Distinguishing vegetation types with airborne waveform lidar data in a tropical forest-savanna mosaic: A case study in Lopé National Park, Gabon

Marselis, S.; Tang, Hao; Armston, John; Calders, Kim; Labrière, Nicolas; Dubayah, Ralph

doi:10.1016/j.rse.2018.07.023

Cited by 43 publications

(38 citation statements)

References 38 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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“…Large-footprint waveform lidar data similar to GEDI (~25 m in diameter) have proven useful for observing distinct canopy structures related to disturbances. For example, large-footprint data have been used to infer past hurricane damage [25], to identify developmental stages of forest plots [26][27][28], to observe phenological cycles [23], and to estimate biomass change [29,30].…”

Section: Lidar Remote Sensing For Monitoring Forest Healthmentioning

confidence: 99%

Detecting Change in Forest Structure with Simulated GEDI Lidar Waveforms: A Case Study of the Hemlock Woolly Adelgid (HWA; Adelges tsugae) Infestation

et al. 2020

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The hemlock woolly adelgid (HWA; Adelges tsugae) is an invasive insect infestation that is spreading into the forests of the northeastern United States, driven by the warmer winter temperatures associated with climate change. The initial stages of this disturbance are difficult to detect with passive optical remote sensing, since the insect often causes its host species, eastern hemlock trees (Tsuga canadensis), to defoliate in the midstory and understory before showing impacts in the overstory. New active remote sensing technologies-such as the recently launched NASA Global Ecosystem Dynamics Investigation (GEDI) spaceborne lidar-can address this limitation by penetrating canopy gaps and recording lower canopy structural changes. This study explores new opportunities for monitoring the HWA infestation with airborne lidar scanning (ALS) and GEDI spaceborne lidar data. GEDI waveforms were simulated using airborne lidar datasets from an HWA-infested forest plot at the Harvard Forest ForestGEO site in central Massachusetts. Two airborne lidar instruments, the NASA G-LiHT and the NEON AOP, overflew the site in 2012 and 2016. GEDI waveforms were simulated from each airborne lidar dataset, and the change in waveform metrics from 2012 to 2016 was compared to field-derived hemlock mortality at the ForestGEO site. Hemlock plots were shown to be undergoing dynamic changes as a result of the HWA infestation, losing substantial plant area in the middle canopy, while still growing in the upper canopy. Changes in midstory plant area (PAI 11-12 m above ground) and overall canopy permeability (indicated by RH10) accounted for 60% of the variation in hemlock mortality in a logistic regression model. The robustness of these structure-condition relationships held even when simulated waveforms were treated as real GEDI data with added noise and sparse spatial coverage. These results show promise for future disturbance monitoring studies with ALS and GEDI lidar data.

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“…The sensor concept was recently once again selected as the Global Ecosystems Dynamics Investigation Lidar (GEDI) via NASA's Earth Ventures Instrument 2 (EVI-2) competition and installed on the International Space Station in December 2018. Research conducted from the mid-1990s through to the present continue to document the critical importance of three-dimensional structure of the Earth's forests for environmental and policy decisions [24]. Had there been EAs projects for VCL, they would need to be patient and engaged for over two decades with NASA on multiple projects before GEDI actually provided them data to integrate into their application.…”

Section: Partnership Contextmentioning

confidence: 99%

NASA’s Early Adopter Program Links Satellite Data to Decision Making

Brown

Escobar

2019

Remote Sensing

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As the cost of satellite missions grow, government agencies are working to increase the relevance and usefulness of the Earth science data that they produce. The US National Aeronautics and Space Administration’s (NASA) early adopter program seeks to formalize partnerships with users of data early within the satellite planning process to ensure the greatest value of the mission. Scientists who are designing the satellite observing system, those who are developing mission data products, and the community who will use them need to work together to determine how satellite data can better inform decision making. NASA is working to initiate engagement with data users much earlier in the satellite program life so that the user needs can be prioritized, continue to engage with users throughout the development cycle, and then include analysis on societal impact after nominal mission life. The Early Adopter Program allows for broad and early engagement with decision makers by encouraging individuals and institutions with clear uses of data to engage with the mission. Early adopters facilitate feedback on mission products during pre-launch and accelerate the utilization of these products post-launch. This paper provides background and detail on how NASA is working to engage with early adopters, describes the partnership between early adopters and NASA missions, and connects the program to improved societal impacts of its satellite missions.

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Distinguishing vegetation types with airborne waveform lidar data in a tropical forest-savanna mosaic: A case study in Lopé National Park, Gabon

Cited by 43 publications

References 38 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

Detecting Change in Forest Structure with Simulated GEDI Lidar Waveforms: A Case Study of the Hemlock Woolly Adelgid (HWA; Adelges tsugae) Infestation

NASA’s Early Adopter Program Links Satellite Data to Decision Making

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