Monitoring Annual Land Use/Land Cover Change in the Tucson Metropolitan Area with Google Earth Engine (1986&ndash;2020)

Dubertret, Fabrice; Le Tourneau, François-Michel; Villarreal, Miguel L.; Norman, Laura M.

doi:10.3390/rs14092127

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Monitoring Annual Land Use/Land Cover Change in the Tucson Metropolitan Area with Google Earth Engine (1986–2020)

Fabrice Dubertret

^1,*,

François-Michel Le Tourneau

²,

Miguel L. Villarreal

and

Laura M. Norman

⁴

International Research Laboratory on Interdisciplinary Global Environmental Studies (IRL iGLOBES), National Scientific Research Center (CNRS), University of Arizona, 845 N. Park Avenue, Marshall Building 5th Floor, Tucson, AZ 85719, USA

National Scientific Research Center (CNRS)—Pôle de Recherche pour l’Organisation et la Diffusion de l’Information Géographique (PRODIG), Campus Condorcet, Bâtiment Recherche Sud, 5 Cours des Humanités, 93300 Aubervilliers, France

U.S. Geological Survey, Western Geographic Science Center, Moffett Field, CA 94035, USA

⁴

U.S. Geological Survey, Western Geographic Science Center, Tucson, AZ 85719, USA

Author to whom correspondence should be addressed.

Academic Editor: Parth Sarathi Roy

Remote Sens. 2022, 14(9), 2127; https://doi.org/10.3390/rs14092127

Received: 27 January 2022 / Revised: 19 April 2022 / Accepted: 26 April 2022 / Published: 28 April 2022

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Abstract

The Tucson metropolitan area, located in the Sonoran Desert of southeastern Arizona (USA), is affected by both massive population growth and rapid climate change, resulting in important land use and land cover (LULC) changes. As its fragile arid ecosystem and scarce resources are increasingly under pressure, there is a crucial need to monitor such landscape transformations. For such ends, we propose a method to compute yearly 30 m resolution LULC maps of the region from 1986 to 2020, using a combination of Landsat imagery, derived transformation and indices, texture analysis and other ancillary data fed to a Random Forest classifier. The entire process was hosted in the Google Earth Engine with tremendous computing capacities that allowed us to process a large amount of data and to achieve high overall classification accuracy for each year, ranging from 86.7 to 96.3%. Conservative post-processing techniques were also used to mitigate the persistent confusions between the numerous isolated houses in the region and their desert surroundings and to smooth year-specific LULC changes in order to identify general trends. We then show that policies to lessen urban sprawl in the area had little effects and we provide an automated tool to continue monitoring such dynamics in the future. View Full-Text

Keywords: land use classification; Landsat; Random Forest (RF); Google Earth Engine (GEE); cloud computing; urban sprawl; Arizona

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Dubertret, F.; Le Tourneau, F.-M.; Villarreal, M.L.; Norman, L.M. Monitoring Annual Land Use/Land Cover Change in the Tucson Metropolitan Area with Google Earth Engine (1986–2020). Remote Sens. 2022, 14, 2127. https://doi.org/10.3390/rs14092127

AMA Style

Dubertret F, Le Tourneau F-M, Villarreal ML, Norman LM. Monitoring Annual Land Use/Land Cover Change in the Tucson Metropolitan Area with Google Earth Engine (1986–2020). Remote Sensing. 2022; 14(9):2127. https://doi.org/10.3390/rs14092127

Chicago/Turabian Style

Dubertret, Fabrice, François-Michel Le Tourneau, Miguel L. Villarreal, and Laura M. Norman. 2022. "Monitoring Annual Land Use/Land Cover Change in the Tucson Metropolitan Area with Google Earth Engine (1986–2020)" Remote Sensing 14, no. 9: 2127. https://doi.org/10.3390/rs14092127

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Author Biographies

Fabrice Dubertret

Fabrice Dubertret holds a PhD in geography (2020) from Paris Sorbonne Nouvelle University and is currently a research engineer at CNRS. His various research interests revolve around Geographic Information Systems as a tool for empowerment, knowledge building and decision-making. They include the new uses of maps by Indigenous Peoples to assert their territorial rights, analysis of human-environment interactions and remote sensing for land cover classification. Fabrice is a co-founder of LandMark: global platform of Indigenous and Community Lands (www.landmarkmap.org) which is the first observatory on the worldwide situation of collective land rights.

François-Michel Le Tourneau

François-Michel Le Tourneau holds a phd in geography (1999) and is a senior research fellow at CNRS. He worked in several research labs located in French Universities (Paris Sorbonne Nouvelle, Université Paris 1 Panthéon-Sorbonne) or abroad (University of Brasilia in Brazil, The University of Arizona, USA). His research interests are about sparsely populated areas in general and the Amazon in particular. He is the author of a number of scientific papers in top journals in the geographical fields and of books for which he won several French awards (two times bronze medal of the French geographical society, Sophie Barluet Prize).

Miguel L. Villarreal

Miguel Villarreal is a Research Geographer with the USGS Western Geographic Science Center in Moffett Field, CA. Miguel received his MA and PhD from the School of Geography and Development at the University of Arizona. Miguel’s research is management-focused landscape ecology/geography, using remote sensing and spatial analysis to study the effects of natural disturbances and land use changes on plant and animal biodiversity and ecosystem services.

Laura M. Norman

Dr. Laura M. Norman is a research scientist and principal investigator in the Land Change Science Program at the Western Geographic Science Center of the U.S. Geological Survey. She has conducted international research for decades, exploring proactive management solutions, advantageous to shared environments via complex models that describe sediment transport and geomorphology, land use change and urban sprawl, watershed restoration, hydrologic response, hydraulics, and two-dimensional flow.

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Monitoring Annual Land Use/Land Cover Change in the Tucson Metropolitan Area with Google Earth Engine (1986–2020)

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