Mapping the structure of Borneo's tropical forests across a degradation gradient
File(s)
Author(s)
Type
Journal Article
Abstract
South East Asia has the highest rate of lowland forest loss of any tropical region, with logging and deforestation for conversion to plantation agriculture being flagged as the most urgent threats. Detecting and mapping logging impacts on forest structure is a primary conservation concern, as these impacts feed through to changes in biodiversity and ecosystem functions. Here, we test whether high-spatial resolution satellite remote sensing can be used to map the responses of aboveground live tree biomass (AGB), canopy leaf area index (LAI) and fractional vegetation cover (FCover) to selective logging and deforestation in Malaysian Borneo. We measured these attributes in permanent vegetation plots in rainforest and oil palm plantations across the degradation landscape of the Stability of Altered Forest Ecosystems project. We found significant mathematical relationships between field-measured structure and satellite-derived spectral and texture information, explaining up to 62% of variation in biophysical structure across forest and oil palm plots. These relationships held at different aggregation levels from plots to forest disturbance types and oil palms allowing us to map aboveground biomass and canopy structure across the degradation landscape. The maps reveal considerable spatial variation in the impacts of previous logging, a pattern that was less clear when considering field data alone. Up-scaled maps revealed a pronounced decline in aboveground live tree biomass with increasing disturbance, impacts which are also clearly visible in the field data even a decade after logging. Field data demonstrate a rapid recovery in forest canopy structure with the canopy recovering to pre-disturbance levels a decade after logging. Yet, up-scaled maps show that both LAI and FCover are still reduced in logged compared to primary forest stands and markedly lower in oil palm stands. While uncertainties remain, these maps can now be utilised to identify conservation win–wins, especially when combining them with ongoing biodiversity surveys and measurements of carbon sequestration, hydrological cycles and microclimate.
Date Issued
2016-01-28
Date Acceptance
2016-01-20
Citation
Remote Sensing of Environment, 2016, 176, pp.84-97
ISSN
0034-4257
Publisher
Elsevier
Start Page
84
End Page
97
Journal / Book Title
Remote Sensing of Environment
Volume
176
Copyright Statement
© 2016 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor
Commission of the European Communities
Rainforest Research Sdn Bhd
Grant Number
281986
LBEE_P34395
Subjects
Science & Technology
Life Sciences & Biomedicine
Technology
Environmental Sciences
Remote Sensing
Imaging Science & Photographic Technology
Environmental Sciences & Ecology
Borneo
Humid tropical forests
Degradation
RapidEye (TM)
Co-occurrence measures
Spectral reflectance
Biophysical structure
Maps
Field data
LEAF-AREA INDEX
ABOVEGROUND BIOMASS ESTIMATION
RESOLUTION GLOBAL-MAPS
BRAZILIAN AMAZON
RAIN-FORESTS
COVER CHANGE
ALLOMETRIC MODELS
VEGETATION INDEX
SOUTHEAST-ASIA
CARBON STORAGE
Geological & Geomatics Engineering
0406 Physical Geography And Environmental Geoscience
0909 Geomatic Engineering
Publication Status
Published