Reach Us +1-845-458-6882


Remote Sensing Change Detection Technique For Snow Cover Area On Himalayan Region | 9541
ISSN: 2155-9910

Journal of Marine Science: Research & Development
Open Access

Like us on:

Our Group organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)
Recommended Conferences
Google scholar citation report
Citations : 1720

Journal of Marine Science: Research & Development received 1720 citations as per google scholar report

Indexed In
  • CAS Source Index (CASSI)
  • Index Copernicus
  • Google Scholar
  • Sherpa Romeo
  • Open J Gate
  • Genamics JournalSeek
  • Academic Keys
  • ResearchBible
  • Ulrich's Periodicals Directory
  • Electronic Journals Library
  • RefSeek
  • Directory of Research Journal Indexing (DRJI)
  • Hamdard University
  • OCLC- WorldCat
  • Scholarsteer
  • SWB online catalog
  • Virtual Library of Biology (vifabio)
  • Publons
Share This Page

Remote sensing change detection technique for snow cover area on Himalayan region

International Conference on Oceanography & Natural Disasters

Devesh Khosla

Accepted Abstracts: J Marine Sci Res Dev

DOI: 10.4172/2155-9910.S1.004

Remote sensing is a valuable method to monitor larges area of Himalayan region and to perform change detection on different set of images to calculate area under snow because as daily changing atmospheric condition may effect on snow area of Himalayan region. The major task is to remove shadow and to get high spectral resolution image. So we proposed technique slow matching for removing shadow and done pan sharping to get high resolution image. After that we calculate area under snow and perform accuracy assessment with change detection to two different images. The experimental result shows that the effect of slope matching and pan sharpening is a valuable method for finding snow area with topographic correction in which overall accuracy of 95% ( Kappa coefficient 0.84) as compared to un topographic correction and un sharpening image in which overall accuracy is 90% (Kappa coefficient 0.78)