Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability...

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Bibliographic Details
Published in:PloS one 2017-09, Vol.12 (9), p.e0184926-e0184926
Main Authors: Midekisa, Alemayehu, Holl, Felix, Savory, David J, Andrade-Pacheco, Ricardo, Gething, Peter W, Bennett, Adam, Sturrock, Hugh J W
Format: Article
Language:English
Subjects:
Africa
Analysis
Archives & records
Biology and Life Sciences
Classification
Cloud Computing
Computer and Information Sciences
Computer applications
Computing time
Demographic aspects
Earth Sciences
Earth surface
Earth, Planet
Ecology and Environmental Sciences
Geographic Information Systems
High resolution
Land cover
Land use
Landsat
Landsat satellites
Malaria
Mapping
Models, Theoretical
Physical Sciences
Remote sensing
Research and Analysis Methods
Satellite data
Satellite observation
Satellites
Social Sciences
Spacecraft
Spatial analysis
Spatial discrimination
Spatial resolution
Time series
Trends
United Kingdom
United States
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Summary:Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0184926