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- Title
Collect Earth: Land Use and Land Cover Assessment through Augmented Visual Interpretation.
- Authors
Bey, Adia; Sánchez-Paus Díaz, Alfonso; Marchi, Giulio; Mollicone, Danilo; Ricci, Stefano; Federici, Sandro; Rezende, Marcelo; Patriarca, Chiara; Hitofumi Abe; Bastin, Jean-François; Maniatis, Danae; Moore, Rebecca; Miceli, Gino; Turia, Ruth; Gamoga, Gewa; Kaidong, Elizabeth
- Abstract
Collect Earth is a free and open source software for land monitoring developed by the Food and Agriculture Organization of the United Nations (FAO). Built on Google desktop and cloud computing technologies, Collect Earth facilitates access to multiple freely available archives of satellite imagery, including archives with very high spatial resolution imagery (Google Earth, Bing Maps) and those with very high temporal resolution imagery (e.g., Google Earth Engine, Google Earth Engine Code Editor). Collectively, these archives offer free access to an unparalleled amount of information on current and past land dynamics for any location in the world. Collect Earth draws upon these archives and the synergies of imagery of multiple resolutions to enable an innovative method for land monitoring that we present here: augmented visual interpretation. In this study, we provide a full overview of Collect Earth’s structure and functionality, and we present the methodology used to undertake land monitoring through augmented visual interpretation. To illustrate the application of the tool and its customization potential, an example of land monitoring in Papua New Guinea (PNG) is presented. The PNG example demonstrates that Collect Earth is a comprehensive and user-friendly tool for land monitoring and that it has the potential to be used to assess land use, land use change, natural disasters, sustainable management of scarce resources and ecosystem functioning. By enabling non-remote sensing experts to assess more than 100 sites per day, we believe that Collect Earth can be used to rapidly and sustainably build capacity for land monitoring and to substantively improve our collective understanding of the world’s land use and land cover.
- Subjects
PAPUA New Guinea; LAND use; CLOUD computing; OPEN source software; REMOTE-sensing images; COMPUTER network resources
- Publication
Remote Sensing, 2016, Vol 8, Issue 10, p807
- ISSN
2072-4292
- Publication type
Article
- DOI
10.3390/rs8100807