Paper
11 December 2006 Remote sensing and GIS based information system for sustainable resources planning at Panchayat level
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Abstract
Spatial databases of natural resources are very much essential to ensure enhanced productivity by conserving soil and water and to maintain ecological integrity of any region. Integration of various thematic layers prepared from high resolution data and detailed field survey would be preferred for grass root level planning (Panchayat) aimed to realize the potential of production system on a sustained basis. In this study, a detailed spatial data base was created for part of Kasaragod dist., Kerala, India. Detailed soil survey was carried out using cadastral map and registered over high resolution satellite data (IRS LISS-IV) which helped to identify problems and potentials of the area. Nearly 600 ha of land were found to be at higher erosion risk category out of ten soil series identified in the study area. Remote sensing data was used to prepare land use/land cover map and coconut (53%) followed by mixed vegetation type (16%) were found to be dominant. Soil site suitability assessment for major crops of the area was carried out and crossed with present land use to get the mismatch in land use/land utilization type. Alternate land use plan was prepared considering the potentials and problems of various available resources. Decision Support System (DSS) along with user interface is developed to support decision and extract relevant information. As organic carbon is one of the most important indicators of soil fertility C stock in the present and proposed land use was also estimated to understand the environmental significance.
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A. Velmurugan, S. Bhatt, and V. K. Dadhwal "Remote sensing and GIS based information system for sustainable resources planning at Panchayat level", Proc. SPIE 6411, Agriculture and Hydrology Applications of Remote Sensing, 64110Q (11 December 2006); https://doi.org/10.1117/12.694814
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KEYWORDS
Soil science

Decision support systems

Geographic information systems

Remote sensing

Data modeling

Carbon

Databases

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