Comparison of optical and SAR data in tropical land cover classification for REDD+

Laura Sirro, Tuomas Häme, Yrjö Rauste, Oleg Antropov, Jarno Hämäläinen, Petri Latva-Käyrä, Fernando Paz, Bernardus de Jong

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientific

    Abstract

    A comparison study was performed to evaluate the applicability of optical and SAR data for land cover classification for REDD+ services on a test site in Chiapas State in Mexico. The accuracy of the maps was assessed using an independent data set that was collected from very high resolution optical data. The overall accuracy of the maps varied between 79 % of ENVISAT ASAR and 94 % of RapidEye for the forest - non-forest classifications. The accuracies for the six IPCC compliant classes were from 5 to 9 percentage units lower. Results that were obtained with the optical data were somewhat better than the results using SAR data. However, the difference between the optical and SAR results was fairly small when L-band SAR data were used. L-band SAR data seem to be competitive alternative for optical data particularly in the areas with frequent cloud cover
    Original languageEnglish
    Title of host publicationProceedings of the ESA Living Planet Symposium 2013
    EditorsLeny Ouwehand
    Place of PublicationNoordwijk
    PublisherEuropean Space Agency (ESA)
    Number of pages7
    ISBN (Print)978-92-9221-286-5
    Publication statusPublished - 2013
    MoE publication typeB3 Non-refereed article in conference proceedings
    EventESA Living Planet Symposium 2013 - Edinburgh, United Kingdom
    Duration: 9 Sept 201313 Sept 2013
    Conference number: ESA SP-722

    Conference

    ConferenceESA Living Planet Symposium 2013
    Country/TerritoryUnited Kingdom
    CityEdinburgh
    Period9/09/1313/09/13

    Keywords

    • Remote sensing
    • land cover
    • classification
    • REDD
    • optical
    • SAR

    Fingerprint

    Dive into the research topics of 'Comparison of optical and SAR data in tropical land cover classification for REDD+'. Together they form a unique fingerprint.

    Cite this