Estimation of coarse dead wood stocks in intact and degraded forests in the Brazilian Amazon using airborne lidar

Scaranello, MAS; Keller, M; Longo, M; Dos-Santos, MN; Leitold, V; Morton, DC; Pinagé, ER; Del Bon Espírito-Santo, F

Estimation of coarse dead wood stocks in intact and degraded forests in the Brazilian Amazon using airborne lidar

Scaranello, MAS Keller, M

Longo, M

Dos-Santos, MN Leitold, V Morton, DC Pinagé, ER

Del Bon Espírito-Santo, F

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Publication Type:: Journal Article
Citation:: Biogeosciences, 2019, 16 (17), pp. 3457 - 3474
Issue Date:: 2019-09-13

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Field	Value	Language
dc.contributor.author	Scaranello, MAS	en_US
dc.contributor.author	Keller, M https://orcid.org/0000-0002-0253-3359	en_US
dc.contributor.author	Longo, M https://orcid.org/0000-0001-5062-6245	en_US
dc.contributor.author	Dos-Santos, MN	en_US
dc.contributor.author	Leitold, V	en_US
dc.contributor.author	Morton, DC	en_US
dc.contributor.author	Pinagé, ER https://orcid.org/0000-0003-3714-8175	en_US
dc.contributor.author	Del Bon Espírito-Santo, F	en_US
dc.date.issued	2019-09-13	en_US
dc.identifier.citation	Biogeosciences, 2019, 16 (17), pp. 3457 - 3474	en_US
dc.identifier.issn	1726-4170	en_US
dc.identifier.uri	http://hdl.handle.net/10453/136039
dc.description.abstract	© Author(s) 2019. Coarse dead wood is an important component of forest carbon stocks, but it is rarely measured in Amazon forests and is typically excluded from regional forest carbon budgets. Our study is based on line intercept sampling for fallen coarse dead wood conducted along 103 transects with a total length of 48 km matched with forest inventory plots where standing coarse dead wood was measured in the footprints of larger areas of airborne lidar acquisitions. We developed models to relate lidar metrics and Landsat time series variables to coarse dead wood stocks for intact, logged, burned, or logged and burned forests. Canopy characteristics such as gap area produced significant individual relations for logged forests. For total fallen plus standing coarse dead wood (hereafter defined as total coarse dead wood), the relative root mean square error for models with only lidar metrics ranged from 33% in logged forest to up to 36% in burned forests. The addition of historical information improved model performance slightly for intact forests (31% against 35% relative root mean square error), not justifying the use of a number of disturbance events from historical satellite images (Landsat) with airborne lidar data. Lidarderived estimates of total coarse dead wood compared favorably with independent ground-based sampling for areas up to several hundred hectares. The relations found between total coarse dead wood and variables quantifying forest structure derived from airborne lidar highlight the opportunity to quantify this important but rarely measured component of forest carbon over large areas in tropical forests.	en_US
dc.relation.ispartof	Biogeosciences	en_US
dc.relation.isbasedon	10.5194/bg-16-3457-2019	en_US
dc.subject.classification	Meteorology & Atmospheric Sciences	en_US
dc.title	Estimation of coarse dead wood stocks in intact and degraded forests in the Brazilian Amazon using airborne lidar	en_US
dc.type	Journal Article
utslib.citation.volume	17	en_US
utslib.citation.volume	16	en_US
utslib.for	0406 Physical Geography and Environmental Geoscience	en_US
utslib.for	0705 Forestry Sciences	en_US
utslib.for	04 Earth Sciences	en_US
utslib.for	05 Environmental Sciences	en_US
utslib.for	06 Biological Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access
pubs.issue	17	en_US
pubs.publication-status	Published	en_US
pubs.volume	16	en_US

Abstract:

© Author(s) 2019. Coarse dead wood is an important component of forest carbon stocks, but it is rarely measured in Amazon forests and is typically excluded from regional forest carbon budgets. Our study is based on line intercept sampling for fallen coarse dead wood conducted along 103 transects with a total length of 48 km matched with forest inventory plots where standing coarse dead wood was measured in the footprints of larger areas of airborne lidar acquisitions. We developed models to relate lidar metrics and Landsat time series variables to coarse dead wood stocks for intact, logged, burned, or logged and burned forests. Canopy characteristics such as gap area produced significant individual relations for logged forests. For total fallen plus standing coarse dead wood (hereafter defined as total coarse dead wood), the relative root mean square error for models with only lidar metrics ranged from 33% in logged forest to up to 36% in burned forests. The addition of historical information improved model performance slightly for intact forests (31% against 35% relative root mean square error), not justifying the use of a number of disturbance events from historical satellite images (Landsat) with airborne lidar data. Lidarderived estimates of total coarse dead wood compared favorably with independent ground-based sampling for areas up to several hundred hectares. The relations found between total coarse dead wood and variables quantifying forest structure derived from airborne lidar highlight the opportunity to quantify this important but rarely measured component of forest carbon over large areas in tropical forests.

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http://hdl.handle.net/10453/136039