<i>In Situ</i> Reference Datasets From the TropiSAR and AfriSAR Campaigns in Support of Upcoming Spaceborne Biomass Missions

Labrière, Nicolas; Tao, Shengli; Chave, Jérôme; Scipal, Klaus; Toan, Thuy Le; Abernethy, Katharine; Alonso, Alfonso; Barbier, Nicolas; Bissiengou, Pulchérie; Casal, Tânia; Davies, Stuart J.; Ferraz, António; Hérault, Bruno; Jaouen, Gaëlle; Jeffery, Kathryn J.; Kenfack, David; Körte, Lisa; Lewis, Simon L.; Malhi, Yadvinder; Memiaghe, Herve R.; Poulsen, John R.; Réjou‐Méchain, Maxime; Villard, Ludovic; Vincent, Grégoire; White, Lee; Saatchi, Sassan

doi:10.1109/jstars.2018.2851606

Cited by 55 publications

(47 citation statements)

References 51 publications

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“…Large scale airborne LiDAR surveys are becoming available in tropical forest regions. For example, recent regional to national level LiDAR campaigns have been carried out in Democratic Republic of Congo [71] and Gabon [72,73]. Potentially, these data can be used with training data and a classification approach similar to ours to develop degradation status maps based on vegetation structure.…”

Section: Discussionmentioning

confidence: 99%

Long-Term Impacts of Selective Logging on Amazon Forest Dynamics from Multi-Temporal Airborne LiDAR

Pinagé

Keller

Duffy³

et al. 2019

Remote Sensing

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Forest degradation is common in tropical landscapes, but estimates of the extent and duration of degradation impacts are highly uncertain. In particular, selective logging is a form of forest degradation that alters canopy structure and function, with persistent ecological impacts following forest harvest. In this study, we employed airborne laser scanning in 2012 and 2014 to estimate three-dimensional changes in the forest canopy and understory structure and aboveground biomass following reduced-impact selective logging in a site in Eastern Amazon. Also, we developed a binary classification model to distinguish intact versus logged forests. We found that canopy gap frequency was significantly higher in logged versus intact forests even after 8 years (the time span of our study). In contrast, the understory of logged areas could not be distinguished from the understory of intact forests after 6–7 years of logging activities. Measuring new gap formation between LiDAR acquisitions in 2012 and 2014, we showed rates 2 to 7 times higher in logged areas compared to intact forests. New gaps were spatially clumped with 76 to 89% of new gaps within 5 m of prior logging damage. The biomass dynamics in areas logged between the two LiDAR acquisitions was clearly detected with an average estimated loss of −4.14 ± 0.76 MgC ha−1 y−1. In areas recovering from logging prior to the first acquisition, we estimated biomass gains close to zero. Together, our findings unravel the magnitude and duration of delayed impacts of selective logging in forest structural attributes, confirm the high potential of airborne LiDAR multitemporal data to characterize forest degradation in the tropics, and present a novel approach to forest classification using LiDAR data.

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Section: Discussionmentioning

confidence: 99%

Long-Term Impacts of Selective Logging on Amazon Forest Dynamics from Multi-Temporal Airborne LiDAR

Pinagé

Keller

Duffy³

et al. 2019

Remote Sensing

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“…In addition, long-term continuous P-band tower-based measurements were made in French Guiana (Tropiscat), Ghana (Afriscat) and Sweden (Borealscat) to investigate diurnal and seasonal variations in backscatter and temporal coherence. Earlier P-band datasets from the NASA AirSAR system were also helpful, especially tropical forest data from Costa Rica, to extend the range of tropical biomass values , and NASA was heavily involved in the AfriSAR campaign, providing lidar coverage of the AfriSAR test-sites (Labrière et al, 2018). No specific ESA campaigns were conducted in temperate forests, but substantial amounts of tomographic data are available for such forests from experimental campaigns carried out by DLR.…”

