Generation and study of satellite gravity over Gujarat,India and their possible correlation with earthquake occurrences

High-resolution satellite gravity data have been generated and utilized to infer subsurface geological structures in the area of devastating earthquake that struck the Bhuj region in Gujarat on 26 January 2001. Latitudinal gravity profiles have been generated in the Bhuj, Anjar and IBF regions across the epicentres (23.5° N, 69.8° E/M_w 7.0 in 2001; 23.2° N, 70° E/M_w 7.0 in 1956; 24.2° N, 69.2° E/M_w 7.8 in 1819). Substantial differences in gravity anomaly patterns as high as 37 mGal could be observed existing near the epicentre regions. These gravitational differences might have caused due to the plate tectonic processes and due to the changes in densities of different lithospheric zones/sedimentary layers. Temporal variations of the satellite-derived gravity and their probable relations with already occurred major earthquakes in this region have been studied. Hence we conclude that drastic changes in gravity anomalies can be considered as a precursor for occurrences of substantially large earthquakes.     

Plume and bloom: effect of the Mississippi River diversion on the water quality of Lake Pontchartrain

The opening of the Bonnet Carré spillway to prevent flood threat to New Orleans in April 2008 created a sediment plume in the Lake Pontchartrain. The nutrient rich plume triggered a massive algal bloom in the lake. In this article, we have quantified the spatio-temporal distribution of the plume (suspended solids) and the bloom (chlorophyll-a (chl-a)) in the lake using remotely-sensed data. We processed the Moderate-resolution Imaging Spectroradiometer satellite data for mapping the total suspended solids (TSS) and chl-a concentrations. An existing algorithm was used for estimating TSS whereas a novel slope model was developed to predict the per-pixel chl-a concentration. Both algorithms were successful in capturing the spatio-temporal trend of TSS and chl-a concentrations, respectively. Algal growth was found to be inversely related to TSS concentrations and a time lag of ～45 days existed between the spillway opening and the appearance of the first algal bloom at an observation location.     

Spectral material mapping using hyperspectral imagery: a review of spectral matching and library search methods

Imaging spectroscopy is an emerging and versatile technique that finds applications in diverse fields concerned with remote identification, discrimination and mapping of materials. The large amount of spectral data produced by hyperspectral imaging necessitates the development of automated techniques that convert imagery directly into thematic maps. Spectral library search method, a method of choice for organic compound identification by the mass spectroscopy, has caught the attention of researchers as one of the appropriate methods for an efficient exploitation of high quality spectral data available from the hyperspectral imaging systems. Given the apparent increase in the number of papers appearing on the subject as well as the variety of methods proposed, it is reasonable to say that the field of automated interpretation of reflectance spectral data has passed its infancy now gaining important space in the scientific community. We present an overall view of the literature relevant to the development of library search method, the various search algorithms and systems available in the purview for developing an automated hyperspectral data analysis system for material identification.     

Predicting agricultural drought in eastern Rajasthan of India using NDVI and standardized precipitation index

In the present study, prediction of agricultural drought has been addressed through prediction of agricultural yield using a model based on NDVI-SPI. It has been observed that the meteorological drought index SPI with different timescale is correlated with NDVI at different lag. Also NDVI of current fortnight is correlated with NDVI of previous lags. Based on the correlation coefficients, the Multiple Regression Model was developed to predict NDVI. The NDVI of current fortnight was found highly correlated with SPI of previous fortnight in semi-arid and transitional zones. The correlation between NDVI and crop yield was observed highest in first fortnight of August. The RMSE of predicted yield in drought year was found to be about 17.07 kg/ha which was about 6.02 per cent of average yield. In normal year, it was 24 kg/Ha denoting about 2.1 per cent of average yield.     

Use of high-resolution satellite data,GIS and NRCS-CN technique for the estimation of rainfall-induced run-off in small catchment of Jharkhand India

The present study demonstrates the use of NRCS-CN technique for rainfall-induced run-off estimation using high-resolution satellite data for small watershed of Palamu district, Jharkhand. The CN model was applied to the daily rainfall data of 15 years (1986–2000) along with use of large-scale thematic maps (1:10,000) pertaining to land use/land cover using IRS-P6 LISS-IV satellite data. The LU/LC map was spatially intersected with the hydrological soil group map to calculate the watershed area under different hydrological similar units for assigning CN values to compute discharge. The study showed that Daltonganj watershed exhibits an average run-off volume of 7,881,019 m³ from an average cumulative monsoon rainfall of 821 mm and the average actual direct run-off generated during the southwest monsoon season was 203 mm. The strong correlation between rainfall and run-off as well as between observed run-off and estimated run-off indicated high accuracy of run-off estimation by NRCS-CN technique.     

A Spatio‐Temporal Graph Model for Marine Dune Dynamics Analysis and Representation

Defining a model for the representation and the analysis of spatio‐temporal dynamics remains an open domain in geographical information sciences. In this article we investigate a spatio‐temporal graph‐based model dedicated to managing and extracting sets of geographical entities related in space and time. The approach is based on spatial and temporal local relations between neighboring entities during consecutive times. The model allows us to extract sets of connected entities distant in time and space over long periods and large spaces. From GIS concepts and qualitative reasoning on space and time, we combine the graph model with a dedicated spatial database. It includes information on geometry and geomorphometric parameters, and on spatial and temporal relations. This allows us to extend classical measurements of spatial parameters, with comparisons of entities linked by complex relations in space and time. As a case study, we show how the model suggests an efficient representation of dunes dynamics on a nautical chart for safe navigation.     

Field Measurements of Plant Emissivity Spectra: An Experimental Study on Remote Sensing of Vegetation in the Thermal Infrared Region

Spectral features of plant species in the visible to SWIR (0.4–2.5 μm) region have been studied extensively, but scanty attention has been given to plant thermal infrared (TIR: 4–14 μm) properties. This paper presents preliminary results of a study that was conducted first time in India to measure radiance and emissivity properties of eight plant species in TIR spectral region in the field conditions using a FTIR (Fourier Transform Infrared) field spectroradiometer working in 4–14 μm at an agriculture experimental farm. Several spectral features in the emissivity spectra of plant species were observed that are probably related to the leaf chemical constituents, such as cellulose and xylan (hemicellulose) and structural aspects of leaf surface like abundance of trichomes and texture. Observations and results from the field measurements were supported by the laboratory measurements like biochemical analysis. These preliminary field emissivity measurements of leaves in TIR show that there is useful spectral information that may be detectable by field-based instrument. More detailed field and laboratory measurements are underway to explore this research theme.     

Towards an integral strategy for modelling uncertain geospatial data

This paper endeavours to put the discussion on errors and uncertainties in geographical information systems (GISs) in a more systematic way by examining the strength and weakness of discrete objects and continous fields, the two distinct schools of spatial data modelling. In doing so, it argues that neither discrete objects nor continous fields alone provide objective and complete representations of highly complex geographical phenomena, though there are good reasons for asserting that continuous fields are better suited to modelling spatial dependence, heterogeneity and fuzzines significant in geographical reality than discrete objects. Thus, there seems to be merit in adopting an integrated model incorporating analytical capabilities of fields and generalization functions of objects, for which extended TIN (triangulated irregular network) models along with their duals (Voronoi diagrams) provide a pragmatical solution.