Google Earth Engine Applications Since Inception: Usage, Trends, and Potential
By Lalit Kumar, Onisimo Mutanga. Remote Sensing, 2018
609 citations recorded by the source corpus.
The Google Earth Engine (GEE) portal provides enhanced opportunities for undertaking earth observation studies. Established towards the end of 2010, it provides access to satellite and other ancillary data, cloud computing, and algorithms for processing large amounts of data with relative ease. However, the uptake and usage of the opportunity remains varied and unclear. This study was undertaken to investigate the usage patterns of the Google Earth Engine platform and whether researchers in developing countries were making use of the opportunity. Analysis of published literature showed that a total of 300 journal papers were published between 2011 and June 2017 that used GEE in their research, spread across 158 journals. The highest number of papers were in the journal Remote Sensing, followed by Remote Sensing of Environment. There were also a number of papers in premium journals such as Nature and Science. The application areas were quite varied, ranging from forest and vegetation studies to medical fields such as malaria. Landsat was the most widely used dataset; it is the biggest component of the GEE data portal, with data from the first to the current Landsat series available for use and download. Examination of data also showed that the usage was dominated by institutions based in developed nations, with study sites mainly in developed nations. There were very few studies originating from institutions based in less developed nations and those that targeted less developed nations, particularly in the African continent.
Subfields: Ecological Modeling, Epidemiology, Geography, Planning and Development
View Paper: https://www.semanticscholar.org/paper/7a93c6ef6660c76b932ae966243b8b8022e4edb1
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Citations in the corpus
- Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review (2020, methodology): “TherearecurrentlyfourGEEliterature reviewstudiesconductedbyGorelick et al. [6], Kumar and Mutanga [9], Mutanga and Kumar [10], and Tamiminia et al. [2], published between 2017 and 2020, respectively.”
- Google Earth Engine Applications (2019, background): “At a continental scale, cropland and non-cropland areas were mapped for the entire continent of Africa using a combination of 10-day Sentinel data and 16-day Landsat TM data.”