scholarly journals Identification of Groundwater Potential Zones of Visakhapatnam Urban Area using Integrating Multi Criteria Evaluation with Geographical Information System

2018 ◽  
Vol 7 (3.31) ◽  
pp. 234
Author(s):  
K M. Ganesh ◽  
G Jai Sankar ◽  
M Jagannadha Rao ◽  
R Subba Rao
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Data Interpretation ◽  
Groundwater Potential ◽  
Digital Data ◽  
Geographical Information ◽  
Human Beings ◽  
Groundwater Potential Zones ◽  
Ancillary Data ◽  
Sensing Data

Groundwater forms very little quantity when compared to the total water available on the earth. Therefore it is very vital for all living beings especially for human beings. Visakhapatnam, one of the fastest growing industrial city, is situated on the East Coast of India between longitudes E83o11’ 30” and 83o 22’ 16” and latitudes. N170 39’ 16” and 170 45’ 58”.   The present study is aimed to evaluate the groundwater occurrence using Remote sensing and GIS. Remote sensing data interpretation of visual and digital images gave the immediate information about surface features. From this information the groundwater potential zones are identified. The present study used IRS-IC (March 99) and ID (November 99) LISS-III digital data for comparative land use and land cover categorization and  hydrogeomorphological features identification and lineament study. The layers created from Remote sensing data and available ancillary data for index overlay operations for identification of groundwater potential zones in the study area using GIS.  

Groundwater potential zonation for basaltic watersheds using satellite remote sensing data and GIS techniques

2009 ◽  
Vol 1 (1) ◽  
Author(s):  
Biswajeet Pradhan
Keyword(s):  
Remote Sensing ◽  
Process Model ◽  
Remote Sensing Data ◽  
Groundwater Potential ◽  
Remotely Sensed Data ◽  
Drainage Pattern ◽  
Ancillary Data ◽  
Sensing Data ◽  
Gis Techniques ◽  
Gis Tools

AbstractThis paper summarizes the findings of groundwater potential zonation mapping at the Bharangi River basin, Thane district, Maharastra, India, using Satty’s Analytical Hierarchal Process model with the aid of GIS tools and remote sensing data. To meet the objectives, remotely sensed data were used in extracting lineaments, faults and drainage pattern which influence the groundwater sources to the aquifer. The digitally processed satellite images were subsequently combined in a GIS with ancillary data such as topographical (slope, drainage), geological (litho types and lineaments), hydrogeomorphology and constructed into a spatial database using GIS and image processing tools. In this study, six thematic layers were used for groundwater potential analysis. Each thematic layer’s weight was determined, and groundwater potential indices were calculated using groundwater conditions. The present study has demonstrated the capabilities of remote sensing and GIS techniques in the demarcation of different groundwater potential zones for hard rock basaltic basin.

Mapping of groundwater potential zones in the Musi basin using remote sensing data and GIS

2009 ◽  
Vol 40 (7) ◽  
pp. 506-518 ◽  
Author(s):  
Sreedhar Ganapuram ◽  
G.T. Vijaya Kumar ◽  
I.V. Murali Krishna ◽  
Ercan Kahya ◽  
M. Cüneyd Demirel
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Groundwater Potential ◽  
Groundwater Potential Zones ◽  
Sensing Data

scholarly journals Risk management support through India Remote Sensing Satellites

2014 ◽  
Vol XL-8 ◽  
pp. 1-6
Author(s):  
N. Aparna ◽  
A. V. Ramani ◽  
R. Nagaraja
Keyword(s):  
Remote Sensing ◽  
Risk Management ◽  
Satellite Data ◽  
Global Climate ◽  
Remote Sensing Data ◽  
Temporal Variations ◽  
Geographical Information ◽  
Indian Remote Sensing ◽  
Management Support ◽  
Sensing Data

