Mapping deep peat carbon stock from a LiDAR based DTM and field measurements, with application to eastern Sumatra

Abstract

Background: Reduction of carbon emissions from peatlands is recognized as an important factor in global climate change mitigation. Within the SE Asia region, areas of deeper peat present the greatest carbon stocks, and therefore the greatest potential for future carbon emissions from degradation and fire. They also support most of the remaining lowland swamp forest and its associated biodiversity. Accurate maps of deep peat are central to providing correct estimates of peat carbon stocks and to facilitating appropriate management interventions. We present a rapid and cost-effective approach to peat thickness mapping in raised peat bogs that applies a model of peat bottom elevation based on field measurements subtracted from a surface elevation model created from airborne LiDAR data. Results: In two raised peat bog test areas in Indonesia, we find that field peat thickness measurements correlate well with surface elevation derived from airborne LiDAR based DTMs (R 2 0.83-0.88), confirming that the peat bottom is often relatively flat. On this basis, we created a map of extent and depth of deep peat (> 3 m) from a new DTM that covers two-thirds of Sumatran peatlands, applying a flat peat bottom of 0.61 m +MSL determined from the average of 2446 field measurements. A deep peat area coverage of 2.6 Mha or 60.1% of the total peat area in eastern Sumatra is mapped, suggesting that deep peat in this region is more common than shallow peat and its extent was underestimated in earlier maps. The associated deep peat carbon stock range is 9.0-11.5 Pg C in eastern Sumatra alone. Conclusion: We discuss how the deep peat map may be used to identify priority areas for peat and forest conservation and thereby help prevent major potential future carbon emissions and support the safeguarding of the remaining forest and biodiversity. We propose rapid application of this method to other coastal raised bog peatland areas in SE Asia in support of improved peatland zoning and management. We demonstrate that the upcoming global ICESat-2 and GEDI satellite LiDAR coverage will likely result in a global DTM that, within a few years, will be sufficiently accurate for this application.

Degradation of Southeast Asian tropical peatlands and integrated strategies for their better management and restoration

“…Protection of the remaining peatswamp forests across the SE Asian region has to be given the highest possible priority in any conservation activity, given their essential role in protecting large C stocks and hosting forest biodiversity while also mitigating GHG emissions and fire risk (Evers et al, 2017;Page et al, 2009;Vernimmen et al, 2020).…”

Drainage Canals in Southeast Asian Peatlands Increase Carbon Emissions

“…Accordingly, tracking of canal water levels is needed to better understand the impact of drainage density and canal layout on water table depths away from canals. Lidar measurements, previously used in tropical peatlands for mapping carbon stocks (Vernimmen et al., 2020a) and for estimating carbon losses from burn scars (Ballhorn et al., 2009; Simpson et al., 2016) are especially promising for measuring canal water levels (Rahman et al., 2017; Vernimmen et al., 2020b). However, spaceborne lidar does not have sufficient density of sampling needed to cover all canals in the region, and airborne lidar measurements have only been made over a small fraction of the region.…”

A review of carbon monitoring in wet carbon systems using remote sensing

“…In Southeast Asia, degradation, loss, and recovery were major research topics enabled by lidar, SAR, and multispectral imagery. Studies have used lidar to detect illegal logging and carbon sequestration [305], map peat depth [306], and estimate AGB for tropical peatlands [307]. Minasny et al detail an open data and mapping methodology with the ability to predict peat depth at a lower cost than lidar [308].…”