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Earth Observation Data Analytics Using Machine and Deep Learning
Modern tools, applications and challenges
Earth Observation Data Analytics Using Machine and Deep Learning: Modern tools, applications and challenges covers the basic properties, features and models for Earth observation (EO) recorded by very high-resolution (VHR) multispectral, hyperspectral, synthetic aperture radar (SAR), and multi-temporal observations.
Approaches for applying pre-processing methods and deep learning techniques to satellite images for various applications - such as identifying land cover features, object detection, crop classification, target recognition, and the monitoring of earth resources - are described. Cost-efficient resource allocation solutions are provided, which are robust against common uncertainties that occur in annotating and extracting features on satellite images.
This book is a valuable resource for engineers and researchers in academia and industry working on AI, machine and deep learning, data science, remote sensing, GIS, SAR, satellite communications, space science, image processing and computer vision. It will also be of interest to staff at research agencies, lecturers and advanced students in related fields. Readers will need a basic understanding of computing, remote sensing, GIS and image interpretation.
About the Editors
Sanjay Garg is a former professor in the Computer Science and Engineering Department at the Institute of Technology, Nirma University, India. His research interests include data science, algorithms and pattern recognition. He has over thirty years of teaching experience. He has completed three funded research projects sponsored by ISRO under the RESPOND scheme and GUJCOST as principal investigator. He is a senior member of the IEEE.
Swati Jain is an associate professor in Computer Science and Engineering Department at the Institute of Technology, Nirma University, India. She works in the areas of machine learning, data analytics, and deep learning. She is currently working on four funded research projects, two of them under BRNS Department of Atomic Energy and two by ISRO. She is actively working on establishing a Center of Excellence in-Data Science in association with Binghamton University, USA.
Nitant Dube is group director of MOSDAC Research at the joined Space Applications Centre (SAC) and ISRO, India. His research fields include satellite image processing, big data analytics, AI/ML and its applications for Earth observation data, geo-intelligence and web-based processing. He is involved in the design and development of software for meteorological and oceanographic applications. He has been responsible for the design and development of data products and information processing systems for remote sensing satellites.
Nebu Varghese is an assistant manager (GIS) in the Land and Municipal Service at Dholera Industrial City Development Limited (DICDL), India. He works in the areas of GIS systems analysis and prepare design for new GIS methodologies, urban planning, satellite image processing and analysis, machine learning & deep learning. He has been involved in various government DST and ISRO funded projects. He is a member of ISPRS.
Publication Year:
2023
Pages:
244
ISBN-13: 978-1-83953-617-5
Format:
HBK
Editors:
Sanjay Garg, Swati Jain, Nitant Dube, Nebu Varghese