• Spatial and temporal deep learning methods for deriving land-use following deforestation: A pan-tropical case study using Landsat time series

    Masolele RN, De Sy V et al.
    Remote Sensing of Environment

    In this paper, we assess the potential of spatial, temporal and spatio-temporal deep learning methods for large-scale classification of land-use following tropical deforestation using dense satellite time series on the pan-tropical scale. Continental models performed better than the pan-tropical model, while overall spatio-temporal models performed better than spatial or temporal ones.

  • An assessment of data sources, data quality and changes in national forest monitoring capacities in the Global Forest Resources Assessment 2005–2020

    Nesha MK, Herold, M, De Sy V et al.
    Environmental Research Letters

    In this paper, we assess the use and quality of forest monitoring data sources for national reporting to the FRA in 236 countries and territories. More specifically, we analyze the use of remote sensing and for forest monitoring in FRA 2005–2020, assess data quality in FRA 2020 using FAO tier-based indicators, and zoom in to investigate changes in tropical forest monitoring capacities in FRA 2010–2020.

  • Variation in aboveground biomass in forests and woodlands in Tanzania along gradients in environmental conditions and human use

    Suarez DR, Rozendaal DM, De Sy V et al.
    Environmental Research Letters

    Disturbed African tropical forests and woodlands have the potential to contribute to climate change mitigation. Therefore, there is a need to understand how carbon stocks of disturbed and recovering tropical forests are determined by environmental conditions and human use. In this case study, we explore how gradients in environmental conditions and human use determine aboveground biomass in national forest inventory plots located in forests and woodlands in mainland Tanzania.

  • Integrated assessment of deforestation drivers and their alignment with subnational climate change mitigation efforts

    Bos AB, De Sy V et al.
    Environmental Science & Policy

    Our interdisciplinary approach revealed the complexities of local direct and indirect DD drivers, and the complementarity of remotely sensed, spatially modelled and locally reported methods for driver identification. Overall, REDD+ interventions were found to be aligned with deforestation drivers.

  • Tropical deforestation drivers and associated carbon emission factors derived from remote sensing data

    De Sy V, Herold M, Achard F et al.
    Environmental Research Letters

    This study quantified post-deforestation land use across the tropics for the period 1990–2000. This dataset was then combined with a pan-tropical AGB map at 30 m resolution to refine emission factor from forest conversion by matching deforestation areas with their carbon stock before and after clearing and to assess spatial dynamics by follow-up land use.

  • Global data and tools for local forest cover loss and REDD+ performance assessment: Accuracy, uncertainty, complementarity and impact

    Bos A, De Sy V, Duchelle A et al.
    International Journal of Applied Earth Observation and Geoinformation

    Assessing the performance of REDD+ efforts requires data on forest cover change. Innovations in remote sensing and forest monitoring provide ever-increasing levels of coverage, spatial and temporal detail, and accuracy. In this paper we analyse (1) differences in accuracy between datasets of forest cover change; (2) if and how combinations of datasets can increase accuracy; and we demonstrate (3) the effect of (not) doing accuracy assessments for REDD+ performance measurements.

  • Comparing methods for assessing the effectiveness of subnational REDD+ initiatives

    Bos AB, Duchelle AE, Angelsen A et al.
    Environmental Research Letters

    Subnational REDD+ initiatives present an opportunity to compare different approaches to quantifying impacts on carbon emissions. This study (1) develops a Before-After-Control-Intervention (BACI) method to assess the effectiveness of 23 subnational REDD+ initiatives in Brazil, Peru, Cameroon, Tanzania, Indonesia and Vietnam; (2) compares the results at different scales; and (3) compares BACI with the simpler Before-After (BA) results.

  • Remote sensing of land use and carbon losses following tropical deforestation

    De Sy V
    PhD dissertation, Wageningen University

    The need for data on drivers and activities causing forest carbon change have been highlighted as central components in REDD+ readiness efforts. Assessment of direct and indirect drivers on the national level is often lacking or incomplete. This thesis explores the role of remote sensing for monitoring tropical forests for REDD+ in general, and for assessing land use and related carbon emissions linked to drivers of tropical deforestation in particular.

  • Synergies of multiple remote sensing data sources for REDD+ monitoring

    De Sy V, Herold M, Achard F et al.
    Current Opinion in Environmental Sustainability

    Remote sensing technologies can provide objective, practical and cost-effective solutions for developing and maintaining REDD+ monitoring systems. This paper reviews the potential and status of available remote sensing data sources with a focus on synergies among various approaches and evolving technologies.