Knowledge discovery from GIS in 'Natural Resources Targeting'
Nihar R. Sahoo
Tata Infotech Limited, Noida
Email: nihar.sahoo@tatainfotech.com
Shishir K. Mahapatra
Exploration Business Analyst, Tata Petrodyne Limited New Delhi.
Email: shishir_m@hotmail.com
Abstract
With the advent of GIS Technology and its tremendous capability of handling complex spatial data, there has been ample of opportunities for an explicitly reasoned evaluation for decision making, however the extraction and comprehension of the knowledge implied by this huge amount of spatial data, poses a great challenge.
Often hard real-world problems, as to their larger size, formidable structure, complex dependencies, and with a definite objective, escape classical optimization techniques. The traditional approach of reducing size of this problem attempted few ways such as: removing less significant parameters, observations, constraint, ignores analysis of relevant constraints and uncertainties in the dataset. This activity of knowledge discovery requires a thorough analysis for extraction of implicit knowledge, spatial relations, patterns and nugget effect in spatial datasets. Further the possibly obvious data inadequacy and procedure of assigning credible weights to input data need to be analyzed.
This paper describes the process of knowledge discovery in exploring pattern or nature of data from Remote Sensing and GIS, and integration of data-layers in targeting natural resources. Potential application of logistic regression analysis in resource targeting has been described here. The capability of this tool in handling varied data-types, data-driven approach of factor-weighting and studying interactions of the evidences has been explained.