Mahendra Singh Nathawat

Assessment of land consumption rate with urban dynamics change using geospatial techniques

Land consumption is increasing rapidly with the exponential growth of population. The built-up environment configuration influences the management processes for development and other municipality works. Population growth also affects the availability of land for different purposes in its spatial distribution. The present study was conducted using satellite remote sensing data Landsat MSS (Multi-spectral Scanner), ETM+ (Enhanced Thematic Mapper), IRS P-6 (Indian Remote Sensing Satellite), LISS IV (Linear Imaging Self-Scanner), and IRS P-5 Cartosat-1 for the assessment of urban area change dynamics between years 1976 and 2008 in Bhagalpur city in the state of Bihar in India. The ground truth and coordinate points were collected using a Global Positioning System (GPS) for the location of the built-up themes prepared in the Geographic Information System (GIS). Land Consumption Rate (LCR) and Land Absorption Coefficient (LAC) were introduced to aid in the quantitative assessment changes. The results show a rapid growth in land consumption rate till 1976, reduction in 1999 and again increase in 2008.

A review of radar remote sensing for biomass estimation

Forest plays a vital role in regulating climate through carbon sequestration in its biomass. Biomass reflects the health and environmental conditions of a forest ecosystem. In context to the climate change mitigation mechanisms like REDD (reducing emissions from deforestation and forest degradation), an extensive forest monitoring campaign is especially important. Remote sensing of forest structure and biomass with synthetic aperture radar (SAR) bears significant potential for mapping and understanding forest ecological processes. Limitations of the conventional forest inventory procedures, like the extensive cost, labor and time, can be overcome through integrated geospatial techniques. Optical sensor or SAR data are suitable for extracting information about simple and homogeneous forest stand sites. However, optical sensors face serious limitations, specifically in tropical regions, like the cloud cover that SAR can overcome along with targeting saturation and penetration aspects. Simultaneous use of spectral information and image texture parameters improves the biomass assessment over undulating terrain and in radical conditions. Also, synergic use of multi-sensor optical and SAR has better potential than single sensor. Interferometric (InSAR) and polarimetric (PolSAR) SAR or a combination of the both (PolInSAR) serves as effective alternatives. These techniques could serve as valuable methods for biomass assessment of heterogeneous complex biophysical environments. However, SAR data have its own limitations and complexities. Identifying, understanding and solving major uncertainties in different stages of the biomass estimation procedure are critical. In this regard, the current study provides a review of radar remote sensing-based studies in forest biomass estimation.

Geospatial strategy for sustainable management of municipal solid waste for growing urban environment

This paper presents the implementation of a Geospatial approach for improving the Municipal Solid Waste (MSW) disposal suitability site assessment in growing urban environment. The increasing trend of population growth and the absolute amounts of waste disposed of worldwide have increased substantially reflecting changes in consumption patterns, consequently worldwide. MSW is now a bigger problem than ever. Despite an increase in alternative techniques for disposing of waste, land-filling remains the primary means. In this context, the pressures and requirements placed on decision makers dealing with land-filling by government and society have increased, as they now have to make decisions taking into considerations environmental safety and economic practicality. The waste disposed by the municipal corporation in the Bhagalpur City (India) is thought to be different from the landfill waste where clearly scientific criterion for locating suitable disposal sites does not seem to exist. The location of disposal sites of Bhagalpur City represents the unconsciousness about the environmental and public health hazards arising from disposing of waste in improper location. Concerning about urban environment and health aspects of people, a good method of waste management and appropriate technologies needed for urban area of Bhagalpur city to improve this trend using Multi Criteria Geographical Information System and Remote Sensing for selection of suitable disposal sites. The purpose of GIS was to perform process to part restricted to highly suitable land followed by using chosen criteria. GIS modeling with overlay operation has been used to find the suitability site for MSW.

Fuzzy AHP for forest fire risk modeling

Purpose – The purpose of study is linked to management and policy‐making strategies, such as forest management, land use planning and sustainable management of natural resources. It aims to help prevent forest fire by taking precautions. It also aims to be helpful for authorities coping during the event of occurrence of fire.Design/methodology/approach – The methodology paradigm applied here is based on knowledge‐based and analytic hierarchy process (AHP) techniques. Knowledge‐based criteria involve topographic and different themes for risk assessment. The assignment of value given to equation is significant due to its importance.Findings – Results are in strong agreement with actual fire occurrences in the past years. The risk zones are identified according to past occurrence of fire. The gradients of low‐ to high‐risk zones are according to fuel, topographic features and weather conditions. Direction and aspect value were taken accordingly.Originality/value – The paper presents forest fire risk zones de...

Use of Satellite Data, GIS and RUSLE for Estimation of Average Annual Soil Loss in Daltonganj Watershed of Jharkhand (India)

The present study demonstrated the utility of high resolution LISS IV satellite data for accurate mapping of landuse landcover which forms an important component while computing the land cover and management factor and erosion control practice factor for soil loss estimation using RUSLE model. The Cartosat-I DEM was used for computing the flow accumulation and the slope length (LS) factor with adequate precision. The results showed that the Daltonganj watershed has an average annual soil loss upto 69 tons ha -1 yr -1 . The maximum area contributing to soil erosion was from agricultural lands where the slope is less than 5˚ and having soil loss upto 10 tons ha -1 yr -1 however the maximum rate of soil erosion was observed near the upper catchment near the 6 th order river channel and over the hilly region with annual average soil erosion between 26 and 30 tons ha -1 yr -1 .

