Abstract

Extraction of water bodies from satellite imagery has been widely explored in the recent past. Several approaches have been developed to delineate water bodies from different satellite imagery varying in spatial, spectral, and temporal characteristics. The current study puts forward an automatic approach to extract the water body from a Landsat satellite imagery using a perceptron model. Perceptron involves classification based on a linear predictor function that merges few characteristic properties of the object commonly known as feature vectors. The feature vectors, combined with the weights, sum up to provide an input to the output function which is a binary hard limit function. The feature vector in this study is a set of characteristic properties shown by a pixelof the water body. Low reflectance of water in SWIR band, comparison of reflectance in different bands, and a modified normalized difference water index are used as descriptors. The normalized difference water index is modified to enhance its reach over shallowregions. For this study a threshold value of 2 has been proved as best among the three possible threshold values. The proposed method accurately and quickly discriminated water from other land cover features.

Abstract

The current study evaluates the growing stock, biomass and carbon content of Andhra Pradesh state’s forest (India) along with its current status of forest degradation and loss. For this purpose, the study used the growing stock data collected by state forest department in 2010 for the calculation of biomass and carbon storage using the standard conversion and expansion factors given by IPCC. The analysis shows low biomass and carbon values for the state’s forest in comparison to the mean values recorded in different studies made for Andhra Pradesh. It is also observed to be lower when compared with the average carbon and biomass for Indian forests. Overall, the analysis showed degradation and loss of forest in the state, coupled with reduction in biomass and carbon sink.

Abstract

The Jaisalmer district of Rajasthan province of India was known to suffer with frequent drought due to poor and delayed monsoon, abnormally high summer-temperature and insufficient water resources. However fl ood-like situation prevails in the drought prone Jaisalmer district of Rajasthan as torrential rains are seen to affect the region in the recent years. In the present study, detailed analysis of meteorological, hydrological and satellite data of the Jaisalmer district has been carried out for the years 2006−2008. Standardized Precipitation Index (SPI), Consecutive Dry Days (CDD) and Effective Drought Index (EDI) have been used to quantify the precipitation defi cit. Standardized Water-Level Index (SWI) has been developed to assess ground-water recharge-defi cit. Vegetative drought indices like Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI), Normalized Difference Vegetation Index (NDVI) and Modifi ed Soil-Adjusted Vegetation Index 2 have been calculated. We also introduce two new indices Soil based Vegetation Condition Index (SVCI) and Composite Drought Index (CDI) specifi cally for regions like Jaisalmer where aridity in soil and affects vegetation and water-level.

Abstract

Survival of plant species is governed by a number of functions. The participation of each function in species survival and the impact of the contrary behaviour of the species vary from function to function. The probability of extinction of species varies in all such scenarios and has to be calculated separately. Secondly, species follow different patterns of dispersal and localisation at different stages of occupancy state of the site, therefore, the scenarios of competition for resources with climatic shifts leading to deterioration and loss of biodiversity resulting in extinction needs to be studied. Furthermore, most possible deviations of species from climax community states needs to be calculated before species become extinct due to sudden environmental disruption. Globally, various types of anthropogenic disturbances threaten the diversity of biological systems. The impact of these anthropogenic activities needs to be analysed to identify extinction patterns with respect to these activities. All the analyses mentioned above have been tried to be achieved through probabilistic or graphical models in this study

Abstract

This research note focuses on the current climate change research scenario and discusses primarily what is required in the present global climate change conditions. Most of the climate change research and models predict adverse future conditions that have to be faced by humanity, with less emphasis on mitigation measures. Moreover, research ends as reports on the shelves of scientists and researchers and as publications in journals. At this juncture the major focus should be on research that helps in reducing the impact rather than on analysing future scenarios of climate change using different models. The article raises several questions and suggestions regards climate change research and lays emphasis on what we really need from climate change researchers.

Abstract

The scan-line corrector (SLC) of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor failed in May 2003, and this abnormal functioning of SLC resulted in about 22% of the pixels per scene without being scanned. By filling the un-scanned gap by a good technique will help in more use of ETM+ data for many scientific applications. While there have been a number of approaches developed to fill in the data gaps in ETM+ imagery, each method has shortcomings, especially they require SLC-on (images acquired before SLC-off anomaly) imagery for the same location to fill the gaps in SLC-off (images acquired after SLC anomaly) image. To overcome such shortcomings this study proposes an alternative interpolation method based on the partial derivative. This case study shows that this technique is very much useful to interpolate the missing pixel values in the SLC-off ETM+ data.

Abstract

The deterioration and loss of water bodies like lakes due to anthropogenic activities, are at the same pace at which forests are degraded. Lakes and ponds play a major role in the global cycle (carbon, water, etc.). They act as the basic units of hydrological systems to better understand the biogeochemical processes that take place within these aquatic systems and further for their management plans. As an initiative of managing resources at the unit level (lake) in the current study, we tried to understand the history and ecological dynamics of" Brahmayyalingam Cheruvu", a lake located in the peri-urban areas of the rapidly expanding Vijayawada city, Andhra Pradesh State, India. The study is based on field inventories, local surveys and satellite data, both current and past. Use of satellite images aided in capturing the changing spatiao-temporal lake dynamics due to climatic variations and government policy. The …

Abstract

One of the major challenges in the current scenario for ecological conservation is to quantify the forest landscape in its spatio-temporal domain and understand further implications of those. While the detailed study of the forest ecosystems may provide insights into biodiversity, carrying capacity and productive nature, most of the studies are restricted to single time/event inventory and focused on assessment of tree diversity patterns. Through the adoption of geospatial technologies like remote sensing and Geographical Information System (GIS), though forest monitoring has been possible, the linkages to the biodiversity distribution and its patterns are still at an empirical level, thus supporting broad measures of protection and preservation without accounting for the local/regional variability.

Abstract

Geometry in ecological patterns of landscape and vegetation is not truly fractal, and varies across a range of scales, whereas fractal geometry provides tools for predicting and describing ecological patterns. In this study, fractal analysis is used to assess presence of pseudo random quadrats or spatial dependence which hamper generality and performance of classical inferential statistics. Fractal dimension (FD) as a function of scale is used to determine quadrat size which eliminates spatial dependence. The semivariograms are plotted with fractograms to correlate structures of spatial dependence of the properties studied. The use of FD as a degree of spatial dependence of variables is the basis of applications of fractals.

Abstract

: Railway is the largest undertaking in the country. A retrospective study of prevailing conditions is necessary to assimilate the progress of the sector and how far have the changes introduced in previous few years been successful. The paper examines how the proposed changes in the Indian railways have changed the face of it through rigorous spatial analysis in diversified fields. A balanced analysis of shortcomings as well as achievements has been tried to be achieved through this paper for few selected regions of India.Each year there has to be more emphasis on enhancing the services provided. The rail budgets play a vital role and are responsible for taking care of it. The numerous promises made in terms of introduction of trains, electrification of routes, gauge conversion, doubling and increasing frequency of trains are made every year, in order to keep track of fulfillment of those decisions the spatial analysis is conducted rigorously. Railway has also witnessed a number of disasters in past few years; the spatial analysis conducted brings out few major reasons of those. A section of study also covers the topographic conditions in the state of Jammu and Kashmir that have not allowed the progress of railways in these regions.