Variability analysis of groundwater levels — AGIS-based case study

The present study has analyzed the variability in depth to water level below ground level (bgl) vis-à-vis groundwater development and rainfall from 1987 to 2007 in agriculture dominated Kaithal district of Haryana state in India. Spatial distribution of groundwater depth was mapped and classified into different zones using ILWIS 3.6 GIS tools. Change detection maps were prepared for 1987–1997 and 1997–2007. Groundwater depletion rates during successive decades were compared and critical areas with substantial fall in groundwater levels were identified. Further, block wise trends of change in groundwater levels were also analyzed. The water table in fresh belt areas of the district (Gulha, Pundri and Kaithal blocks) was observed to decline by a magnitude ranging from 10 m to 23 m. In Kalayat and Rajaund blocks, the levels were found fluctuating in a relatively narrow range of 4–9 m. During 1997–2007, the depletion has been faster compared to the preceding decade. Excessive groundwater depletion in major part of the district may be attributed to indiscriminate abstraction for irrigation and decrease in rainfall experienced since 1998. Changes in cropping pattern and irrigation methods are needed in the study area for sustainable management of the resource.     

Entropy-based fuzzy classification parameter optimization using uncertainty variation across spatial resolution

In the past researchers have suggested hard classification approaches for pure pixel remote sensing data and to handle mixed pixels soft classification approaches have been studied for land cover mapping. In this research work, while selecting fuzzy c-means (FCM) as a base soft classifier entropy parameter has been added. For this research work Resourcesat-1 (IRS-P6) datasets from AWIFS, LISSIII and LISS-IV sensors of same date have been used. AWIFS and LISS-III datasets have been used for classification and LISS-III and LISS-IV data were used for reference data generation, respectively. Soft classified outputs from entropy based FCM classifiers for AWIFS and LISS-III datasets have been evaluated using sub-pixel confusion uncertainty matrix (SCM). It has been observed that output from FCM classifier has higher classification accuracy with higher uncertainty but entropy-based classifier with optimum value of regularizing parameter generates classified output with minimum uncertainty.     

Accuracy improvement of ASTER stereo satellite generated DEM using texture filter

The grid DEM(digital elevation model) generation can be from any of a number of sources:for instance,analogue to digital conversion of contour maps followed by application of the TIN model,or direct elevation point modelling via digital photogrammetry applied to airborne images or satellite images.Currently,apart from the deployment of point-clouds from LiDAR data acquisition,the generally favoured approach refers to applications of digital photogrammetry.One of the most important steps in such deployment i...     

Sustainable Utilisation of Water Resource in Watershed Perspective - A Case Study in Alaunja Watershed, Hazaribagh, Bihar

Alaunja watershed, located on ‘Chotanagpur’ plateau of Bihar, is mainly under single cropping. The area receives more than 1000 mm of rainfall but it has not been utilised properly to increase the agricultural output. The remote sensing, geophysical, DBTM (Digital Basement Terrain Model) and GIS (Geographic information System) techniques were used for providing scientific database for sustainable utilisation of water resources in watershed perspective. The landuse, soil and surface water body maps have been prepared using remotely sensed data. DBTM has been generated based on depth of basement information derived from geophysical data to provide information regarding aquifer geometry, fracture zones and sub-surface basins. Analysis indicated that surface and groundwater resources have potential to irrigate 53 per cent of geographical area of the watershed. But at present, this available potential has been utilised only to irrigate 7.03 per cent area of the watershed. Feasibility for large scale development of groundwater through dugwell is possible only in 2 per cent area of the watershed. The available groundwater potential to irrigate 28 per cent area of watershed can not be utilised through dugwells. The surface water potential is also poorly utilised. The present study also helped in prioritising the water resource development activities.     

Delineation of geology of a part of bundelkhand complex around girar, distt. lalitpur, u.p., using remote sensing data

An attempt is made to mark regional geology of part of Lalitpur district. The area is characterized by flat topography gently sloping east ward with isolated hillocks. The well contrasted lithology has been marked on the basis of variation in tone, drainage pattern and texture. The main lithounits are foliated granites/gneiss, banded iron formation, granites, ultra basic, quartz reef and basic dykes. The structural elements of lineaments are visible on aerial photos and imagery which range in length from 1 to 10 km. The lineaments at places intersect with each other. The major trends are NNW- SSE. NE- SW. NNH- SSW. These NNW- SSE and NE-SW lineaments are retlected by well aligned body of quartz- sericite schist and quartz reef respectively.     

Multiple statistical approaches for the discrimination of mangrove species of Rhizophoraceae using transformed field and laboratory hyperspectral data

This study aims at discriminating eight mangrove species of Rhizophoraceae family of Indian east coast using field and laboratory spectra in spectral range (350–2500 nm). Parametric and non-parametric statistical analyses were applied on spectral data in four spectral modes: (i) reflectance (ii) continuum removed, (iii) additive inverse and (iv) continuum removed additive inverse. We introduced continuum removal of inverse spectra to utilize the advantage of continuum removal in reflectance region. Non-parametric test gave better separability than parametric test. Principal component analysis and stepwise discriminant analysis were applied for feature reduction and to identify optimal wavelengths for species discrimination. To quantify the separability, Jeffries–Matusita distance measure was derived. Green (550 nm), red edge (680–720 nm) and water absorption region (1470 and 1850 nm) were found to be optimal wavelengths for species discrimination. The continuum removal of additive inverse spectra gave better separability than the continuum removed spectra.