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1 Jul 19, 2017
MORPHOMETRIC ANALYSISOF NAR RIVER BASIN, RAMPUR BAGHELAN BLOCK, SATNA DISTRICT(M.P.) USINGREMOTESENSING AND GIS TECHNIQUE

In the present paper, an attempt has been made to study the drainage morphometry of Nar river basin. A drainage map of the study area has been prepared with the help of Arc GIS 10.3.1 The present study deals mainly with the geometry, more emphasis being placed on the evaluation of morphometric parameters such as stream order (Nu), stream length (Lu), bifurcation ratio (Rb), drainage density (D), stream frequency (Fs), elongation ratio (Re), circularity ratio (Rc) and form factor ratio (Rf) etc.The Morphometry analysis is mathematical calculation of the parameter likes stream order, bifurcation ratio, and drainage density and so on. study area selected is Nar river basin which is located in Rampur Baghelan block of Satna district of Madhya Pradesh state and covered between Longitude 80°58'40.546"E to 81°8'53.944" E and Latitude between 24°37'56.971"N 24°22'52.068"N. Different Morphometric parameters were calculated by spatial and nonspatial analysis of drainage basin with the help of Arc GIS software. The drainage density (Dd) of study area is 1.65 km/sqkm2.This study would help the local people to utilize the resources for sustainable development of the basin area....

Authors: Shweta Rai, Shyam Avtar, Shashikant Tripath.

2 Jul 19, 2017
GROUNDWATER POTENTIAL ZONE IDENTIFICATION BY ANALYTICAL HIERARCHY PROCESS (AHP) WEIGHTED OVERLAY IN GIS ENVIRONMENT - A CASE STUDY OF JHARGRAM BLOCK, PASCHIM MEDINIPUR

It is very important to reasonably develop and utilize groundwater resources in an area because groundwater resource is linked mainly with drinking purpose and different sectors like agriculture. And Jhargram is the township and only developing area in Jhargram subdivision. Shallow groundwater level is an essential factor related to the eco-environmental problems such as oasis degeneration and land salinification. GIS integration tool is proposed to demarcate the groundwater potential zone in a soft rock area using eight themes: geology, geomorphology, lineament, soil, drainage density, slope, land use/ land cover and the potentiality around stream channels. Except for net recharge and slope, the other five themes are derived from remote sensing data (LISS-IV). The potentiality around the major streams found from the primary field survey. Each feature of all the thematic maps was evaluated according to its relative importance in the prediction of groundwater potentiality. Finally, the weighted overlay analysis rank value assigned for each class for all the thematic layers according to their influence on ground water hydrology and factor weighted values are assigned according to analytical hierarchy process (AHP). The result shows the high potentiality areas are mainly north-eastern part around Kangsabati River and some valley fills areas near to Dulong Nala. Groundwater potentiality is very poor in the Jhargram township area and some parts of upland plains. The Remote Sensing and GIS plays the key role to explore the groundwater monitoring and open new paths to take needful guideline and proper management of the water resource....

Authors: Santanu Pani, Abhisek Chakrabarty, Sandhya Bhadury.

3 Jul 19, 2017
INFLUENCE OF FOREST TYPES ON SOIL CARBON SEQUESTRATION IN UTTARA KANNADA DISTRICT AS ASSESSED BY REMOTE SENSING AND GIS TECHNIQUE

The study was taken up in haliyal and Joida taluka of UK districts during the year 2012-2014. The study area lies between 140 55' N to 150 30' N Latitude and 740 15' E to 740 55' E Longitude. The IRS P6 LISS-III imageries were used for estimating the area under different land use land cover classes using ERDAS software with ground truth data collected from GPS. The land use land cover classes viz., Dense forest, , Horticulture plantation, Sparse forest, forest plantation, open land and Agriculture land were identified in supervised classification. According to the land use systems, soil samples at one meter depth were collected and soil organic carbon (SOC) was estimated. The result indicated that the SOC in soils of different land use classes are significantly different. The total and average SOC in Haliyal taluka was 11.257 million tonnes (in 81792 ha) and 123.55 t/ha respectively, similarly in Joida taluka was 20.69 million tone (in 177206 ha) and 83.59 t/ha, respectively. Among the different land use land cover classes, in haliyal taluka dense forest sequestered more SOC 184.08 t/ha, followed by horticulture plantaion (143.80 t/ha) where as in Joida taluka dense forest sequestered SOC of 120.36 t/ha followed by open land (73.80 t/ha). It is concluded that deciduous forest in Haliyal taluka sequestered more soil organic carbon compared to evergreen forest of Joida taluka due to more contribution from the leaf litter in deciduous forest hence forest types play an important role in sequestering atmospheric carbon in to the soil. Key words:Forest...

Authors: A.G. Koppad , B.S.Janagoudar , Rajakumar G.R..

4 Jul 19, 2017
ASTER DEM BASED GEOLOGICAL AND GEOMOR-PHOLOGICAL INVESTIGATION USING GIS TECHNOLOGY IN KOLLI HILL, SOUTH INDIA

Digital elevation models (DEMs) are increasingly used for visual analysis of topography, landforms, as well as model-ing of surface processes. DEM of study area is generated from ASTER DEM data of 30m resolution with using ArcGIS software. The analysis of the remote sensing data with conventional studies and sufficient ground truth infor-mation makes it easy to distinguish and demarcate the vari-ous ground features such as geology, structures, geomorpho-logical features and their characteristics. This study is an attempt to delineate the geology and geomorphology inter-pretation in Kolli hill, South India. The present study is done using an integrated approach of Remote Sensing and GIS techniques, especially ASTER DEM, by observing the ele-vation, aspect, slope, lineament, and shaded relief of images. DEM has been an excellent supplementary information da-tabase for interpretations in the present study area along with other data....

Authors: Gurugnanam.B, Kalaivanan.M, Bairavi.S.

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