Your search found 2 records
1 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]
Satellite imagery ; Remote sensing ; Vegetation ; Climate change ; Temperature ; Precipitation ; Scrublands ; Grasslands ; Ecology ; Global positioning systems ; Land cover ; Assessment ; Cultivation / India
(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).
2 Thapa, R.; Gupta, S.; Guin, S.; Kaur, H. 2018. Sensitivity analysis and mapping the potential groundwater vulnerability zones in Birbhum District, India: a comparative approach between vulnerability models. Water Science, 32(1):44-66. [doi: https://doi.org/10.1016/j.wsj.2018.02.003]
Groundwater assessment ; Sensitivity analysis ; Mapping ; Models ; Forecasting ; Groundwater recharge ; Aquifers ; Hydraulic conductivity ; Soil types ; Land use ; Land cover / India / West Bengal / Birbhum
(Location: IWMI HQ Call no: e-copy only Record No: H048836)
https://www.sciencedirect.com/science/article/pii/S1110492917300085/pdfft?md5=51b266dc01392ceeef29146aaa27a3d4&pid=1-s2.0-S1110492917300085-main.pdf
https://vlibrary.iwmi.org/pdf/H048836.pdf
https://vlibrary.iwmi.org/pdf/H048836.pdf
(10.80 MB) (10.8 MB)
The assessment of groundwater vulnerability is essential especially in developing areas, where agriculture is the main source of the population. In the present study, four different overlay and index method, namely, DRASTIC, modified DRASTIC, pesticide DRASTIC and modified pesticide DRASTIC are implemented with a view to identifying the most appropriate method that predicts the vulnerable zone to groundwater pollution. Sensitivity analysis reveals that net recharge is the most influential parameter of the vulnerability index. Cross comparison of model output shows the highest similarity of 97% is observed between drastic and modified drastic while the maximum difference in models prediction of 49% is observed between modified drastic and pesticide drastic. Reported nitrate concentrations in groundwater are considered for validation of model-generated final output map. The prediction power of the models are assessed using success and prediction rate method and it highlights DRASTIC model as the most suitable model with 89.69% and 84.54% of the area under area under the curve (AUC) for success and prediction rate respectively.
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