Abstract
Forests in Southeast Asia are experiencing some of the highest rates of deforestation and degradation in the world, with natural forest species being replaced by cropland and plantation monoculture. In this work, we have developed an innovative method to accurately map rubber and palm oil plantations using fusion of Landsat-8, Sentinel 1 and 2. We applied cloud and shadow masking, bidirectional reflectance distribution function (BRDF), atmospheric and topographic corrections to the optical imagery and a speckle filter and harmonics for Synthetic Aperture Radar (SAR) data. In this workflow, we created yearly composites for all sensors and combined the data into a single composite. A series of covariates were calculated from optical bands and sampled using reference data of the land cover classes including surface water, forest, urban and built-up, cropland, rubber, palm oil and mangrove. This training dataset was used to create biophysical probability layers (primitives) for each class. These primitives were then used to create land cover and probability maps in a decision tree logic and Monte-Carlo simulations. Validation showed good overall accuracy (84%) for the years 2017 and 2018. Filtering for validation points with high error estimates improved the accuracy up to 91%. We demonstrated and concluded that error quantification is an essential step in land cover classification and land cover change detection. Our overall analysis supports and presents a path for improving present assessments for sustainable supply chain analyses and associated recommendations.
Highlights
Up to 27% of forest loss has been attributed to permanent land use change for commodity production, and is currently estimated at 61% in southeast Asia [1]
This study focuses on mapping rubber and palm oil plantations, and includes other existing dominant land cover types in the area
We have demonstrated that a combination of Sentinel-2, Landsat-8 and Sentinel-1 provides a sufficiently dense spatio-temporal data series, even in regions with persistent cloud cover, to separate between different land cover and plantations types
Summary
Up to 27% of forest loss has been attributed to permanent land use change for commodity production, and is currently estimated at 61% in southeast Asia [1]. The inventory of available mature plantation wood, relative to biodiversity assets, protected areas, and the extent, size, and stand age of rubber plantations is supporting improved characterization of the available rubber wood supply for sustainable management of these resources This information is key for the development of responsible natural fiber and timber supply chains for these commodities which benefit local stakeholders. This information can help to identify high and low risk business opportunities for alternative timber sources in Myanmar in order to have reduced impacts on biodiversity and livelihoods
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