Mapping of apple orchards using remote sensing techniques in cold desert of Himachal Pradesh,India

The present study was conducted to map Apple orchards in dry alpine Spiti region of Indian Himalaya using LISS III satellite image. The barren terrain with sparse woody vegetation helped in classification of apple orchards with 91.3 % accuracy. The orchards were found in 154.6 ha of the study area and are anticipated to expand owing to its economic importance.     

Remote Sensing and GIS Based Analysis of Geomorphic Evidences and Morphometry of Active Faults in Kachchh Area

Kachchh basin is a Mesozoic rift basin under the influence of many active faults. This in turn gives rise to marked structural complexity and associated seismicity. Remote Sensing study of geomorphic evidences of these faults has been carried out using satellite images and is validated using morphometric analysis and digital elevation model data. Satellite images not only help in identifying expression of active faults and active tectonics on a macroscopic scale, but also provide the image characteristics of active faults directly. A few faults along with nature of lateral displacement could be identified from the Kachchh area. Morphometric analysis viz., sinuosity, asymmetry factor and hypsometry indicated affected streams and drainage basins due to fault activity.     

Mapping of Coal Fire in Jharia Coalfield,India: a Remote Sensing Based Approach

In India, Jharia Coalfield (JCF) has one of the densest congregations of surface-subsurface coal fires known worldwide. Systematic investigation and quantification of actual scenario of coal fires in JCF is always necessary to plan sustainable mining, industrial growth and environmental remediation on a long term basis. The present approach involves evaluation and mapping of coal fire using ASTER (Advanced Spaceborne Thermal Emission and Reflection) data. Mapping reveals that the area located around western, eastern and south-eastern parts of JCF covering territories of Shatabdi opencast, Barora; Sijua opencast; Godhar colliery; Kusunda; Bokapahari; Kujama and Lodna are under intense fire with cumulative coverage of 6.23 km². The ASTER derived Land Surface Temperature (LST) of the anomalous areas have been subsequently validated by the field observations, carried out in JCF in February, 2010. The methodology adopted in the present study would provide precise evaluation and monitoring of coal fire in Jharia.     

An effective ensemble classification framework using random forests and a correlation based feature selection technique

Accurate classification of heterogeneous land surfaces with homogeneous land cover classes is a challenging task as satellite images are characterized by a large number of features in the spectral and spatial domains. The identifying relevance of a feature or feature set is an important task for designing an effective classification scheme. Here, an ensemble of random forests (RF) classifiers is realized on the basis of relevance of features. Correlation‐based Feature Selection (CFS) was utilized to assess the relevance of a subset of features by studying the individual predictive ability of each feature along with the degree of redundancy between them. Predictability of RF was greatly improved by random selection of the relevant features in each of the splits. An investigation was carried out on different types of images from the Landsat Enhanced Thematic Mapper Plus (Landsat ETM+) and QuickBird sensors. It has been observed that the performance of the RF classifier was significantly improved while using the optimal set of relevant features compared with a few of the most advanced supervised classifiers such as maximum likelihood classifier (MLC), Navie Bayes, multi‐layer perception (MLP), support vector machine (SVM) and bagging.     

Rice-acreage estimation for Orrisa using remotely sensed data

Rice is one of the most important foodgrains grown in India. Attempts have been made to estimate kharif rice acreage of Orissa state since 1986 using digital remote sensing data from Landsat MSS/TM and/or IRS-1A. Accuracies of the estimates obtained have been evaluated against BES (Bureau of Economics and Statistics) estimate. This paper describes the methodology adopted for rice acreage estimation of Orissa state, the results obtained for three years, i.e. 1986–87, 1988–89 and 1989–90, and their accuracy.     

Use of the Hilbert transform to interpret self-potential anomalies due to two-dimensional inclined sheets

Self-potential anomalies due to two-dimensional inclined sheet of finite depth extent are analysed from their horizontal and vertical derivatives via the Hilbert transform. The depths to the top and bottom of the sheet and the inclination are obtained by means of simple mathematical expressions. The method is applied to a theoretical example and to a field S.P. anomaly over a sulphide deposit in the Kalava fault zone of Cuddapah basin, India. The presence of random noise is analysed for various levels and its effect is discussed. This interpretation process can be automated for all practical purposes by simple programming.     

Landslide susceptibility assessment of the region affected by the 25 April 2015 Gorkha earthquake of Nepal

Nepal was hit by a 7.8 magnitude earthquake on 25^th April, 2015. The main shock and many large aftershocks generated a large number of coseismic landslips in central Nepal. We have developed a landslide susceptibility map of the affected region based on the coseismic landslides collected from remotely sensed data and fieldwork, using bivariate statistical model with different landslide causative factors. From the investigation, it is observed that most of the coseismic landslides are independent of previous landslides. Out of 3,716 mapped landslides, we used 80% of them to develop a susceptibility map and the remaining 20% were taken for validating the model. A total of 11 different landslide-influencing parameters were considered. These include slope gradient, slope aspect, plan curvature, elevation, relative relief, Peak Ground Acceleration (PGA), distance from epicenters of the mainshock and major aftershocks, lithology, distance of the landslide from the fault, fold, and drainage line. The success rate of 87.66% and the prediction rate of 86.87% indicate that the model is in good agreement between the developed susceptibility map and the existing landslides data. PGA, lithology, slope angle and elevation have played a major role in triggering the coseismic mass movements. This susceptibility map can be used for relocating the people in the affected regions as well as for future land development.     

A new find of lamproite dyke near Chintalapalle area,NW margin of the Cuddapah basin,eastern Dharwar craton,southern India

A singular outcrop of a lamproite dyke is located ~1.5 km south-west of Chintalapalle village at the NW margin of the Cuddapah basin, eastern Dharwar craton, southern India.. The dyke trends E-W and is emplaced within the granitic rocks belonging to the peninsular gneissic complex. The lamproite dyke has a porphyritic to weakly porphyritic texture comprising microphenocrysts of sanidine, and potassic richterite set in a groundmass rich in carbonate, and chlorite with rutile and titanate as accessory phases. This new occurrence of lamproite is located mid-way between the well-known Narayanpet kimberlite field towards the west and the Ramadugu and Vattikod lamproite fields in east. The Chintalapalle lamproite dyke, together with those from Vattikod, Ramadugu, Krishna and Cuddapah basin lamproite fields, constitute a wide spectrum of ultrapotassic magmatism emplaced in and around the Palaeo-Mesoproterozoic Cuddapah basin in southern India.