Water quality assessment of Majhiaon block of Garwa district in Jharkhand with special focus on fluoride analysis

Fluoride in groundwater is known to contaminate the water sources globally. Jharkhand, one of the states in the eastern part of India, is known to have excessive fluoride content in groundwater sources. The present work involves assessment of water quality with special reference to fluoride in Majhiaon block of Garwa district in Jharkhand. Iron, nitrate and arsenic were also tested for the water samples collected from site. Eight hundred forty samples were tested for fluoride on site using colourimetry method, and one tenth of the samples were brought to laboratory for iron, nitrate, arsenic and fluoride analysis. Results show that 402 samples were having fluoride above permissible limit. Iron and nitrate were found to be beyond permissible limits in 302 and 286 water samples, respectively. More than 50% of samples collected from school had fluoride levels above permissible limits. Arsenic was well within the limits. However, few samples shown were excessive of iron and nitrate.

A Rulebase physiographic characterization of a drought prone watershed applying remote sensing and GIS

Efficient micro-watershed management needs characterization of it to optimize natural resources, which is especially important in drought prone areas. In the present study micro-watersheds of Gandheshwari tributary in Chotta-Nagpur Plateau are characterized based on physiographic properties towards agricultural potentiality. An algorithm interpolating elevation values using an empirical formula is proposed to obtain an improved Digital Elevation Model (DEM). IRS LISS-Ill Satellite data is used to acquire important parameters like landuse/ landcover and drainage. Image processing techniques like edge enhancement, edge detection, and principal components analysis are used for improving lineament detection. For characterization of watershed landform analysis using physiographic parameters is done in Geographic Information System (GIS). Detailed drainage network obtained from satellite image, the improved DEM and other GIS layers of land based information are used to delineate micro-watersheds. The Agricultural 1-lydrologic Response Units (AHRU) targeting agricultural use of the land are derived by overlaying the delineated parameters and are grouped into thirty response units based on their agricultural potential. Micro-watersheds are characterized based on the dominant Al-IRU giving spatial information about agricultural suitability, emphasizing availability and scarcity of water so that respective water conservation practices can be improved to use the potential AHRU.

Analysing the impact of anthropogenic activities on waterlogging dynamics in Indo-Gangetic Plains, northern Bihar, India

Historical to recent spatial variability in surface waterlogging was evaluated using a topographical map of 1925 and satellite images of 1975, 1988, 1999 and 2006. A visual satellite image interpretation technique was used to delineate waterlogged areas and associated infrastructure details. Areas of 31, 73.89, 163.86, 143.61 and 102.59 km2 were found to be affected by surface waterlogging during 1925, 1975, 1988, 1999 and 2006, respectively. A sharp increase in waterlogging from 1925 to 1975 is attributed to the functioning of irrigation projects in the region. The very high areas under waterlogging during 1988 and 1999 reflect intensification of agricultural activity. A substantial decrease in waterlogging during 2006 is attributed to the implementation of government wasteland reclamation measures. The area statistics of waterlogging computed for the buffer zone along select features showed that the maximum waterlogging occurs along canals and railways followed by rivers and the least along roads.

Analysis of L-band SAR backscatter and coherence for delineation of land-use/land-cover

In this study, we investigated the potential improvement of land-use/land-cover (LU/LC) classification using multidate backscatter intensity as well as interferometric coherence images derived from Advanced Land Observing Satellite phased array L-band synthetic aperture radar data. Four interferometric synthetic aperture radar data pairs in horizontal–horizontal polarizations were processed to obtain backscatter intensity and coherence images. From the analysis of these images, it was observed that backscatter values alone are not sufficient to separate certain LU/LC classes, e.g. forest and mining areas, due to similarities in the associated scattering mechanisms producing similar backscatter values. However, the temporal coherence values from these LU/LC features were found to be distinctly different. Supervised classifications using maximum-likelihood distance were performed with various combinations of data (three-date backscatter intensity and two-date backscatter intensity with corresponding coherence data) to generate LU/LC maps of the study area. The comparison of classification accuracies obtained for different combinations of data indicates that the classification accuracy is improved by adding coherence information to the backscatter intensity data compared to using the multidate backscatter intensity data alone. Thus, the analysis of backscatter intensity along with coherence is a better alternative than using backscatter intensity alone to improve the accuracy in LU/LC classification.

Mapping of debris-covered glaciers in parts of the Greater Himalaya Range, Ladakh, western Himalaya, using remote sensing and GIS

Abstract Glacier inventories based on visual interpretation and manual delineation of glacier boundaries are time consuming. Supraglacial debris (debris accumulated on glacier terrain) of Himalayan glaciers creates difficulty with automated glacier mapping when using satellite images. In the present study, a combination of band ratio using the TM image and slope parameter was proven to be useful for delineating glaciers’ debris-covered areas. Compared to original TM bands, supervised classification using a combination of principal components two, three, and six of debris and nonglacierized areas facilitated identification of various types of supraglacial debris. Use of principal components four, three, and two of snow- and ice-covered areas as input bands for supervised classification was helpful in classifying different types of snow and ice. Results corresponded well with manually delineated glacier outlines and field observations. Error matrix revealed that the accuracy of classification of the snow- and ice-covered parts of glaciers was 86.29%. Although manual editing was required to differentiate supraglacial debris from periglacial debris (debris outside the glacier boundary), the approach using the ability of morphometric parameter combined with band ratio for delineation of debris-covered parts of glaciers and supervised classification with principal component analysis for mapping of supraglacial covers is observed to be faster than manual delineation.