Your search found 3 records
1 Dash, P.; Göttsche, F. M.; Olesen, F. S.; Fischer, H. 2002. Land surface temperature and emissivity estimation from passive sensor data: Theory and practice – current trends. International Journal of Remote Sensing, 23(13):2563-2594.
(Location: IWMI-HQ Call no: P 6040 Record No: H030219)
2 Dash, P.; Gottsche, F. M.; Olesen, F. S.; Fischer, H. 2005. Separating surface emissivity and temperature using two-channel spectral indices and emissivity composites and comparison with a vegetation fraction method. Remote Sensing of Environment, 96:1-17.
(Location: IWMI-HQ Call no: P 7658 Record No: H039404)
3 Roy, P. S.; Behera, M. D.; Murthy, M. S. R.; Roy, A.; Singh, S.; Kushwaha, S. P. S.; Jha, C. S.; Sudhakar, S.; Joshi, P. K.; Reddy, S.; Gupta, S.; Pujar, G.; Dutt, C. B. S.; Srivastava, V. K.; Porwal, M. C.; Tripathi, P.; Singh, J. S.; Chitale, V.; Skidmore, A. K.; Rajshekhar, G.; Kushwaha, D.; Karnatak, H.; Saran, S.; Amarnath, Giriraj; Padalia, H.; Kale, M.; Nandy, S.; Jeganathan, C.; Singh, C. P.; Biradar, C. M.; Pattanaik, C.; Singh, D. K.; Devagiri, G. M.; Talukdar, G.; Panigrahy, R. K.; Singh, H.; Sharma, J. R.; Haridasan, K.; Trivedi, S.; Singh, K. P.; Kannan, L.; Daniel, M.; Misra, M. K.; Niphadkar, M.; Nagabhatla, N.; Prasad, N.; Tripathi, O. P.; Prasad, P. R. C.; Dash, P.; Qureshi, Q.; Tripathi, S. K.; Ramesh, B. R.; Gowda, B.; Tomar, S.; Romshoo, S.; Giriraj, S.; Ravan, S. A.; Behera, S. K.; Paul, S.; Das, A. K.; Ranganath, B. K.; Singh, T. P.; Sahu, T. R.; Shankar, U.; Menon, A. R. R.; Srivastava, G.; Sharma, N. S.; Mohapatra, U. B.; Peddi, A.; Rashid, H.; Salroo, I.; Krishna, P. H.; Hajra, P. K.; Vergheese, A. O.; Matin, S.; Chaudhary, S. A.; Ghosh, S.; Lakshmi, U.; Rawat, D.; Ambastha, K.; Malik, A. H.; Devi, B. S. S.; Gowda, B.; Sharma, K. C.; Mukharjee, P.; Sharma, A.; Davidar, P.; Raju, R. R. V.; Katewa, S. S.; Kant, S.; Raju, V. S.; Uniyal, B. P.; Debnath, B.; Rout, D. K.; Thapa, R.; Joseph, S.; Chhetri, P.; Ramachandran, R. M. 2015. New vegetation type map of India prepared using satellite remote sensing: comparison with global vegetation maps and utilities. International Journal of Applied Earth Observation and Geoinformation, 39:142-159. [doi: https://doi.org/10.1016/j.jag.2015.03.003]
(Location: IWMI HQ Call no: e-copy only Record No: H047008)
(2.48 MB)
A seamless vegetation type map of India (scale 1: 50,000) prepared using medium-resolution IRS LISS-III images is presented. The map was created using an on-screen visual interpretation technique and has an accuracy of 90%, as assessed using 15,565 ground control points. India has hitherto been using potential vegetation/forest type map prepared by Champion and Seth in 1968. We characterized and mapped further the vegetation type distribution in the country in terms of occurrence and distribution, area occupancy, percentage of protected area (PA) covered by each vegetation type, range of elevation, mean annual temperature and precipitation over the past 100 years. A remote sensing-amenable hierarchical classification scheme that accommodates natural and semi-natural systems was conceptualized, and the natural vegetation was classified into forests, scrub/shrub lands and grasslands on the basis of extent of vegetation cover. We discuss the distribution and potential utility of the vegetation type map in a broad range of ecological, climatic and conservation applications from global, national and local perspectives. Weused 15,565 ground control points to assess the accuracy of products available globally (i.e., GlobCover, Holdridge’s life zone map and potential natural vegetation (PNV) maps). Hence we recommend that the map prepared herein be used widely. This vegetation type map is the most comprehensive one developed for India so far. It was prepared using 23.5m seasonal satellite remote sensing data, field samples and information relating to the biogeography, climate and soil. The digital map is now available through a web portal (http://bis.iirs.gov.in).
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