Mapping and monitoring global forest canopy height through integration of GEDI and Landsat data

Potapov, P.; Li, Xinyuan; Hernández-Serna, Andrés; Tyukavina, Alexandra; Hansen, Matthew C.; Kommareddy, Anil; Pickens, Amy; Turubanova, Svetlana; Tang, Hao; Silva, Carlos Edibaldo; Armston, John; Dubayah, Ralph; Blair, J. B.; Hofton, M. A.

doi:10.5281/zenodo.4008406

Cited by 1 publication

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“…Spaceborne LiDAR altimetry observation from GLAS onboard ICESat-1 [32,105], Advanced Topographic Altimeter System (ATLAS) onboard ICESat-2 [117][118][119] and the GEDI onboard International Space Station (ISS) [108] are extensively being used for developing forest canopy and height parameters which are essential for AGB estimation models [23]. Recently, a forest canopy height map of 2019 at a 30 m spatial resolution is released by the UMD GLAD [120,121]. The global forest canopy height map is derived from combined analysis of LiDAR observation acquired by the GEDI and time series of the Landsat.…”

Section: Canopy Heightmentioning

confidence: 99%

Approaches of Satellite Remote Sensing for the Assessment of Above-Ground Biomass across Tropical Forests: Pan-tropical to National Scales

Abbas

Wong

et al. 2020

Remote Sensing

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Tropical forests are acknowledged for providing important ecosystem services and are renowned as “the lungs of the planet Earth” due to their role in the exchange of gasses—particularly inhaling CO2 and breathing out O2—within the atmosphere. Overall, the forests provide 50% of the total plant biomass of the Earth, which accounts for 450–650 PgC globally. Understanding and accurate estimates of tropical forest biomass stocks are imperative in ascertaining the contribution of the tropical forests in global carbon dynamics. This article provides a review of remote-sensing-based approaches for the assessment of above-ground biomass (AGB) across the tropical forests (global to national scales), summarizes the current estimate of pan-tropical AGB, and discusses major advancements in remote-sensing-based approaches for AGB mapping. The review is based on the journal papers, books and internet resources during the 1980s to 2020. Over the past 10 years, a myriad of research has been carried out to develop methods of estimating AGB by integrating different remote sensing datasets at varying spatial scales. Relationships of biomass with canopy height and other structural attributes have developed a new paradigm of pan-tropical or global AGB estimation from space-borne satellite remote sensing. Uncertainties in mapping tropical forest cover and/or forest cover change are related to spatial resolution; definition adapted for ‘forest’ classification; the frequency of available images; cloud covers; time steps used to map forest cover change and post-deforestation land cover land use (LCLU)-type mapping. The integration of products derived from recent Synthetic Aperture Radar (SAR) and Light Detection and Ranging (LiDAR) satellite missions with conventional optical satellite images has strong potential to overcome most of these uncertainties for recent or future biomass estimates. However, it will remain a challenging task to map reference biomass stock in the 1980s and 1990s and consequently to accurately quantify the loss or gain in forest cover over the periods. Aside from these limitations, the estimation of biomass and carbon balance can be enhanced by taking account of post-deforestation forest recovery and LCLU type; land-use history; diversity of forest being recovered; variations in physical attributes of plants (e.g., tree height; diameter; and canopy spread); environmental constraints; abundance and mortalities of trees; and the age of secondary forests. New methods should consider peak carbon sink time while developing carbon sequestration models for intact or old-growth tropical forests as well as the carbon sequestration capacity of recovering forest with varying levels of floristic diversity.

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