Section: Forest Agb and Height Estimation Techniquesmentioning

confidence: 99%

The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space

Quegan

Toan

Chave

et al. 2019

Remote Sensing of Environment

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The primary objective of the European Space Agency's 7 th Earth Explorer mission, BIOMASS, is to determine the worldwide distribution of forest above-ground biomass (AGB) in order to reduce the major uncertainties in calculations of carbon stocks and fluxes associated with the terrestrial biosphere, including carbon fluxes associated with Land Use Change, forest degradation and forest regrowth. To meet this objective it will carry, for the first time in space, a fully polarimetric P-band synthetic aperture radar (SAR). Three main products will be provided: global maps of both AGB and forest height, with a spatial resolution of 200 m, and maps of severe forest disturbance at 50 m resolution (where "global" is to be understood as subject to Space Object tracking radar restrictions). After launch in 2022, there will be a 3-month commissioning phase, followed by a 14-month phase during which there will be global coverage by SAR tomography. In the succeeding interferometric phase, global polarimetric interferometry Pol-InSAR coverage will be achieved every 7 months up to the end of the 5-year mission. Both Pol-InSAR and TomoSAR will be used to eliminate scattering from the ground (both direct and double bounce backscatter) in forests. In dense tropical forests AGB can then be estimated from the remaining volume scattering using non-linear inversion of a backscattering model. Airborne campaigns in the tropics also indicate that AGB is highly correlated with the backscatter from around 30 m above the ground, as measured by tomography. In contrast, double bounce scattering appears to carry important information about the AGB of boreal forests, so ground cancellation may not be appropriate and the best approach for such forests remains to be finalized. Several methods to exploit these new data in carbon cycle calculations have already been demonstrated. In addition, major mutual gains will be made by combining BIOMASS data with data from other missions that will measure forest biomass, structure, height and change, including the NASA Global Ecosystem Dynamics Investigation lidar deployed on the International Space Station after its launch in December 2018, and the NASA-ISRO NISAR Land S-band SAR, due for launch in 2022. More generally, space-based measurements of biomass are a core component of a carbon cycle observation and modelling strategy developed by the Group on Earth Observations. Secondary objectives of the mission include imaging of sub-surface geological structures in arid environments, generation of a true Digital Terrain Model without biases caused by forest cover, and measurement of glacier and icesheet velocities. In addition, the operations Here Eff denotes fossil fuel emissions; Elb is net land biospheric emissions, comprising both Land Use 94 Change and ecosystem dynamics, and including alterations to biomass stocks linked to process 95 responses to climate change, nitrogen deposition and rising atmospheric CO2; ΔCatmos is the change in 96 atmospheric CO2; and Uland and Uocean are net average uptake by t...

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“…Although long-term forest plots are essential for understanding the dynamics of tropical forests (Losos and Leigh, 2004), they are scarce, inherently labor-intensive, expensive and time-consuming to maintain, and not evenly distributed in the tropics. In addition, most studies of carbon dynamics along tropical forest successions are concentrated in Latin America (Chave et al, 2020;Letcher and Chazdon, 2009;Norden et al, 2015;Poorter et al, 2016a;Rozendaal et al, 2017;Rozendaal andChazdon, 2015, but see N'Guessan et al, 2019, for Africa). They show high among-site variation in forest carbon recovery rates, suggesting a high context dependence (Chazdon et al, 2007;Norden et al, 2011Norden et al, , 2015, partly depending on climate conditions (Poorter et al, 2016a).…”

Section: Introductionmentioning

confidence: 99%

Forest aboveground biomass stock and resilience in a tropical landscape of Thailand

et al. 2020

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Half of Asian tropical forests were disturbed in the last century resulting in the dominance of secondary forests in Southeast Asia. However, the rate at which biomass accumulates during the recovery process in these forests is poorly understood. We studied a forest landscape located in Khao Yai National Park (Thailand) that experienced strong disturbances in the last century due to clearance by swidden farmers. Combining recent field and airborne laser scanning (ALS) data, we first built a high-resolution aboveground biomass (AGB) map of over 60 km 2 of forest landscape. We then used the random forest algorithm and Landsat time series (LTS) data to classify landscape patches as non-forested versus forested on an almost annual basis from 1972 to 2017. The resulting chronosequence was then used in combination with the AGB map to estimate forest carbon recovery rates in secondary forest patches during the first 42 years of succession. The ALS-AGB model predicted AGB with an error of 14 % at 0.5 ha resolution (RMSE = 45 Mg ha −1 ) using the mean top-of-canopy height as a single predictor. The mean AGB over the landscape was 291 Mg ha −1 , showing a high level of carbon storage despite past disturbance history. We found that AGB recovery varies non-linearly in the first 42 years of the succession, with an increasing rate of accumulation through time. We predicted a mean AGB recovery rate of 6.9 Mg ha −1 yr −1 , with a mean AGB gain of 143 and 273 Mg ha −1 after 20 and 40 years, respectively. This rate estimate is about 50 % larger than the rate prescribed for young secondary Asian tropical rainforests in the 2019 refinement of the 2006 IPCC guidelines for national greenhouse gas inventories. Our study hence suggests that the new IPCC rates, which were based on limited data from Asian tropical rainforests, strongly underestimate the carbon potential of forest regrowth in tropical Asia. Our recovery estimates are also within the range of those reported for the well-studied Latin American secondary forests under similar climatic conditions. This study illustrates the potential of ALS data not only for scaling up field AGB measurements but also for predicting AGB recovery dynamics when combined with long-term satellite data. It also illustrates that tropical forest landscapes that were disturbed in the past are of utmost importance for the regional carbon budget and thus for implementing international programs such as REDD+.Published by Copernicus Publications on behalf of the European Geosciences Union.

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In Situ Reference Datasets From the TropiSAR and AfriSAR Campaigns in Support of Upcoming Spaceborne Biomass Missions

Cited by 55 publications

References 51 publications

Long-Term Impacts of Selective Logging on Amazon Forest Dynamics from Multi-Temporal Airborne LiDAR

Long-Term Impacts of Selective Logging on Amazon Forest Dynamics from Multi-Temporal Airborne LiDAR

The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space

Forest aboveground biomass stock and resilience in a tropical landscape of Thailand

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