Remote Sensing along with Geographical Information System (GIS) has been proven as a very important tools for the monitoring of the Earth resources and the detection of its temporal variations. A variety of operational National applications in the fields of Crop yield estimation , flood monitoring, forest fire detection, landslide and land cover variations were shown in the last 25 years using the Remote Sensing data. The technology has proven very useful for risk management like by mapping of flood inundated areas identifying of escape routes and for identifying the locations of temporary housing or a-posteriori evaluation of damaged areas etc. The demand and need for Remote Sensing satellite data for such applications has increased tremendously. This can be attributed to the technology adaptation and also the happening of disasters due to the global climate changes or the urbanization. However, the real-time utilization of remote sensing data for emergency situations is still a difficult task because of the lack of a dedicated system (constellation) of satellites providing a day-to-day revisit of any area on the globe. The need of the day is to provide satellite data with the shortest delay. Tasking the satellite to product dissemination to the user is to be done in few hours. Indian Remote Sensing satellites with a range of resolutions from 1 km to 1 m has been supporting disasters both National & International. In this paper, an attempt has been made to describe the expected performance and limitations of the Indian Remote Sensing Satellites available for risk management applications, as well as an analysis of future systems Cartosat-2D, 2E ,Resourcesat-2R &RISAT-1A. This paper also attempts to describe the criteria of satellite selection for programming for the purpose of risk management with a special emphasis on planning RISAT-1(SAR sensor).

scholarly journals Groundwater Potential Zones in Relation to Catchment Condition in Orenburg, Russia

2019 ◽  
pp. 60-65
Author(s):  
K Choudhary ◽  
M S Boori ◽  
A Kupriyanov
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Remote Sensing Data ◽  
Ground Truth ◽  
Groundwater Potential ◽  
Groundwater Potential Zone ◽  
Potential Zone ◽  
Ground Truth Data ◽  
Groundwater Availability ◽  
Sensing Data

The main objective of this study was to detect groundwater availability for agriculture in the Orenburg, Russia. Remote sensing data (RS) and geographic information system (GIS) were used to locate potential zones for groundwater in Orenburg. Diverse maps such as a base map, geomorphological, geological structural, lithology, drainage, slope, land use/cover and groundwater potential zone were prepared using the satellite remote sensing data, ground truth data, and secondary data. ArcGIS software was utilized to manipulate these data sets. The groundwater availability of the study was classified into different classes such as very high, high, moderate, low and very low based on its hydro-geomorphological conditions. The land use/cover map was prepared using a digital classification technique with the limited ground truth for mapping irrigated areas in the Orenburg, Russia.

Mapping of Groundwater potential zones in Lingasugur Taluk in North-eastern part of Karnataka, India using Remote Sensing, GIS and multi-criteria data analysis

2021 ◽  
Vol 14 (12) ◽  
pp. 13-22
Author(s):  
Ajgaonkar Swanand ◽  
S. Manjunatha
Keyword(s):  
Remote Sensing ◽  
Groundwater Resources ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Groundwater Exploration ◽  
Geographical Information ◽  
Groundwater Potential Zones ◽  
Thematic Maps ◽  
North Eastern

Groundwater research has evolved tremendously as presently it is the need of society. Remote Sensing (RS) and Geographical Information System (GIS) are the main methods in finding the potential zones for the groundwater. They help in assessing, exploring, monitoring and conserving groundwater resources. A case study was conducted to find the groundwater potential zones in Lingasugur taluk, Raichur District, Karnataka State, India. Ten thematic maps were prepared for the study area such as geology, hydrogeomorphology, land use/ land cover, soil type, NDVI, NDWI, slope map, lineament density, rainfall and drainage density. A weighted overlay superimposed method was used after converting all the thematic maps in raster format. Thus from analysis, the classes in groundwater potential were made as very good, moderate, poor and very poor zones covering an area of 10.1 sq.km., 169.25 sq.km., 1732.31 sq.km. and 53.66 sq.km. respectively. By taking the present study into consideration, the future plans for urbanization, recharge structures and groundwater exploration sites can be decided.

scholarly journals A Novel Rayleigh Dynamical Model for Remote Sensing Data Interpretation

2020 ◽  
Vol 58 (7) ◽  
pp. 4989-4999
Author(s):  
Fabio M. Bayer ◽  
Debora M. Bayer ◽  
Andrea Marinoni ◽  
Paolo Gamba
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Data Interpretation ◽  
Dynamical Model ◽  
Sensing Data
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