scholarly journals Comparison between parametric and non-parametric methods for the spazialization of forest standing volume by integrating field measures, remote sensing data and ancillary data

2007 ◽  
Vol 4 (1) ◽  
pp. 110-117 ◽  
Author(s):  
R Bertini ◽  
G Chirici ◽  
P Corona ◽  
D Travaglini
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Parametric Methods ◽  
Ancillary Data ◽  
Sensing Data ◽  
Non Parametric

scholarly journals Non-parametric Methods for Soil Moisture Retrieval from Satellite Remote Sensing Data

2009 ◽  
Vol 1 (1) ◽  
pp. 3-21 ◽  
Author(s):  
Tarendra Lakhankar ◽  
Hosni Ghedira ◽  
Marouane Temimi ◽  
Manajit Sengupta ◽  
Reza Khanbilvardi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Satellite Remote Sensing ◽  
Remote Sensing Data ◽  
Parametric Methods ◽  
Sensing Data ◽  
Non Parametric

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.

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.  

scholarly journals Mapping soil degradation using remote sensing data and ancillary data: South-East Moravia, Czech Republic

2018 ◽  
Vol 52 (sup1) ◽  
pp. 108-122 ◽  
Author(s):  
Daniel Žížala ◽  
Anna Juřicová ◽  
Tereza Zádorová ◽  
Kateřina Zelenková ◽  
Robert Minařík
Keyword(s):  
Remote Sensing ◽  
Czech Republic ◽  
Soil Degradation ◽  
Remote Sensing Data ◽  
Ancillary Data ◽  
Sensing Data

Assessment of the national market demand for high-resolution remote sensing data

2002 ◽  
Vol 8 (1) ◽  
pp. 15-22
Author(s):  
V.N. Astapenko ◽  
◽  
Ye.I. Bushuev ◽  
V.P. Zubko ◽  
V.I. Ivanov ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Remote Sensing Data ◽  
Market Demand ◽  
Sensing Data ◽  
National Market
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