Electronic versions


  • Mailys Lopes
    Zoological Society of London
  • Pierre-Louis Frison
    University Paris-Est Marne-la-Vallée
  • Merry Crowson
    Zoological Society of London
  • Eleanor Warren-Thomas
    University of York
  • Bambang Hariyadi
    Jambi University, Jambi, Indonesia
  • Winda D. Kartika
    Jambi University, Jambi, Indonesia
  • Fahmuddin Agus
    Indonesian Soil Research Institute
  • Keith C. Hamer
    University of Leeds
  • Lindsay Stringer
    University of Leeds
  • Jane K. Hill
    University of York
  • Nathalie Pettorelli
    Zoological Society of London
1. The recent availability of high spatial and temporal resolution optical and radar satellite imagery has dramatically increased opportunities for mapping land coverat fine scales. Fusion of optical and radar images has been found useful in tropical areas affected by cloud cover because of their complementarity. However,the multitemporal dimension these data now offer is often neglected because
these areas are primarily characterized by relatively low levels of seasonality and
because the consideration of multitemporal data requires more processing time.
Hence, land cover mapping in these regions is often based on imagery acquired fora single date or on an average of multiple dates.
2. The aim of this work is to assess the added value brought by the temporal dimension of optical and radar time series when mapping land cover in tropical environments. Specifically, we compared the accuracies of classifications based on (a)
optical time series, (b) their temporal average, (c) radar time series, (d) their temporal average, (e) a combination of optical and radar time series and (f) a combination
of their temporal averages for mapping land cover in Jambi province, Indonesia,
using Sentinel-1 and Sentinel-2 imagery.
3. Using the full information contained in the time series resulted in significantly
higher classification accuracies than using temporal averages (+14.7% for
Sentinel-1, +2.5% for Sentinel-2 and +2% combining Sentinel-1 and Sentinel-2).
Overall, combining Sentinel-2 and Sentinel-1 time series provided the highest accuracies (Kappa = 88.5%).
4. Our study demonstrates that preserving the temporal information provided by
satellite image time series can significantly improve land cover classifications in
tropical biodiversity hotspots, improving our capacity to monitor ecosystems of high conservation relevance such as peatlands. The proposed method is reproducible, automated and based on open-source tools satellite imagery.


  • cloud persistent areas, conservation, data combination, land cover classification, remote sensing, satellite image time series, Sentinel-1, Sentinel-2
Original languageEnglish
Pages (from-to)532-541
JournalMethods in Ecology and Evolution
Issue number4
Early online date27 Jan 2020
Publication statusPublished - 1 Apr 2020
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