21
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Monitoring tropical forest carbon stocks and emissions using Planet satellite data

      research-article

      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.

          Abstract

          Tropical forests are crucial for mitigating climate change, but many forests continue to be driven from carbon sinks to sources through human activities. To support more sustainable forest uses, we need to measure and monitor carbon stocks and emissions at high spatial and temporal resolution. We developed the first large-scale very high-resolution map of aboveground carbon stocks and emissions for the country of Peru by combining 6.7 million hectares of airborne LiDAR measurements of top-of-canopy height with thousands of Planet Dove satellite images into a random forest machine learning regression workflow, obtaining an R 2 of 0.70 and RMSE of 25.38 Mg C ha −1 for the nationwide estimation of aboveground carbon density (ACD). The diverse ecosystems of Peru harbor 6.928 Pg C, of which only 2.9 Pg C are found in protected areas or their buffers. We found significant carbon emissions between 2012 and 2017 in areas aggressively affected by oil palm and cacao plantations, agricultural and urban expansions or illegal gold mining. Creating such a cost-effective and spatially explicit indicators of aboveground carbon stocks and emissions for tropical countries will serve as a transformative tool to quantify the climate change mitigation services that forests provide.

          Related collections

          Most cited references48

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

          Random forest in remote sensing: A review of applications and future directions

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

            Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction

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

              Continental-scale patterns of canopy tree composition and function across Amazonia.

              The world's greatest terrestrial stores of biodiversity and carbon are found in the forests of northern South America, where large-scale biogeographic patterns and processes have recently begun to be described. Seven of the nine countries with territory in the Amazon basin and the Guiana shield have carried out large-scale forest inventories, but such massive data sets have been little exploited by tropical plant ecologists. Although forest inventories often lack the species-level identifications favoured by tropical plant ecologists, their consistency of measurement and vast spatial coverage make them ideally suited for numerical analyses at large scales, and a valuable resource to describe the still poorly understood spatial variation of biomass, diversity, community composition and forest functioning across the South American tropics. Here we show, by using the seven forest inventories complemented with trait and inventory data collected elsewhere, two dominant gradients in tree composition and function across the Amazon, one paralleling a major gradient in soil fertility and the other paralleling a gradient in dry season length. The data set also indicates that the dominance of Fabaceae in the Guiana shield is not necessarily the result of root adaptations to poor soils (nodulation or ectomycorrhizal associations) but perhaps also the result of their remarkably high seed mass there as a potential adaptation to low rates of disturbance.
                Bookmark

                Author and article information

                Contributors
                ocsillik@asu.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                28 November 2019
                28 November 2019
                2019
                : 9
                : 17831
                Affiliations
                [1 ]ISNI 0000 0001 2151 2636, GRID grid.215654.1, Center for Global Discovery and Conservation Science, Arizona State University, ; Tempe, AZ USA
                [2 ]Planet Labs Inc, San Francisco, CA USA
                Author information
                http://orcid.org/0000-0002-4590-3807
                Article
                54386
                10.1038/s41598-019-54386-6
                6882785
                31780757
                e85b11d1-c911-4c17-a35d-b5877da5923a
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 2 April 2019
                : 13 November 2019
                Funding
                Funded by: Erol Foundation
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                forest ecology,tropical ecology
                Uncategorized
                forest ecology, tropical ecology

                Comments

                Comment on this article