Description
The usability of Land Cover maps primarily depends on its accuracy. This book covers the development of an object oriented approach to land cover analysis and evaluate this approach along with five other classifiers for accuracy in classifying Level II land-cover categories in Ohio. These methods consist of (1) USGS National Land Cover Data; (2) the spectral angle mapper; (3) the maximum likelihood classifier; (4) the maximum likelihood classifier with texture analysis; and (5) a recently introduced hybrid artificial neural network. The author has Ph.D. in Geography from University of Cincinnati, with specialization in Remote Sensing and GIS. He has post graduate degree in Environmental Science from University of Cincinnati. He is currently working as an Assistant Professor in Symbiosis Institute of Geoinformatics(SIU), Pune, India.
