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Biomass Resources Assessment : Non-availability of accurate, reliable and up-to-date data for various biomass resources is the main reason hindering an accurate assessment of the bioresources of a region. Such data need to be obtained and updated periodically. Surveying, sampling and analytical procedures is used for the collection of this data. 1. Wood Biomass
2. Forrage Grasses and Shrubs
3. Residues and Wastes Crop Residues and Wastes
4. GIS in Bioresources Assessment and Monitoring Spatial data input, editing, maps creation, overlaying, reclassification and suitability analyses characterize the inventorying, monitoring and decision making process. Resource assessment include
In addition to remote sensing, spatial positioning technologies have begun to influence surveying techniques and, thus resource inventories. Global Positioning System (GPS) technology is based on a set of orbiting satellites (a total of 24), which provides three dimensional positional fixes with an accuracy within tens of meters. With four or more satellites in view, a GPS receiver can interpret the carefully timed satellite signals to determine geometrically the latitude, longitude and altitude at the operators position. GIS applications of GPS include georeferencing of satellite imagery and navigating to sample sites for ground truth exercises particularly relevant for forest and plantation inventories. 5. IRS-1C LISS -III Data for Bioresource Assessment 6. Interpretation of Remotely Sensed Data for Land Use / Land Cover 7. Sampling Frame An important initial objective is to develop the agro-ecological zonation to provide a valid basis for extrapolating the results of the supply survey to the regional level. The woody biomass and agricultural residues surveys requires a regional zonation which reflected the range of natural vegetation as well as agricultural land use. A suitable zonation is also required to provide a valid sampling frame to spatially link the results of the supply and demand surveys. The use of satellite imagery enables actual land cover classes to be mapped at a regional level, which is a more preferable approach to developing a valid and robust sampling frame. There are well-established methodologies for developing land cover zonation at national scales by using multi-temporal imagery to distinguish between patterns of vegetation activity with time. The imageries, with Geographic Information System and combined with ancillary data on rainfall, topography, climate, and the extent of irrigated farmland to produce a zonation of land cover types for the whole Region. Sampling units was selected within each IRS scene for field measurement of woody biomass and crop residues. Acquisition dates depends on cloud free period for both woody vegetation and crop sampling. This required a trade-off between the optimal season for classifying woody vegetation (June-July)_and for classifying crops at their stage of maximum greenness (March-April for the spring or rabi harvest and September for the autumn or kharif harvest). 8. Selection of Sampling units for Measurement of Woody Biomass Sampling units for field measurements of biomass fuels would fit within each scene. Both imagery, topographic maps, GPS were used the field work. Digital classifications of vegetation cover from the LISS be used as a second-level sampling frame for drawing field samples for the woody biomass survey. For a selection of primary sampling units for field work, to ensure robustness with respect to any variation in classification accuracy between images. The following approaches were used.
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