Your search found 3 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 Mehmood, Q.; Mehmood, W.; Awais, M.; Rashid, H.; Rizwan, M.; Anjum, L.; Muneer, M. A.; Niaz, Y.; Hamid, S. 2020. Optimizing groundwater quality exploration for irrigation water wells using geophysical technique in semi-arid irrigated area of Pakistan. Groundwater for Sustainable Development, 11:100397. (Online first) [doi: https://doi.org/10.1016/j.gsd.2020.100397]
Groundwater ; Water quality ; Irrigation water ; Tube wells ; Semiarid zones ; Geophysics ; Techniques ; Aquifers ; Pumping ; Hydrogeology ; Models / Pakistan / Punjab / Okara District / Indus Basin
(Location: IWMI HQ Call no: e-copy only Record No: H049764)
(1.45 MB)
Geophysical method using vertical electrical sounding (VES) technique, in combination with borehole lithological data analysis was used to locate the subsurface layers containing good quality water in District Okara, Punjab Pakistan. Ten VES surveys (VES-1-10) were conducted by utilizing the Schlumberger electrode configuration. A calibrated model was developed for the study area by integrating the resistivity and lithological data. The model showed that the study area has three geoelectric layers below the water table with resistivities 50-100 O-m, 25-50 O-m and <25 O-m describing the good, marginal and poor quality water layers respectively. Integrated data analysis show that six sites (i.e., VES-1, VES-2, VES-3, VES-5, VES-7, & VES-10) have layers of good quality water at different depths. Out of these 6 sites, 3 sites (VES-3, VES-7 and VES-10) are suitable for installing the irrigation water wells in terms of water quality and potential while the remaining three sites (VES-1, VES-2 and VES-5) were not suitable due to shallow thickness of good quality aquifer. Three sites VES-3, VES-5 and VES-10 were selected for drilling in order to validate the modeled results, samples were collected from each 1.5–3.0 m depth for the laboratory analysis. The results showed that the resistivity data were in close agreement with the lithological data and VES-10 was most suitable for groundwater extraction. An Irrigation tube-well was installed at VES-10 and its quality was monitored for one year which showed successful supply of groundwater in terms of quality and potential.
3 Waqas, M. M.; Niaz, Y.; Ali, S.; Ahmad, I.; Fahad, M.; Rashid, H.; Awan, U. K. 2020. Soil salinity mapping using satellite remote sensing: a case study of Lower Chenab Canal System, Punjab. Earth Sciences Pakistan, 4(1):07-09. [doi: https://doi.org/10.26480/esp.01.2020.07.09]
Soil salinity ; Mapping ; Canals ; Irrigation schemes ; Satellite imagery ; Remote sensing ; Groundwater ; Landsat ; Normalized difference vegetation index ; Case studies / Pakistan / Punjab / Indus Basin / Lower Chenab Canal System
(Location: IWMI HQ Call no: e-copy only Record No: H050213)
https://earthsciencespakistan.com/archives/1esp2020/1esp2020-07-09.pdf
https://vlibrary.iwmi.org/pdf/H050213.pdf
https://vlibrary.iwmi.org/pdf/H050213.pdf
(0.31 MB) (318 KB)
Salinity is the most important factor of consideration for the water management policies. The water availability from the rootzone reduced with the increase in the soil salinity due to the increase in the osmatic pressure. In Pakistan, salinity is the major threat to the agriculture land due to the tradition practices of irrigation and extensive utilization of the groundwater to meet the cope the irrigation water requirement of high intensity cropping system. The salinity impact is spatially variable on the canal commands area of the irrigation system. There is dire need to map the spatially distributed soil salinity with the high resolution. Landsat satellite imagery provides an opportunity to have 30m pixel information in seven spectral wavelength ranges. In this study, the soil salinity mapping was performed using pixel information on visible and infrared bands for 2015. These bands were also used to infer Normalized Difference Vegetation Index (NDVI). The raw digital numbers were converted into soil salinity information. The accuracy assessment was carried out using ground trothing information obtained using the error matrix method. Four major classes of non-saline, marginal saline, moderate saline and strongly, saline area was mapped. The overall accuracy of the classified map was found 83%. These maps can be helpful to delineate hot spots with severe problem of soil salinity in order to prepare reciprocate measures for improvement.
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