Elsevier, Remote Sensing of Environment, (176), p. 84-97
DOI: 10.1016/j.rse.2016.01.014
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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.