D. Ramakrishnan

Delineation of potential sites for water harvesting structures through remote sensing and GIS techniques: a case study of Kali watershed, Gujarat, India

Site suitability studies for check dams, percolation ponds, and subsurface dykes form an integral part of watershed management. This work illustrates the efficacy of remote sensing and GIS tools for identifying suitable sites for these structures. Thematic layers such as land use/land cover, lithology, soils, slope, rainfall and drainage were generated using LISS-III, PAN (IRS-1D), Landsat Thematic Mapper (TM) and collateral data. Runoff potential for different combinations of land use and hydraulic soil groups was computed and classified into three classes. A potential site suitability map for water harvesting/recharging structures was derived following an analytical hierarchy process. The analytically derived potential site suitability map was validated in the field. The accuracy of prediction was estimated on the basis of proximity between derived and field validated sites. In 75% of cases, the sites derived for check dam, percolation pond and subsurface dyke were accurate.

Probabilistic Techniques, GIS and Remote Sensing in Landslide Hazard Mitigation: A Case Study from Sikkim Himalayas, India

Abstract Landslides form one of the most devastating natural hazards in the Sikkim State of India. This natural hazard alone causes severe damage to properties and human lives. The identified conditioning factors include adverse rock types (mica schist, phyllite, granite gneiss and calc schist), multiple joint sets, active tectonism, and very high annual precipitation (3539 mm). The triggering factors are mainly rapid pore pressure built up, seismic activity and anthropogenic interference. This paper evaluates the landslide hazard zones using information theory (I) and regression analysis (R) in GIS environment. In all, 14 variables are identified as conditioning and triggering factors and accordingly probabilistic prediction maps are prepared individually by both the methods. The results thus generated are compared and classified into three slope instability zones viz. low (−0.143 < Ij < 0.02 & 0.38 < Rj < 0.55), medium (−0.02 < Ij < 0.103 & 0.55 < Rj < 0.73) and high ( Ij > 0.13 & Rj > 0.73) on the basis of histogram distribution. Further, these probabilistic prediction maps are compared with the actual landslide map generated from recent satellite data (January 2002) for the accuracy of prediction. The generated hazard maps agree with the observed landslide incidences. Thus, the proposed methodology can be utilized effectively in landslide hazard zonation studies.

A field technique for rapid lithological discrimination and ore mineral identification: Results from Mamandur Polymetal Deposit, India

This work illustrates the efficiency of field spectroscopy for rapid identification of minerals in ore body, alteration zone and host rocks. The adopted procedure involves collection of field spectra, their processing for noise, spectral matching and spectral un-mixing with selected library end-members. Average weighted spectral similarity and effective peak matching techniques were used to draw end-members from library. Constrained linear mixture modelling technique was used to convolve end-member spectra. Linear mixture model was optimized based on root mean square error between field- and modelled-spectra. Estimated minerals and their abundances were subsequently compared with conventional procedures such as petrography, X-ray diffraction and X-ray fluorescence for accuracy assessment. The mineralized zone is found to contain azurite, galena, chalcopyrite, bornite, molybdenite, marcacite, gahnite, hematite, goethite, anglesite and malachite. The alteration zone contains chlorite, kaolinite, actinolite and mica. These mineral assemblages correlate well with the petrographic measurements (R2 = 0.89). Subsequently, the bulk chemistry of field samples was compared with spectroscopically derived cumulative weighted mineral chemistry and found to correlate well (R2 = 0.91–0.98) at excellent statistical significance levels (90–99%). From this study, it is evident that field spectroscopy can be effectively used for rapid mineral identification and abundance estimation.

Noise-signal index threshold: a new noise-reduction technique for generation of reference spectra and efficient hyperspectral image classification

Reference spectra of terrestrial targets are usually collected using field spectro-radiometers for mineral abundance mapping and target detection. These spectra often have noise that masks characteristic absorption and reflection features and affects the efficiency of material mapping. This work aims at obtaining an empirical technique for reduction of high-frequency noise from field spectra. The proposed noise correction technique uses a ‘normalized’ measure Rn , where Rn = (Ln − Fn )/Ln for each band (n) calculated from field and laboratory spectra of test material, with Fn and Ln being the depth of the absorption feature in field and laboratory spectra, respectively. On the basis of the assumption of the constancy of this ratio in neighbouring bands, an empirical algorithm that approximates the ratio Rn of a noisy band to the corrected ratio of an adjacent band is used to obtain the noise-corrected field spectra. The classification accuracy increases significantly when noise reduced field spectra are used as reference spectra.

