Quantifying small‐scale deforestation and forest degradation in African woodlands using radar imagery

Abstract

Carbon emissions from tropical land‐use change are a major uncertainty in the global carbon cycle. In African woodlands, small‐scale farming and the need for fuel are thought to be reducing vegetation carbon stocks, but quantification of these processes is hindered by the limitations of optical remote sensing and a lack of ground data. Here, we present a method for mapping vegetation carbon stocks and their changes over a 3‐year period in a > 1000 km2 region in central Mozambique at 0.06 ha resolution. L‐band synthetic aperture radar imagery and an inventory of 96 plots are combined using regression and bootstrapping to generate biomass maps with known uncertainties. The resultant maps have sufficient accuracy to be capable of detecting changes in forest carbon stocks of as little as 12 MgC ha−1 over 3 years with 95% confidence. This allows characterization of biomass loss from deforestation and forest degradation at a new level of detail. Total aboveground biomass in the study area was reduced by 6.9 ± 4.6% over 3 years: from 2.13 ± 0.12 TgC in 2007 to 1.98 ± 0.11 TgC in 2010, a loss of 0.15 ± 0.10 TgC. Degradation probably contributed 67% (96.9 ± 91.0 GgC) of the net loss of biomass, but is associated with high uncertainty. The detailed mapping of carbon stock changes quantifies the nature of small‐scale farming. New clearances were on average small (median 0.2 ha) and were often additions to already cleared land. Deforestation events reduced biomass from 33.5 to 11.9 MgC ha−1 on average. Contrary to expectations, we did not find evidence that clearances were targeted towards areas of high biomass. Our method is scalable and suitable for monitoring land cover change and vegetation carbon stocks in woodland ecosystems, and can support policy approaches towards reducing emissions from deforestation and degradation (REDD).

Local-Scale Mapping of Biomass in Tropical Lowland Pine Savannas Using ALOS PALSAR

“…In contrast, upscaling our finer scale AGWB estimations in both the RBCMA and DR did not produce large overestimation compared to the same local reference values (+8.1% and +4.5%, respectively, for MBE500 and 10.7% and 0.04% for the MBE1000). Similar findings are observed in [63], where Hill et al find considerable differences in mean AGWB by comparing between the biomass maps produced by [23] and [17] for a small study area in Mozambique (~1160 km 2 ), which is dominated by Miombo woodlands (mean AGWB ~35.6-38.4 tha −1 found in [23] vs. 102.4 tha −1 found in [17]). These findings confirm the need for caution when using biomass estimations produced from satellite EO [63] at coarse resolution for quantifying AGWB locally.…”

“…In Africa, [21] created an ALOS PALSAR mosaic at 100-m spatial resolution to be used, among other applications, to map deforestation and agricultural encroachment upon the forest-savanna boundary. In their study within savanna landscapes, [22] identified strong relationships between AGWB and radar backscatter sensed by ALOS PALSAR, concluding that the approach was necessary and sufficient for monitoring and reporting of biomass baselines for REDD+ projects, and [23] similarly found ALOS PALSAR images to assist in quantifying deforestation at small scales in savanna woodlands in Mozambique. In Australia, [24] stressed the value of ALOS PALSAR data for quantifying the contribution of the woody component of tropical savannas to regional carbon stocks.…”

Assessment of Aboveground Woody Biomass Dynamics Using Terrestrial Laser Scanner and L-Band ALOS PALSAR Data in South African Savanna

“…These should therefore be investigated over the study period to assess their magnitude of contribution to the biomass dynamics depicted by the change results. A study by [32] suggested correction of effects of moisture to L-band SAR backscatter recalibration of backscatter to ground data at each time point.…”

“…Relevant studies by [39] utilized multi-temporal and dual-pol SAR in assessing structural components of the vegetation within KNP. The capability of L-band SAR backscatter intensity in quantifying small-scale forest degradation in the Miombo woodlands of Mozambique over a three-year period was demonstrated in [32].…”

“…Longer wavelengths are more relevant in the detection of vegetation geometry due to their penetrative effects, resulting in volume scattering [30,31]. The wavelength interaction with canopy elements results in diffuse scattering, hence more energy returning to the sensor [32]. SAR systems with longer wavelengths like L-band sensors penetrate into the canopy [29,33].…”