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  1. Article ; Online: Remote sensing of forest degradation in Southeast Asia—Aiming for a regional view through 5–30 m satellite data

    Jukka Miettinen / Hans-Jürgen Stibig / Frédéric Achard

    Global Ecology and Conservation, Vol 2, Iss , Pp 24-

    2014  Volume 36

    Abstract: In this review paper we present geographical, ecological and historical aspects of Southeast Asia from the perspective of forest degradation monitoring and critically discuss available approaches for large area forest degradation monitoring with ... ...

    Abstract In this review paper we present geographical, ecological and historical aspects of Southeast Asia from the perspective of forest degradation monitoring and critically discuss available approaches for large area forest degradation monitoring with satellite remote sensing data at high to medium spatial resolution (5–30 m). Several authors have achieved promising results in geographically limited areas within Southeast Asia using automated detection algorithms. However, the application of automated methods to large area assessments remains a major challenge. To-date, nearly all large area assessments of forest degradation in the region have included a strong visual interpretation component. We conclude that due to the variety of forest types and forest disturbance levels, as well as the variable image acquisition conditions in Southeast Asia, it is unlikely that forest degradation monitoring can be conducted throughout the region using a single automated approach with currently available remote sensing data. The provision of regionally consistent information on forest degradation from satellite remote sensing data remains therefore challenging. However, the expected increase in observation frequency in the near future (due to Landsat 8 and Sentinel-2 satellites) may lead to the desired improvement in data availability and enable consistent and robust regional forest degradation monitoring in Southeast Asia. Keywords: Tropical forest disturbance, Selective logging, Shifting cultivation, Satellite data, Indochina peninsula, Maritime continent
    Keywords Ecology ; QH540-549.5
    Language English
    Publishing date 2014-12-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Towards Operational Monitoring of Forest Canopy Disturbance in Evergreen Rain Forests

    Andreas Langner / Jukka Miettinen / Markus Kukkonen / Christelle Vancutsem / Dario Simonetti / Ghislain Vieilledent / Astrid Verhegghen / Javier Gallego / Hans-Jürgen Stibig

    Remote Sensing, Vol 10, Iss 4, p

    A Test Case in Continental Southeast Asia

    2018  Volume 544

    Abstract: This study presents an approach to forest canopy disturbance monitoring in evergreen forests in continental Southeast Asia, based on temporal differences of a modified normalized burn ratio (NBR) vegetation index. We generate NBR values from each ... ...

    Abstract This study presents an approach to forest canopy disturbance monitoring in evergreen forests in continental Southeast Asia, based on temporal differences of a modified normalized burn ratio (NBR) vegetation index. We generate NBR values from each available Landsat 8 scene of a given period. A step of ‘self-referencing’ normalizes the NBR values, largely eliminating illumination/topography effects, thus maximizing inter-comparability. We then create yearly composites of these self-referenced NBR (rNBR) values, selecting per pixel the maximum rNBR value over each observation period, which reflects the most open canopy cover condition of that pixel. The ΔrNBR is generated as the difference between the composites of two reference periods. The methodology produces seamless and consistent maps, highlighting patterns of canopy disturbances (e.g., encroachment, selective logging), and keeping artifacts at minimum level. The monitoring approach was validated within four test sites with an overall accuracy of almost 78% using very high resolution satellite reference imagery. The methodology was implemented in a Google Earth Engine (GEE) script requiring no user interaction. A threshold is applied to the final output dataset in order to separate signal from noise. The approach, capable of detecting sub-pixel disturbance events as small as 0.005 ha, is transparent and reproducible, and can help to increase the credibility of monitoring, reporting and verification (MRV), as required in the context of reducing emissions from deforestation and forest degradation (REDD+).
    Keywords evergreen forest ; continental Southeast Asia ; canopy disturbance ; forest degradation ; selective logging ; change detection ; NBR ; self-referencing ; Science ; Q
    Subject code 333
    Language English
    Publishing date 2018-04-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

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