Spectral pathways for effective delineation of high-grade bauxites: a case study from the Savitri River Basin, Maharashtra, India, using EO-1 Hyperion data

Bauxite, the only source of aluminium, is an aggregate of minerals, most of which are oxides and hydroxides of aluminium and iron such as gibbsite, bohemite, goethite and haematite. Bauxite is used in the chemical and refractory industries and its quality is controlled by the presence of impurities such as iron and silica. Bauxite commonly occurs together with iron-rich laterites as alteration products of parental igneous and metamorphic rocks. Aluminium-rich bauxites grade towards highly ferruginous laterites with a transitional Al-rich laterites or ferruginous bauxite, herein described as Al-laterites. In the Savitri River Basin, bauxite contains 58–75% gibbsite, 6–11% goethite and 19–26% haematite, whereas the mineralogy of Al-laterites and Fe-laterites are dominated by haematite (29–68%) and goethite (6–25%) with subordinate amounts of gibbsite. Conventional techniques to demarcate the high-grade pockets of bauxites rich in gibbsite are tedious, time consuming and involve detailed field sampling and geochemical analyses. Our work illustrates how spectral properties of these three litho-units can be effectively utilized in mapping of high-grade bauxites occurring over wide areas using hyperspectral remote sensing (HRS). The methodology adopted herein involves generation of noise-free field spectral database of target materials, linear unmixing of field spectra for constituent minerals, classification of preprocessed Hyperion images using field spectra and finally accuracy assessment for ore grade estimation. It is observed that bauxite mapping using Hyperion data and noise-free field spectra yielded results that correlate well with the chemistry and mineralogy of representative samples. By adopting the above procedure, we achieved classification accuracies of 100%, 71% and 89% for bauxite, Al-laterite and Fe-laterite classes, respectively.

Uraniferous calcrete mapping using hyperspectral remote sensing

Calcrete, the calcium carbonate duricrust generally occurs in arid/semiarid region. Globally, it has been used as a non-traditional constructional material. The recent discovery of calcrete hosted secondary uranium deposits in Australia and Namibia has kindled interest in exploration of calcretes in many parts of the world. In this study, palaeochannel related calcretes of the Thar desert, India is explored as a possible source for uranium mineralization. The adopted exploration strategy includes mapping of calcretes using hyperspectral satellite data, in-situ radiometric survey, analyses of field collected samples for mineralogy and geochemistry. Calcretes along palaeochannels were mapped using Hyperion data, field spectra and Spectral Angle Mapper (SAM) technique. It was found that the adopted technique could also differentiate high-, and low-Mg calcretes with 72% accuracy. Mineralogy of calcrete includes calcite (40-60%), quartz (30-45%) and feldspar (10-15%) with minor amount of clay minerals (montmorillonite, kaolinite, illite, goethite). In in-situ radiometric survey, the range of uranium, thorium and potassium in the calcretes varies from 2.4-11ppm, 5-28.2ppm, and 0.8-4.2% respectively.

Compositional diversity of near-, far-side transitory zone around Naonobu, Webb and Sinus Successus craters: Inferences from Chandrayaan-1 Moon Mineralogy Mapper (M3) data

This study investigated the potential of Moon Mineralogy Mapper (M3) data for studying compositional variation in the near-, far-side transition zone of the lunar surface. For this purpose, the radiance values of the M3 data were corrected for illumination and emission related effects and converted to apparent reflectance. Dimensionality of the calibrated reflectance image cube was reduced using Independent Component Analysis (ICA) and endmembers were extracted by using Pixel Purity Index (PPI) algorithm. The selected endmembers were linearly unmixed and resolved for mineralogy using United States Geological Survey (USGS) library spectra of minerals. These mineralogically resolved endmembers were used to map the compositional variability within, and outside craters using Spectral Angle Mapper (SAM) algorithm. Cross validation for certain litho types was attempted using band ratios like Optical Maturity (OMAT), Color Ratio Composite and Integrated Band Depth ratio (IBD). The identified lithologies for highland and basin areas match well with published works and strongly support depth related magmatic differentiation. Prevalence of pigeonite-basalt, pigeonite-norite and pyroxenite in crater peaks and floors are unique to the investigated area and are attributed to local, lateral compositional variability in magma composition due to pressure, temperature, and rate of cooling.

