Advanced Environmental Monitoring with Remote Sensing Time Series Data and R
Alexandra Gemitzi
Sold by AHA-BUCH GmbH, Einbeck, Germany
AbeBooks Seller since August 14, 2006
New - Soft cover
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Add to basketSold by AHA-BUCH GmbH, Einbeck, Germany
AbeBooks Seller since August 14, 2006
Condition: New
Quantity: 1 available
Add to basketnach der Bestellung gedruckt Neuware - Printed after ordering - This book provides a step-by-step guide on how to use various publicly available remotely sensed time series data sources for environmental monitoring and assessment. Readers will learn how to extract valuable information on global changes from a 20-year collection of ready-to-use remotely sensed data through the free open statistical software R and its geographic data analysis and modeling tools. The case studies are from the Mediterranean region-a designated hot spot regarding climate change effects. Each chapter is dedicated to specific remote sensing products chosen for their spatial resolution. The methods used are adapted from large-scale to smaller-scale problems for different land cover areas.FeaturesIncludes real-world applications of environmental remotely sensed dataAnalyzes the advantages and restrictions of each data sourceFocuses on a wide spectrum of applications, such as hydrology, vegetation changes, land surface temperature, fire detection, and impactsIncludes R computer codes with explanatory comments and all applications use only freely available remotely sensed dataPresents a step-by-step processing through open source GIS and statistical analysis softwareAdvanced Environmental Monitoring with Remote Sensing Time Series Data and R describes and provides details on recent advances concerning publicly available remotely sensed time series data in environmental monitoring and assessment. This book is a must-have practical guide for environmental researchers, professionals, and students.
Seller Inventory # 9781032475073
This book provides a step-by-step guide on how to use various publicly available remotely sensed time series data sources for environmental monitoring and assessment. Readers will learn how to extract valuable information on global changes from a 20-year collection of ready-to-use remotely sensed data through the free open statistical software R and its geographic data analysis and modeling tools. The case studies are from the Mediterranean region―a designated hot spot regarding climate change effects. Each chapter is dedicated to specific remote sensing products chosen for their spatial resolution. The methods used are adapted from large-scale to smaller-scale problems for different land cover areas.
Features
Advanced Environmental Monitoring with Remote Sensing Time Series Data and R describes and provides details on recent advances concerning publicly available remotely sensed time series data in environmental monitoring and assessment. This book is a must-have practical guide for environmental researchers, professionals, and students.
Alexandra Gemitzi graduated from Aristotle University of Thessaloniki (Greece) in 1993 with a Bachelor degree in Geology and a Master of Science in Groundwater Engineering from University of Newcastle upon Tyne (UK) in 1995. She obtained a Doctorate from the Department of Civil Engineering of Aristotle University of Thessaloniki, sponsored by the National Scholarship Foundation. She is an Associate Professor at the Department of Environmental Engineering of Democritus University of Thrace (Greece). Before starting her academic career, she has worked as geologist for almost ten years in the private and public sector. Her main teaching and research interests are related to environmental modelling using Geographic Information Systems, coupling remote sensing and ground-based observations. Her research focuses on the simulation and assessment of environmental systems, climate and land use change effects and the prediction and risk assessment of extreme natural phenomena or natural disasters. Her published work features over 30 publications in peer reviewed journals and 50 conference presentations.
Venkat Lakshmi graduated from University of Roorkee in 1987 with a Bachelor degree in Civil Engineering and a Doctorate in Civil and Environmental Engineering in 1996 from Princeton. He worked at NASA Goddard Space Flight Center 1996-1999 as a research scientist. His areas of interest are catchment hydrology, satellite data validation and assimilation, field experiments, land-atmosphere interactions, satellite data downscaling, vadose zone and water resources. He is the Carolina Trustee Professor and former Chair of the Department of Earth and Ocean Sciences at the University of South Carolina and has over 80 peer-reviewed articles and 300 presentations and thesis supervisor for 20 graduate students. He is currently is serving as Associate Editor of Journal of Hydrology and editor for Vadose Zone Journal and former chairman of the Chapman Conference committee for AGU and the founding editor of Remote Sensing in Earth System Science. He has served as Cox Visiting Professor at Stanford University 2006-2007 and 2015-2016.
Nikos Koutsias is an Associate Professor at the Department of Environmental and Natural Resources Management of University of Patras, where he gives courses in remote sensing, GIS and spatial analysis. He obtained his diploma degree in Environmental Studies from the University of Aegean, his M.Sc. degree in Environmental and Renewable Resources from the Mediterranean Agronomic Institute of Chania
(MAICh), and his Ph.D. from the Department of Forestry and Natural Environment, Aristotle University of Thessaloniki. He had a post doctorate position at Geographic Information Systems division (GIS) in the Department of Geography of the University of Zurich. He has been working in the field of remote sensing and GIS with special emphasis on wildland fires, forestry and ecology for the last 25 years. He has participated in national and European projects and has several publications in journals, books, and international conferences. He is the recent recipient of a Marie Curie Individual Scholarship.
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