Alejandro Blei Alejandro Blei is a Research Scholar in the Urban Expansion Program at the Marron Institute of Urban Management at New York University, USA. His research interests include global urban settlement mapping and the spatial structure of U.S. metropolitan areas. He was a research coordinator and coauthor of the Atlas of Urban Expansion.
Rostyslav Bun Rostyslav Bun is a Professor of Applied Mathematics at the Lviv Polytechnic National University, Lviv, Ukraine, and a Professor of Computer Science at the WSB University, Dąbrowa Górnicza, Poland. His research interest centers on modeling greenhouse gas emissions and geographic information systems. He is the author of 7 books and 300 papers. He was a Guest Editor of special issues of Climatic Change and Mitigation and Adaptation Strategies for Global Change, which were dedicated to the uncertainty in greenhouse gas inventory estimates.
Austin Bush Austin Bush is a field researcher for the Emergency Management and Homeland Security (EMHS) program at the Florida State University. He is also a doctoral student in the Department of Geography at FSU. His research interests focus on geographic information science, remote sensing, unmanned aircraft systems, and the integration of these technologies into emergency management in the United States.
Frank Canters Frank Canters is a Professor of remote sensing and geo‐information science in the Department of Geography at the Vrije Universiteit Brussel (VUB), Belgium. He is also a Guest Professor at Ghent University and at Katholieke Universiteit (KU) Leuven. Dr. Canters’ research focuses on remote sensing of urban areas, urban imaging spectroscopy, monitoring and modeling of urban dynamics, and on the role of urban form/function and urban green spaces in ecosystem service provision. Developing methods to extract information from remotely sensed data that is useful for local and regional decision making is an important concern in much of the work done by his team.
Guofeng Cao Guofeng Cao is an Assistant Professor in the Department of Geography at the University of Colorado Boulder, USA. His research is characterized by an interdisciplinary perspective on geographic information science driven by advances of spatial Big Data (e.g. social media and remote sensing), machine learning and artificial intelligence, and computational sciences. His research has been supported by different funding agencies. He has published over 60 peer‐reviewed papers and chapters. He received a PhD in Geography from the University of California, Santa Barbara.
Srija Chakraborty Srija Chakraborty is a NASA Postdoctoral Program Fellow at the Goddard Space Flight Center and Universities Space Research Association. She received her PhD in Computer Engineering at the Arizona State University with a focus on multitemporal analysis, and anomaly and novelty detection for monitoring and interpreting remote sensing observations. Her research interests center on ground‐based and onboard machine learning and statistical signal processing applications in Earth and Planetary Sciences.
Tzu‐Hsin Karen Chen Tzu‐Hsin Karen Chen is a PhD candidate majoring in Environmental Science at the Aarhus University, Denmark. Her research promotes a synergy of machine learning, remote sensing, and human–environment relations. Currently, she is investigating how urban form influences mental health through rural–urban migration. Her research has been published in Remote Sensing of Environment and Applied Geography. She served as a reviewer for several international journals.
Wendy Y. Chen Wendy Y. Chen is an Associate Professor at the Department of Geography, the University of Hong Kong (UHK). She also serves as the Director of the International Centre for China Development Studies, UHK. She is the Editor‐in‐Chief for Urban Forestry & Urban Greening, the top international journal in the field of urban forestry. Dr. Chen combines expertise in environmental science and economics to address the quantification of ecosystem services and economic valuation of nonmarket environmental goods as well as interactions between economic development and the environment. She has led several national and international research projects and published over 50 papers in peer‐refereed journals.
Yanhua Chen Yanhua Chen is a doctoral student at the Department of Geography, the University of Hong Kong. Her research interests include remote sensing, ecosystem services, and machine learning.
Alexandra A. Chudnovsky Alexandra Chudnovsky is an Associate Professor of Geography at the Tel‐Aviv University, Israel. Her research focuses on the understanding of ecological effects of air pollutants through integrating state‐of‐the‐art remote sensing techniques with GIS, environmental engineering, and advanced statistics. Using high‐resolution satellite measurements of aerosols, she evaluated the contribution of local and regional pollution sources to the urban air quality, which include anthropogenic activities in and outside cities and natural sources such as desert dusts. She authored or coauthored over 50 peer‐reviewed publications.
Sam Cooper Sam Cooper is a doctoral researcher at the Earth Observation Lab of the Humboldt‐Universität zu Berlin, Germany. He received his BS in Ecology and Environmental Sciences and MS in Geography from South Dakota State University, USA. His research interests focus on the use of remote sensing for mapping and monitoring natural and semi‐natural ecosystems, especially investigating the capability of imaging spectroscopy for such endeavors.
Jeroen Degerickx Jeroen Degerickx completed his PhD track on urban remote sensing at Katholieke Universiteit (KU) Leuven, Belgium in 2019, during which he focused on using hyperspectral and LiDAR data to characterize the urban environment. Currently, he is employed as R&D professional at the Flemish Institute for Technological Research (VITO) in Mol, Belgium, where he is building remote sensing applications in the domains of agricultural monitoring and smart farming. His personal mission is to harness the power of remote sensing for a more sustainable planet.
Sha Feng Sha Feng is an Assistant Research Professor in the Department of Meteorology and Atmospheric Science at the Pennsylvania State University, University Park, USA. Her research centers on carbon cycle science, particularly in the regional numerical modeling, an area in which she has played a leading role. She serves as a proposal review panelist for the National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, and Department of Energy, as well as a manuscript reviewer for more than 16 journals.
Dorothy Furberg Dorothy Furberg recently obtained her doctoral degree in Geoinformatics from KTH Royal Institute of Technology in Stockholm, Sweden. She obtained a master’s degree in international relations and worked for an environmental NGO in Geneva, Switzerland before taking up environmental engineering studies in Stockholm. She is currently a geodata project manager at the city environment unit of Stockholm City’s traffic office. Her main research interest is in the use of geographic information in support of sustainable urban development and environmental conservation in growing metropolitan regions, particularly Stockholm, Sweden.
Song Gao Song Gao is an Assistant Professor in GIScience at the University of Wisconsin‐Madison, USA. He holds a PhD degree in Geography at the University of California‐Santa Barbara, a M.S. degree in Cartography and GIS at Peking University, and a B.S. degree in GIS at the School of Geography, Beijing Normal University. His main research interests include Place‐Based GIS, GeoAI, Geospatial Big Data, and Social Sensing. He is the author of over 40 book chapters, journal, and conference papers. He is currently a board member of CPGIS and AAG GISS Specialty Group and an Associate Editor for Annals of GIS.
Taïs Grippa Taïs Grippa is a Geographer and Geomatician at the Institute for Environmental Management and Land‐use Planning (IGEAT), the Université Libre de Bruxelles (ULB). He received his PhD in 2019. His research activities mainly focus on using state‐of‐the‐art and open‐source GIS, remote sensing, and machine learning solutions for mapping land cover and land use from very high‐resolution satellite imagery.
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