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Geo-spatial Analysis of Lesser Himalayan Landscape For Characterizing Resource Utilization Pattern (Nainital Lake Region)
Visual interpretation and Knowledge base classification
In mountain area, especially in Himalayas due to the terrain complexity, the spectrum signature is influenced by the elevation, the aspect and slope, which might have same objectives show different reflectance or the different objectives could have the same reflectance. In this situation, having the intensive ground truth, Knowledge base visual classification and on-screen visual recoding and rectification is employed to give best accuracy.
Land Use/Land Cover Mapping
Merged (LISS III + PAN) data was used as the source for the land use/land cover mapping. The interpretation key formulated during fieldwork has been used for preliminary land use mapping. Later the image was classified into cover types based on the knowledge based classification and the shadowed areas were put to corresponding classes on the basis of ground knowledge by recoding them. In order to achieve the more accuracy aspect and slope was used as important keys to differentiate the oak and pine.
Resource Mapping
After the land use/ land cover is finalized, the classes were regrouped into various resources available. Six classes are identified as agriculture, dry exposed rocks, forest, scrub/grassland and riverbed. The area dominates oak (dense and looped/open), deodar, pine (dense and open) and open mixed forest. Scrub and grassland include scrub/lowland grassland/pasture and highland grassland. The Resource map is prepared as input for studying resource distribution and resource utilization pattern.
Resource Utilization Pattern
The data collected from the field was analyzed and processed for the information extraction. Field data collected was divided into three types. One is direct information, which can be attributed to villages viz. quantity of agriculture land. Second is indirect information need to process and also can be attributed to villages, viz. Village consumption rates of fuel and fodder. Third is some general information regarding the alternative of resources?
Table 3: Field data types
| DirectAttribute | Population, household number, cattle population, land information, distance for collecting fodder and fuel wood, other energy utilization information… etc. |
| DerivedAttribute | Tree fodder requirement, grass fodder requirement, fuel wood requirement, cattle/capita, land/capita, agriculture land, forest land, grassland, etc. |
Fodder and fuel wood requirement evaluation
Fodder and Fuel wood are very important resources in Nainital watershed. The fodder and fuel wood consumption varies from village to village and from household to household. The calculated average consumption of fodder per cattle (Given that all the kinds of animals have the same requirements) and fuel wood per person from the sampled households. The tree fodder consumption is 5.19kg/day/cattle. The grass fodder consumption is 6.38kg/day/cattle. The fuel wood consumption is 4kg/day/person.
It is need to clarify that the type of fodder utilization is varying with seasons. During monsoon (from July to September), grass is preferred because it is available everywhere around the villages. While tree fodder and grass from highland is collected during the rest time of a year.
Resource Distribution Pattern
Natural resource distribution is uneven due to physiographic factors and human interventions. In the entire lake watershed, forest is well distributed in higher altitude and far from human settlements. Grasslands and scrub are dominated in the southern face and half-mountain area. Agriculture lands are located around the settlements, valley area, gentle slope and flat area. Terrain Accessibility Index (TAI) was calculated considering the terrain complexity viz. slopes (s max) and the maximum distance (d max) to collect the potential resource. The subjective weightage was given to the s max and d max to calculate the TAI. The TAI was used to calculate the plainmetric distance for the proximity analysis for calculation of the resource distribution of individual village.
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