Measuring Dynamics of Ecological Footprint as an Index of Environmental Sustainability at the Regional Level using Geospatial Information Technology

Ecological Footprint (EF) analysis is the spatial measurement of ecological load exerted by the humans on the earth that arises from the concept of sustainability and sustainable use of Earth's resources. A region-based EF study is conducted for Birla Institute of Technology, Mesra (India) campus to improve its sustainability. Highlight of the study is the explicitness of the methodology for determining the EF that incorporates analysis derived from conversion factors mentioned in the Ecological Footprint consultancy publications along with inputs from GIS domain. Questionnaire-based survey from the respondents regarding resource utilization and geospatial enumeration of land use land cover that harbors the population and their resources are the two integral parts of the analysis. Total EF of the institution campus is calculated to be 0.645 gha/ individual. This analysis provides a strong framework for combining efforts in a manner that can communicate the immediate priorities for improving the sustainability strategy of the campus area.

Wildlife Habitat Evaluation

Before an individual can evaluate wildlife habitat and make management recommendations, some basic concepts about habitat and its relationships to different wildlife species should be understood. In this chapter, some of the basic concepts will be described; mainly analyzing of habitat alterations, landscape analysis, networking and creation of corridor between protected areas, wildlife habitat suitability analysis using Remote Sensing & GIS. Since most of the contest will be based on these concepts. Like other natural resource fields, wildlife management is both an art and science that deals with complex interactions in the environment. This means that management includes art or judgment based on experience as well as sound factual information based on scientific studies.

Remote Sensing Techniques and Its Application in Arid Zones of India

Remote sensing technologies offer the potential for contributing the security to human existence on arid zones in the country in variety of ways. Remote Sensing in agriculture particularly for natural resource management. It provides important coverage, mapping and classification of land cover features. The remote view of the sensor and the ability to store, analyze, and display the sensed data on field maps are make remote sensing a potentially important tool for agriculture. The aerial photography gives two main advantages viz., speedy survey in very large area or remote area and precise description and recording of resources status. Remotely sensed images provide a means to assess field conditions and gave valuable insights into agronomic management. It led to understanding of leaf reflectance and leaf emittance changes in response to leaf thickness, species, canopy shape, leaf age, nutrient status, and water status. Understanding of leaf reflectance has led to quantify various agronomic parameters, e.g., leaf area, crop cover, biomass, crop type, nutrient status, and yield.

Space-Time Integrated Landslide Hazard Zonation near Tehri Dam in Uttarakhand, India

The study aims to predict landslide hazard zones near Tehri Dam in Uttarakhand State located in the Western Himalayas in India. Four different models were analysed: Weight Factor Model (M1), Multiple Factor Model (M2), Statistical Bivariate model (M3) and Analytical Hierarchical Processes (AHP) model (M4). Five different combination of reference landslides were used for deriving weights of the classes in the factor maps: all the landslides from 1990, 2002 & 2010 (C1); landslides from 2010 (C2); landslides from 1990 & 2002 (C3); landslides located within 500m from roads (C4); landslides located beyond 500m from roads (C5). The accuracy resulted from each model in each combination was [Mn:C1, C2…Cn]: M1: 60,44,46,38,66%; M2:70,76,79,73,71%; M3:45,37,23,36,85%; M4:64,51,51,64,36%. Multiple Factor Model (M2) resulted in a consistently high accuracy in all the combinations. Finally, the 20 different model outputs were integrated to derive unified hazard zonation maps based on: (a) mean (85% accuracy), (b) penalisation (57% accuracy) and (c) k-means cluster (80% accuracy) approaches.

Development of Web GIS Based Framework for Public Health Management System Using ERDAS Apollo 2010

This paper proposes a framework for an essential creation of a public health information visualization platform, for Japanese Encephalitis (JE) disease outbreaks in the Gorakhpur district, India. The Web GIS technology is used with ERDAS Apollo 2010 software at customized level, to develop architecture for Web GIS-based public health information systems. A GUI has been created using Java Server Pages (JSP) for its customization. This will help in extending the benefit of GIS and Web technology for public availability in the area for preparation of the health plan in multitier system.

