Quantifying the sensitivity of L-Band SAR to a decade of vegetation structure changes in savannas

Konrad Wessels, Xiaoxuan Li, Alexandre Bouvet, Renaud Mathieu, Russell Main, Laven Naidoo, Barend Erasmus, Gregory P. Asner

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Global savannas are the third largest carbon sink with large human populations being highly dependent on their ecosystem services. However, savannas are changing rapidly due to climate change, fire, animal management, and intense fuelwood harvesting. In southern Africa, large trees (>5 m in height) are under threat while shrub cover (<3 m) is increasing. The collection of multi-date airborne LiDAR (ALS) data, initiated over a decade ago in the Lowveld of South Africa, provided a rare opportunity to quantify the ability of L-band SAR to track changes in savanna vegetation structure and this study is the first to do so, to our knowledge. The objective was to test the ability of ALOS PALSAR 1&2, dual-pol (HH, HV) data to quantify woody cover and volume change in savannas over 2-, 8- and 10-year periods through comparison to ALS. For each epoch (2008, 2010, 2018), multiple PALSAR images were processed to Gamma0 (γ0) at 15 m resolution with multi-temporal speckle filtering. ALS data were processed to fractional canopy cover and volume, and then compared to 5 × 5 aggregated (75 m) SAR mean γ0. The ALS cover change (∆CALS) and volume change between pairs of years were highly correlated, with (R2 > 0.8), thus results for cover change applied equally to volume change. Cover change was predicted using (i) direct backscatter change or (ii) the difference between annual cover map product derived using the Bayesian Water Cloud Model (BWCM) and logarithmic models. The linear relationship between ∆γ0 and ∆CALS varied between year pairs but reached a maximum R2 of 0.7 for 2018–2010 and a moderate R2 of 0.4 for 2018–2008. Overall, 1 dB ∆γ0 corresponded to approximately 0.1 cover change. The three cover change models had very similar uncertainties with mean RMSE = 0.15, which is 13% of the observed cover change range (−0.6 to +0.6). The direct backscatter change approach had less underestimation of positive and negative cover change. The L-band backscatter had a higher sensitivity than suggested by previous studies, as it was able to reliably distinguish cover change at 0.25 increments. The SAR-derived cover change maps detected the loss of stands of big trees, and widespread increases in cover of 0.35–0.65 in communal rangelands due to shrub encroachment. In contrast, the maps suggest that cover generally decreased in conservation areas, forming distinct fence-line effects, potentially caused by significant increases in elephant numbers and frequent, intense wildfires in reserves.

Original languageEnglish (US)
Article number113369
JournalRemote Sensing of Environment
StatePublished - Jan 2023


  • L-Band
  • LiDAR
  • SAR
  • Savannas
  • South Africa
  • Vegetation structure

ASJC Scopus subject areas

  • Soil Science
  • Geology
  • Computers in Earth Sciences


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