0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      An Urban Water Extraction Method Combining Deep Learning and Google Earth Engine

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Related collections

          Most cited references55

          • Record: found
          • Abstract: not found
          • Article: not found

          A Threshold Selection Method from Gray-Level Histograms

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Google Earth Engine: Planetary-scale geospatial analysis for everyone

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              High-resolution global maps of 21st-century forest cover change.

              Quantification of global forest change has been lacking despite the recognized importance of forest ecosystem services. In this study, Earth observation satellite data were used to map global forest loss (2.3 million square kilometers) and gain (0.8 million square kilometers) from 2000 to 2012 at a spatial resolution of 30 meters. The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year. Brazil's well-documented reduction in deforestation was offset by increasing forest loss in Indonesia, Malaysia, Paraguay, Bolivia, Zambia, Angola, and elsewhere. Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally. Boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms. These results depict a globally consistent and locally relevant record of forest change.
                Bookmark

                Author and article information

                Contributors
                Journal
                IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
                IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing
                Institute of Electrical and Electronics Engineers (IEEE)
                1939-1404
                2151-1535
                2020
                2020
                : 13
                : 769-782
                Article
                10.1109/JSTARS.2020.2971783
                e2b9b72e-dab1-498e-864f-1d299e72afac
                © 2020

                https://creativecommons.org/licenses/by/4.0/legalcode

                History

                Comments

                Comment on this article