NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Long-Term Impacts of Selective Logging on Amazon Forest Dynamics from Multi-Temporal Airborne LiDARForest 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/hay. 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.
Document ID
20190002287
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Pinage, Ekena Rangel
(University of Technology Sydney, Australia)
Keller, Michael
(Forest Service Rio Piedras, Puerto Rico)
Duffy, Paul
(Neptune & Company, Inc. Lakewood, CO, United States)
Longo, Marcos
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Dos-Santos, Maiza Nara
(Estadual de Campinas Univ. Sao Paulo, Brazil)
Morton, Douglas C.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
April 11, 2019
Publication Date
March 24, 2019
Publication Information
Publication: Remote Sensing
Publisher: MDPI
Volume: 11
Issue: 6
ISSN: 2072-4292
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN67337
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
No Preview Available