Tropical forest carbon assessment: integrating satellite and airborne mapping approaches

By Gregory P. Asner. 2009

284 citations recorded by the source corpus.

Large-scale carbon mapping is needed to support the UNFCCC program to reduce deforestation and forest degradation (REDD). Managers of forested land can potentially increase their carbon credits via detailed monitoring of forest cover, loss and gain (hectares), and periodic estimates of changes in forest carbon density (tons ha−1). Satellites provide an opportunity to monitor changes in forest carbon caused by deforestation and degradation, but only after initial carbon densities have been assessed. New airborne approaches, especially light detection and ranging (LiDAR), provide a means to estimate forest carbon density over large areas, which greatly assists in the development of practical baselines. Here I present an integrated satellite–airborne mapping approach that supports high-resolution carbon stock assessment and monitoring in tropical forest regions. The approach yields a spatially resolved, regional state-of-the-forest carbon baseline, followed by high-resolution monitoring of forest cover and disturbance to estimate carbon emissions. Rapid advances and decreasing costs in the satellite and airborne mapping sectors are already making high-resolution carbon stock and emissions assessments viable anywhere in the world.

Subfields: Ecology, Environmental Engineering, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/40857a7766c888123ec22d8bdf9fbd33a35e98b2

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Citations in the corpus

Monitoring, reporting and verification for national REDD + programmes: two proposals (2011, result): “For example, radar technology, and airborne Lidar may have the potential to generate good data on stock change in the future (Asner 2009), but the costs, particularly of interpretation, are still large, but results from new large area experiments suggest more efficient approaches in the future…”
The potential ecological costs and cobenefits of REDD: a critical review and case study from the Amazon region (2009, methodology): “…be used in REDD are still under discussion (Herold & Johns, 2007; GOFC-GOLD, 2009), and are benefiting from technological breakthroughs, including high-resolution, cloud- and smoke-free imaging of forests using new radar and laser sensors (Kellndorfer et al., 2007; Asner, 2009; Goetz et al., 2009).”
High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision (2013, methodology): “When applied over large spatial extents (e.g., >hundreds of square kilometers) LIDAR can be used to map aboveground biomass at a cost of $0.05 – $0.20 per hectare (Asner, 2009).”
High-resolution forest carbon stocks and emissions in the Amazon (2010, background): “Extensive field validation, including both new and previously published estimates from field plots in the region (10, 11), indicated a LiDAR-to-carbonmeasurement correlation of 92% (Figs.”
Multi-element regulation of the tropical forest carbon cycle (2011, background): “Promising research tools – which can help to overcome the inherent complexity of the tropics, including new approaches in airborne remote sensing (Asner 2009) and in regional inversions of atmospheric data (Stephens et al. 2007) – have also been developed in recent years.”
Dormancy and dispersal as mediators of zooplankton population and community dynamics along a hydrological disturbance gradient in inland temporary pools (2017, background): “In a broader sense, predictability also refers to the variance in the timing of the wet phase.”
Carbon Content of Tree Tissues: A Synthesis (2012, background): “Incorporation of species-specific wood C data may be also particularly challenging, given that recent progress in estimating forest AGB relies heavily on remotely sensed data [73,74].”
Generalizing predictive models of forest inventory attributes using an area-based approach with airborne LiDAR data (2015, background): “…temperate forests (Hall, Burke, Box, Kaufmann, & Stoker, 2005; Zhao& Popescu, 2009), boreal forests (Lim, Treitz, Baldwin, Morrison, & Green, 2003; Næsset & Gobakken, 2008), tropical forests (Asner, 2009; Kronseder, Ballhorn, Böhm, & Siegert, 2012), and savannah woodlands (Lucas et al., 2006).”