Water-logging disaster is a most important environmental as well as socioeconomic problem which directly associated with the utilization of soil and land resources in agricultural command areas. Water resource management and conservation is a crucial approach for agricultural development in a basin area. To identify the maximum extent of waterlogged area in a basin during the pre-monsoon, monsoon and post monsoon season necessitated a multidisciplinary approach that integrates the spatial and non spatial attributes on Geographical Information System (GIS) that can be used by the decision makers for implement strategy of the problematic area in term of waterlogged and flood prone region. The main objective of the present investigation is to identify and mapping of the waterlogged disaster areas and it associated risk using an Analytical Hieratical Process and GIS model through ArcGIS model maker in the Keleghai river basin, India. For this purpose, the post monsoon multi-tem
In recent years educational variability has threatened the sustainability of elementary level in Indian educational system. Systematic methodology to assess the educational development of the elementary sector to educational variability is currently not available. Towards this end, the present paper pays attention with the assessment of spatial structure of Indian educational development to elementary levels in 35 states including union territories (UTs) of all over country. For this purpose, a set of indicators was selected for each of the four components of educational development index (EDI). The data were arranged in the form of diagonal matrix and normalized them using functional relationship. Upon receiving normalized values, here researchers consider a method of unequal weights followed. The choice of the weights in this manner would ensure that large variation in any one of the indicators would not unduly dominate the contribution of the rest of the indicators and distort inter states as well as union territories (UTs) comparisons. It is well known that, in statistical comparisons, it is more efficient to compare two or more means after equalizing their variances. The principal objectives of this article to identification of Hotspot and cold-spot and delineate the spatial cluster of upper primary education level in India based on Getis-Ord Gi* statistic using fixed distance band in ArcGIS software.
In the present paper, various groundwater potential zones for the assessment of groundwater availability in Keleghai river basin have been delineated using remote sensing (RS) and geographic information system (GIS) techniques. Survey of India (SOI) toposheets, field observations and satellite imageries are used to prepare various thematic layers viz. (a) drainage density, (b) geomorphology, (c) lineament density, (d) land use/land cover, (e) soil type, (f) water bodies density, (g) normalized difference vegetation index (NDVI), (h) slope and (i) mean annual rainfall were transformed to raster data using feature to raster converter tool in ArcGIS platform. The thematic maps have been ranked in a scale of 1-9 depending upon their suitability to hold groundwater. The rank of each map has been converted to a probability weight using Bayesian Decision Theory. Similarly, different categories of derived thematic maps were assigned scores in a numeric scale 1-9, depending upon their capability to store and transmit water. These scores were again converted capability values. This capability values ðcv i Þ were then multiplied with the respective probability weight of each thematic map to arrive at the final weight map. Integration analysis was carried out using overlay-intersect method and a composite groundwater potential map was generated. The composite potential index was obtained by multiplying weightages with rank numbers of each category and summing up the values of all categories. The resultant final map indicates the potentiality of groundwater occurrence in the study area. This map was then classified into five categorise based on the groundwater potential index value. The result depicts the groundwater potential zones in the study area and found to be helpful in better planning and management of groundwater resources.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.