPP of Neyveli Lignite Corporation (NLC), India, was investigated by shake and column tests using water and sodium acetate buffer. The leaching of trace metals from LFA was governed by their concentrations, association with the ash particles, leaching duration and pH of the leachate (most influencing parameter). The leaching of metals followed the order: buffer column > aqueous column > aqueous shake > buffer shake test.