Title: Towards operational monitoring of forest canopy disturbance in evergreen rain forests: a test case in continental Southeast Asia
Authors: LANGNER ANDREASMIETTINEN JUKKAKUKKONEN MARKUSVANCUTSEM CHRISTELLESIMONETTI DARIOVIEILLEDENT GHISLAINVERHEGGHEN ASTRIDGALLEGO PINILLA FRANCISCOSTIBIG HANS-JURGEN
Citation: REMOTE SENSING vol. 10 no. 4 p. 544
Publisher: MDPI AG
Publication Year: 2018
JRC N°: JRC109502
ISSN: 2072-4292
URI: http://www.mdpi.com/2072-4292/10/4/544
http://publications.jrc.ec.europa.eu/repository/handle/JRC109502
DOI: 10.3390/rs10040544
Type: Articles in periodicals and books
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 DrNBR 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+).
JRC Directorate:Sustainable Resources

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