|
|
|
GIS application for landuse/land cover management in context of wasteland – A case study of ferozepur Jhirka block in Haryana state
Methodology :
Methodologically speaking, the approach to spatial analysis involves the evaluation of natural resources in terms of its potential, limitations etc. and assessment of felt needs and priorities of the local people. Mainly map data was used for natural resources analysis and socio-economic data for need aspect analysis. Since the data sets were available in different forms, to standardize them, these were reformatted and suitably converted to a form amenable for data storage in GIS.
In this study ARC INFO GIS package was used. This package offers the capability to analyze multiple and wide-ranging types of spatial map data and attribute statistical and tabular data. The graphic (ARC) and tabular database management (INFO) components of this system combine together to offer a complete set of tools to store and handle geographical data. It can compare, as the maps and analysis illustrate, integrate and analyze different data sets in polygon, line or point form. The system provides basic software tools for interactively inputting the map data via digitization, and the tabular data via alphanumeric terminal. Integrated land system analysis approach was employed to determine the capability of the land - a measure of what the land can be best used for, and based on the capability, to recommend the developmental measure for the wasteland patches. Land evaluation through parametric approach was adopted for land capability classes to indicate the land potential. The land was classified at various levels which helped in identifying the homogeneous areas by ways of determining the internal homogeneity and heterogeneity quantitatively and validating the boundary between; the adjacent units. Attributes relating to land capability were mapped and analyzed to build up a land capability map.
Study of wasteland cannot be isolated from other lands and their uses as they are organically related. The relationship is best expressed in the causal relationship - structure <---> process <---> stage. In the context of natural environment it conveys the interdependence in the form of environment <---> land use <---> land productivity as the resultant or the state of land. Since land use and land productivity are influenced by socio-economic condition of the people it is man-made environment or human ecology that was taken the basis of resource evaluation and formulation of the development strategy. Techniques of spatial analysis adopted for the study of spatial distributional pattern of different attributes and their association were mainly cartographic using relatively simple quantitative techniques such as conversion of absolute values into ratios and areal concentration indices - with reference to medium values for the study area.
Quantification of qualitative data based on the spatial pattern of distribution of attributes relating to land quality such as conversion of relief map into slope map, drainage density as a value for the measurement of ruggedness of the terrain, estimation of land use under various categories and wasteland types was attempted. Measurement of the extent of association was done by preparing thematic maps of various attributes, superimposition of related spatial patterns, tabulation of the frequency distribution of different attributes into High, Medium and Low categories, grading them further according value range among each categories e.g. High values into Extremely High (EH), Very High (VH), High (H), High Medium (HM) etc. Similar grades of frequency were adopted among low values (EL, VL, L, LM, etc). Medium value was the average value for the study area. Secondary data on land use and population attributes were compiled from patwari records and census volume related to the study area. Village has been adopted as the areal unit for data compilation and generating the spatial pattern with cartographic techniques as mentioned above.
Broad land use comprising dense forests, degraded forests, barren and unculturable lands, land under pastures, areas not available for cultivation (settlement sites, communications, water bodies etc.) and cultivated areas have been identified from the satellite imageries of 1:50,000 scale and mapped on the same scale of topographical maps to facilitate interpretation of the spatial patterns of land use against the background of topographical and cultural features.
Wasteland is an integral part of all the land uses. The secondary data on seven attributes of broad land use compiled from patwari records were subject to similar processing for converting them into appropriate percentage values as shown on the maps and these percentage values were grouped around the medium value according to different frequency ranges. All the percentage values such as of net sown area, land put to non-agricultural use, barren and unculturable land and culturable waste were calculated with reference to total geographical area while spatial variations in the intensity of cultivation were brought out by mapping the percentage value of the area sown more than once with reference to net sown area.
Work participation rate was arrived at by calculating the percentage of workers to total population. Similarly land-man relationship was analyzed by calculating the percentage of workers in agriculture, industry and other services as defined in census. Spatial variations in the extent of workers in agriculture was studied by calculating the percentage of cultivators to total workers in agriculture and of landless people i.e. agricultural labourers.
Based on the study of landform - land use associations villages have been grouped into contiguous clusters according to homogeneity criteria and their characteristics stated with focus on area approach to problems in land use planning. These served to identify and evaluate the types of wasteland as they occur under different physical conditions.
For the evaluation of non-commercial energy, endogenously available resources were analyzed taking into consideration fuel wood, fodder, crop residue and dung. Database is very scarce and norms and ratios for converting raw materials into energy units are not available through very few empirical surveys. These have been applied to workout surplus/deficit scenario at village level and mapped for understanding the spatial variations and the backward linkage of non-commercial energy to the endogenously available resources (forest, grass, livestock, crops grown etc).
|
|
|