Identification of Geospatial Objects Using Spectral Pattern

Solar radiation on hitting a target surface may be transmitted, absorbed or reflected. Different materials reflect and absorb differently at different wavelengths. The reflectance spectrum of a material is a plot of the fraction of radiation reflected as a function of the incident wavelength and serves as a unique signature for the material. In principle, a material can be identified from its spectral reflectance signature if the sensing system has sufficient spectral resolution to distinguish its spectrum from those of other materials. This premise provides the basis for multispectral remote sensing. Nguyen Dinh Duong (1997) proposed a method for decomposition of multi-spectral image into several sub-images based on modulation (spectral pattern) of the spectral reflectance curve. The hypothesis roots from the fact that different ground objects have different spectral reflectance and absorption characteristics which are stable for a given sensor. This spectral pattern can be considered as invariant and be used as one of classification rules.

Role of Remote Sensing in Potential Fishing Zone Forecast

Forecasting of Potential Fishing Zone (PFZ) is considered as economically and environmentally significant towards ensuring profitable base of economy and planning for sustenance of existing fishing pool. Changes in environmental conditions affect the distribution, abundance and availability of fish. The traditional sampling approaches for PFZ identification using boats and vessels are not only costly and time consuming but practically absurd considering the vastness of seas and oceans. In this chapter importance of alternative but effective methods of airborne and satellite remote sensing has been given. The chapter elucidates the factors for PFZ identification like thermal condition in sea controlling its thermal circulation, chlorophyll-a concentration estimated from ocean color dynamics, etc. Tools/system to prepare PFZ advisories and also the platforms for dissemination of the same, have been illustrated based on Indian scenario.

Land Use - Terrain Correlations in the Piedmont Tract of Eastern India

The Dulung River flows across West Bengal and Jharkhand in India. The geographical variables present within the basin area are categorised into groups like Physiographic, Morphometric and Land Use-Land Cover (LULC) attributes. These facets are mapped and overlain in a GIS environment and correlations drawn between them. Factor Scores obtained through Principal Component Analysis are further compared and correlated. The different variables are fused to obtain a comprehensive grouping of the above three facets that is reflective of the overall terrain attributes and its overlying LULC classes. Through this, within the Dulung River Basin, three broad Physiographic-Soil-Land Use Units (PSLUs) are identified, which comprise of the structural ridges and residual hills, piedmont plains and floodplains. For further insight into existing LULC-landform relations, select villages across the basin landscape are examined in detail. The relations derived help in suggesting possible land management practices in this region.

Improving the Efficiency of Image Interpretation Using Ground Truth Terrestrial Photographs

Researchers worldwide use remotely sensed imagery in their projects, in both the social and natural sciences. However, users often encounter difficulties working with satellite images and aerial photographs, as image interpretation requires specific experience and skills. The best way to acquire these skills is to go into the field, identify your location in an overhead image, observe the landscape, and find corresponding features in the overhead image. In many cases, personal observations could be substituted by using terrestrial photographs taken from the ground with conventional cameras. This chapter discusses the value of terrestrial photographs as a substitute for field observations, elaborates on issues of data collection, and presents results of experimental estimation of the effectiveness of the use of terrestrial ground truth photographs for interpretation of remotely sensed imagery. The chapter introduces the concept of GeoTruth – a web-based collaborative framework for collection, storing and distribution of ground truth terrestrial photographs and corresponding metadata.

A Review of Outline on Spectroscopic vis-a-vis Geochemical Study of Earth Analogues for Mars

It is widely recognized that interpretations about the planet Mars must begin by using Earth as a reference, because Earth analogues can provide ground truth to constrain interpretations on the geological history of Mars. Fortunately, Deccan Basalt and its derivatives, exposed in Kutch area of Gujarat, can be considered as best candidate from Indian subcontinent to approximate this analogue in terms of petrology, stratigraphy and geochemical similarity. It is believed that Deccan Volcanic province with its extensive volcanic plains, cones and craters as well as abundant hydrous sulphates of secondary origin, approximates the geological, geomorphological and environmental conditions on the Mars.