Near-real-time forest cover change detection using multi-spectral satellite imagery and time-series analysis for tropical concession management.
Explore Methodology →Anonymous Forest Concession in Cameroon
Multi-year deforestation monitoring across 18,500 hectares of tropical moist forest using Sentinel-2 and Landsat time series.
Tropical forests face rapid, often illegal, deforestation pressures that require precise, temporally dense monitoring to support compliance and certification frameworks.
Persistent cloud cover in the Congo Basin limits optical satellite acquisition, requiring sophisticated cloud-masking algorithms and dense time-series compositing.
Selective logging and smallholder agriculture create subtle spectral changes that evade detection by coarse-resolution global products.
Certification bodies (FSC, PEFC) and EU Deforestation Regulation require rapid reporting of forest cover changes with documented accuracy metrics.
Our processing chain follows best practices from peer-reviewed remote sensing literature, ensuring reproducibility and accuracy.
Sen2Cor and LaSRC applied to Sentinel-2 and Landsat imagery to convert top-of-atmosphere to bottom-of-atmosphere reflectance.
QA bands and Fmask 4.6 algorithm used to flag clouds, cloud shadows, and cirrus, achieving >95% cloud detection accuracy.
Monthly composites of NDVI and NDMI indices generated, smoothed using Savitzky-Golay filtering to reduce noise.
BFAST algorithm applied to detect abrupt breaks in vegetation time series, with post-classification into deforestation and degradation.
Stratified random sampling (n=500) with aerial validation. Error matrix computed for overall accuracy and Kappa coefficient.
Interactive D3.js time series showing cumulative forest cover loss and annual disturbance rates from 2000 to 2023.
Figure 1: Annual forest cover change (ha/year) for the concession area, derived from Landsat and Sentinel-2 time series. The trend line indicates a significant (p<0.01) declining rate of disturbance post-2015.
Three.js interactive globe showing the Cameroonian study area with Sentinel-2 and Landsat orbit paths.
Figure 2: 3D globe visualization showing the Cameroonian forest concession (red marker) with simulated satellite orbit paths (green) and acquisition swaths.
Our methodology is grounded in peer-reviewed research from leading remote sensing and conservation science journals.
Hansen, M.C., Potapov, P.V., Moore, R., et al. (2013). "High-Resolution Global Maps of 21st-Century Forest Cover Change." Science, 342(6160), 850-853.
DOI: 10.1126/science.1244693Reiche, J., Verbesselt, J., Hoekman, D., & Herold, M. (2018). "Improving near-real time deforestation monitoring in tropical humid forests by combining dense Sentinel-1 radar and dense Sentinel-2 optical time series." Remote Sensing of Environment, 204, 147-161.
DOI: 10.1016/j.rse.2017.10.034Vancutsem, C., Achard, F., Pekel, J.F., et al. (2021). "Long-term (1990-2019) monitoring of forest cover changes in the humid tropics." Science Advances, 7(10), eabe1603.
DOI: 10.1126/sciadv.abe1603