Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification

Kumar, Anil, Upadhyay, Priyadarshi, Kumar, A. Senthil

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商品描述

This book covers the state of art image classification methods for discrimination of earth objects from remote sensing satellite data with an emphasis on fuzzy based learning methods including applications for preparing land cover classification outputs from actual satellite data. It provides details about the temporal indices database using proposed class-based sensor independent approach supported by practical examples. Fuzzy based algorithms with machine learning algorithms to prepare land cover maps is discussed. Accuracy assessment for soft classification outputs are included and all algorithms are supported by in-house developed tool as Sub-pixel Multi-spectral Image Classifier. Aimed at researchers, graduate students, professionals in earth remote sensing, remote sensing image and data processing, geography and geoinformation science, image classification, this book Exclusively focuses on using fuzzy classification to remote sensing images Covers Sub Pixel Multi-Spectral Image Classifier Tool (SMIC) to support discussed algorithms Explains fuzzy and learning based classifiers with in-house developed SMIC tool Discusses how ANN, CNN, RNN and hybrid learning classifiers application on remote sensing images Combines explanation of the algorithms with examples, graph, and charts.

作者簡介

Anil Kumar is working as Scientist/Engineer-'SG' & Head Photogrammetry and Remote Sensing Department at Indian Institute of Remote Sensing (IIRS), Indian Space Research organisation (ISRO), Dehradun, India. He received his B.Tech degree in Civil Engineering from University of Lucknow, India and M.E. degre as well as inservise Ph.D in soft computing from Indian Institute of Technology, Roorkee, India. He has published 46 papers in journals. Guided 36 masters and 5 Ph.D thesis. He has been recipient of the prestigious P. R. Pisharoty Memorial Award conferred by the Indian Society of Remote Sensing. He is a life member of the Indian Society of Remote Sensing. His current research interests are in Soft computing, Deep Learning, Multi-sensor temporal data processing, Digital Photogrammetry, GPS and LiDAR.

Priyadarshi Upadhyay is working as a Scientist/Engineer-SD in Uttarakhand Space Application Centre (USAC), Dehradun, India. He received his M.Sc. degree in Physics from Kumaun University Nainital, India and M.Tech. degree in Remote Sensing from Birla Institute of Technology, Mesra Ranchi, India. He has received his Ph.D. degree from Indian Institute of Technology Roorkee, India in the area of time series remote sensing for single crop identification. He has published 15 research papers in various International Journals, Internation and National Conferences. He has been awarded by presitigious CSIR-NET, GATE and MHRD Travel Grant Fellowships. He is a life member of Indian Society of Remote Sensing and The Institute of Engineers (India). His current research interest are Microwave Remote Sensing for Soil Moisture and Crop Mapping, Polarimatric and Inerferrometric SAR, Hyperspectral and Optical Remote Sensing, Climate Change, Ecological Studies in Himalayan Region for Economically Important Crops and Plants.

A. Senthil Kumar is the Director of UN-affliated Centre for Space Science and Technology Education in Asia and the Pacific in Dehradun, India. He received M.Sc. (Engg.) and Ph.D. from the Indian Institute of Science, Bangalore in the field of image processing in 1985 and 1990 respectively. He joined ISRO in 1991. Since then he has served in Indian Remote Sensing programs in various capacities. He has published more than 120 technical papers in international journals and conferences and co-edited a book on Remote Sensing of Northwest Himalayan Ecosystems. He has received ISRO Team awards for his contributions to Chandrayaan-1 and Cartosat-1 missions. His research areas include remote sensing sensor characterization, radiometric data processing, image restoration, data fusion techniques and in soft computing techniques. He has also been a recipient of the prestigious Prof. Satish Dhawan Award conferred by the Indian Society of Remote Sensing. He is a life member of the Indian Society of Remote Sensing and the Indian Society of Geomatics.