Journal of Remote Sensing (Jan 2023)

Earth Map: A Novel Tool for Fast Performance of Advanced Land Monitoring and Climate Assessment

  • Carmen Morales,
  • Alfonso Sanchez-Paus Díaz,
  • Daniel Dionisio,
  • Laura Guarnieri,
  • Giulio Marchi,
  • Danae Maniatis,
  • Danilo Mollicone

DOI
https://doi.org/10.34133/remotesensing.0003
Journal volume & issue
Vol. 3

Abstract

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Earth Map (https://earthmap.org/) is an innovative and free application developed by the Food and Agriculture Organization of the United Nations that was designed in the framework of the Food and Agriculture Organization of the United Nations–Google partnership and facilitates the visualization, processing, and analysis of land and climate data. Earth Map makes petabytes of multitemporal, multiscale, multiparametric, and quasi-real-time satellite imagery and geospatial datasets available to any user thanks to the power of Google Earth Engine (https://earthengine.google.com/) and a point-and-click graphical user interface. These are further complemented with more planetary-scale analytical capabilities so that global and local changes and trends on Earth’s surface can be easily detected, quantified, and visualized. It does not require users to master coding techniques, thereby avoiding bottlenecks in terms of technical capacities of nonexpert users. It ultimately paves the way for countries, research institutes, farmers, and members of the general public to access critical knowledge to develop science-based policy interventions, leverage investments, and sustain livelihoods. We provide a full overview of Earth Map’s software architecture, design, features, and datasets. To illustrate the possible applications of the tool, different examples are presented including a few case studies that show how quick historical analysis of environmental and climate parameters can be performed and research questions answered. The examples demonstrate that Earth Map is a comprehensive and user-friendly tool for land monitoring and climate assessment and that it has the potential to be used to assess land use, land use change, climate change impacts, and natural disasters.