Ramasamy S.,Gandhigram Rural University |
Kumanan C.J.,Bharathidasan University |
Saravanavel J.,Bharathidasan University |
Rajawat A.S.,Marine and Earth science Group MESG |
And 2 more authors.
Journal of the Indian Society of Remote Sensing | Year: 2010
The coastal zones around the world are very densely populated and hence heavily packed with related infrastructures. So, the territorial nations have obvious apprehensions against the IPCC SRES (Intergovernmental Panel on Climate Change, Special Report on Emission Scenario) predicted sea level rise, as it would cause flooding of the low lying coasts and also other related chains of environmental endangers. This has driven these nations to initiate research studies in multiple directions for scientifically evaluating the phenomenon and impacts of sea level rise using all possible technologies including the Geomatics which possesses unique credentials in geosystem mapping. But certain advanced virtues available with Geomatics technology are yet to be capitalized deservingly in this. In addition, almost all the earlier studies have focused only on the impacts of sea level rise (SLR) and not on the predicted shift of high tide line (HTL) and the related inter tidal activities, which would cause a series of environmental disaster. Hence, the present research study was undertaken in a test site of 750 km2 in central Tamil Nadu coast to visualize the areas prone to submergence due to predicted SLR and areas prone to environmental disasters/degradation viz. erosion, deposition, salination of agricultural lands, pollution of aquifers, etc. due to predicted shift of HTL, using digital elevation models derived from SRTM data (Shuttle Radar Topographic Mission), geomorphology and land use/cover maps interpreted using IRS P6 LISS IV satellite data. The paper narrates the certain newer concepts and methodologies adopted in the study and the results. © 2011 Indian Society of Remote Sensing.
Singh S.K.,Marine and Earth science Group MESG |
Kulkarni A.V.,Marine and Earth science Group MESG |
Chaudhary B.S.,Kurukshetra University
Annals of Glaciology | Year: 2010
Reflectance data for contaminated and different grain-size snow were collected using a spectroradiometer ranging from 350 to 2500 nm. Contamination was predominantly due to soil. The radiometer data were binned at 10 nm intervals by averaging, and then principal component analysis, shape, size and strength of the absorption peak, first and second derivatives were computed, providing information about the effect of grain size and contamination on snow reflectance. Relative strength for contamination and grain size showed a distinct reverse pattern at 1025nm after continuum removal. Band absorption depth at 1025nm showed an increase with increasing snow grain size, whereas the band depth was found to decrease with increased soil contamination. The curve shape was right asymmetric and showed a change to left asymmetry with increase in contamination. The first derivative of reflectance in the visible region showed a shift of peak due to contamination. Soil contamination significantly reduced the albedo of snow at a low level of contamination but showed little influence at higher level. Relative strength, shape of curve and reflectance characteristics have shown the potential to identify the influence of contamination and grain-size based metamorphism using satellite-based hyperspectral remote sensing.