{"product_id":"9781032446523","title":"Multi-Sensor and Multi-Temporal Remote Sensing : Specific Single Class Mapping by Priyadarshi Upadhyay","description":"This book elaborates fuzzy machine and deep learning models for single class mapping from multi-sensor, multi-temporal remote sensing images while handling mixed pixels and noise. It also covers the ways of pre-processing and spectral dimensionality reduction of temporal data. Further, it discusses the `individual sample as mean' training approach to handle heterogeneity within a class. The appendix section of the book includes case studies such as mapping crop type, forest species, and stubble burnt paddy fields.   Key features:Focuses on use of multi-sensor, multi-temporal data while handling spectral overlap between classesDiscusses range of fuzzy\/deep learning models capable to extract specific single class and separates noiseDescribes pre-processing while using spectral, textural, CBSI indices, and back scatter coefficient\/Radar Vegetation Index (RVI) Discusses the role of training data to handle the heterogeneity within a classSupports multi-sensor and multi-temporal data processing through in-house SMIC softwareIncludes case studies and practical applications for single class mappingThis book is intended for graduate\/postgraduate students, research scholars, and professionals working in environmental, geography, computer sciences, remote sensing, geoinformatics, forestry, agriculture, post-disaster, urban transition studies, and other related areas.\u003cbr\u003eBinding: Paperback \/ softback","brand":"Gardners","offers":[{"title":"Default Title","offer_id":56295984071029,"sku":"9781032446523","price":45.99,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0612\/7193\/3106\/files\/9781032446523.jpg?v=1762769791","url":"https:\/\/backstory.london\/products\/9781032446523","provider":"Backstory","version":"1.0","type":"link"}