Exploring the unusual uranium enrichment zones in the Thar Desert, India, using remote sensing, GIS and gamma-ray spectroscopy

In this work, unusual enrichment of uranium and thorium in duricrusts associated with palaeochannels, palaeo alluvial plains and delta of the Thar Desert, India, is investigated. Optical and microwave satellite data, digital elevation model and 3D geographic information system were used to identify exposed, buried channels and associated duricrusts. It is evident from field radiometric surveys, geochemistry of soil and groundwater samples that zones of higher uranium (max 190 ppm) and thorium (max 142 ppm) concentration exist in the Thar. These enrichments are unusual and could be of economic significance.

Spectral discrimination of Recent sediments around Bhuj, India, using Landsat-TM data and assessment of their vulnerability to seismicity-related failures

Kachchh region of India is a rift basin filled with sediments from Jurassic to Quaternary ages. This area is tectonically active and witnessed several major earthquakes since the recent historical past. During an earthquake event, the water-laden foundation soil liquefies and causes damage to buildings and other civil engineering structures. The January 26, 2001, Bhuj earthquake demonstrated extensive liquefaction-related damages in entire Kachchh Peninsula. Therefore, evaluation of liquefaction susceptibility of unconsolidated sediments is a vital requirement for developing seismic microzonation maps. In this paper, a new approach involving remote sensing techniques and geotechnical procedures is demonstrated for effective mapping of liquefaction-susceptible areas. The present and paleo-alluvial areas representing unconsolidated sediments were mapped using Landsat-TM data and field reflectance spectra. Spectral discrimination of alluvial area was made using the feature-oriented principal component selection and spectral angle mapping techniques. Subsequently, field geotechnical investigations were carried out in these areas. It is evident from the results that the alluvial soils are predominantly sandy loam with very low (7–28) standard penetration test values. The evaluated factor of safety for these soils varies from 0.43 to 1.7 for a peak ground acceleration of 0.38. Finally, a liquefaction susceptibility map is prepared by integrating results on alluvium distribution, factor of safety, and depth to water table.

Landslide hazard zonation of Tawaghat-Jipti route corridor, Pithoragarh, Uttaranchal State: using GIS and probabilistic technique approach

The stratigraphically important Tawaghat - Jipti Route corridor along Kali River Valley in Pithoragarh district of Uttaranchal State is characterized by formidable physical features. The lofty hill ranges, steep valleys, cliffs, gorges and huge accumulation of scree and debris mass owe their origin to complex physical, geologic and tectonic processes. Being a part of the active Himalayan orogenic belt, the natural hazards viz. landslides and earthquakes forms an integral part of the study area. In the investigated area, landslides are by far the most significant natural hazard in terms of damage caused to lives and properties. Landslides in the study area are triggered both due to natural phenomena (high rainfall, seismicity) and anthropogenic activities (road development and deforestation). Commonly observed slope failures include block slide, debris slide and earth creep. The presented study aims to develop a methodology that could produce a hazard map over a large area with higher degree of accuracy in a GIS environment; incorporating utility of information theory in landslide hazard zonation. In all, 37 variables are identified as conditioning and triggering factors and accordingly probabilistic prediction map is prepared by this method. On the basis of histogram distribution, the polygon elements are classified into five hazard classes viz. very low (Ij <= -0.02), Low (-0.02 < Ij < 0.103) moderate (0.10 0.40) landslide hazard prone zones. Further, this probabilistic prediction map is compared with the actual landslide map generated from recent satellite data (IRS ID LISS-III+PAN, December 2002) for the accuracy of prediction. The generated hazard maps agree with the observed landslide incidences. Thus, this adopted approach effectively proves its efficacy in deriving a reliable landslide hazard zonation.