Machine learning and geostatistical approaches for estimating aboveground biomass in Chinese subtropical forests

Background Aboveground biomass (AGB) is a fundamental indicator of forest ecosystem productivity and health and hence plays an essential role in evaluating forest carbon reserves and supporting the development of targeted forest management plans. Methods Here, we proposed a random forest/co-kriging...

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Veröffentlicht in:	Forest ecosystems 2020-11, Vol.7 (1), Article 64
Hauptverfasser:	Su, Huiyi, Shen, Wenjuan, Wang, Jingrui, Ali, Arshad, Li, Mingshi
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Backscattering Biomass Biomedical and Life Sciences Carbon sequestration Climate change Ecology Ecosystems Elevation Environmental changes Errors Forest biomass Forest ecosystems Forest management Forestry Geostatistics Landsat Landsat satellites Learning algorithms Life Sciences Machine learning Mapping Nature reserves Nuclear factor I Phased arrays Radar Radar arrays Remote sensing Satellite observation Sustainable forestry Synthetic aperture radar Terrestrial ecosystems Tropical forests
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