Minimal Energy Efficient Routing (MEER) Protocol using GSP For Sensor Network

The most important criterion while designing wireless sensor network is the consumption of energy[5,6,7]. There are many schemes cited for conservation of energy issues[1,2,8]. Again the efficient minimal energy consumption routing schemes are an important consideration. In this paper, we have proposed an energy saving scheme, named as minimal energy efficient routing (MEER) Protocol, which uses GSP (Gossip based sleep Protocol) to achieve energy efficiency in sensor networks. Here, we have compared our work with the existing work given by GSP[1] . We have shown the correctness & effectiveness of our protocol by mathematical simulation studies

Evaluation of the influence of various physico-chemical parameters on coastal water quality, around Orissa, by factor analysis

360-364Physico-chemical parameters such as salinity, pH, DO, BOD, chlorophyll-a, nutrients (NO2 N, NO3-N, NH4-N, PO4-P, total phosphorus) and major ions (Ca2+, Mg2+, F) were studied during February-March, 1994 in the coastal waters off Orissa. Data comprising 13 variables obtained from 38 water samples have been subjected to R-mode factor analysis so as to understand the sources, the processes occurring and the influence of various physico-chemical parameters on coastal water quality. About 67.8 % of variance has accounted for three factors such as (i) river run-off or terrestrial input; high positive loading on nutrients with high negative loading on salinity implying that the nutrient economy in the coastal waters off Orissa is primarily dependent on the magnitude of river run-off; (ii) estuarine discharges which include remineralisation of organically bound materials into its dissolved inorganic form or oxidation product of ammonia; high positive loading on nitrite and high negative loading of pH and ammonia in second factor suggest the possibility of oxidation of ammonia to nitrite and (iii) land drainage (including waste discharged from domestic sewage, fertilizer plant and fresh water run-oft) has significant influence on fluoride content in coastal water.</span

New vegetation type map of India prepared using satellite remote sensing: Comparison with global vegetation maps and utilities

International audienceA 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. We used 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 23.5 m 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)

New vegetation type map of India prepared using satellite remote sensing: comparison with global vegetation maps and utilities

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)