Abstract
This study develops a modelling framework by utilizing multi-sensor imagery for classifying different forest and land use types in the Phnom Kulen National Park (PKNP) in Cambodia. Three remote sensing datasets (Landsat optical data, ALOS L-band data and LiDAR derived Canopy Height Model (CHM)) were used in conjunction with three different machine learning (ML) regression techniques (Support Vector Machines (SVM), Random Forests (RF) and Artificial Neural Networks (ANN)). These ML methods were implemented on (a) Landsat spectral data, (b) Landsat spectral band & ALOS backscatter data, and (c) Landsat spectral band, ALOS backscatter data, & LiDAR CHM data. The Landsat-ALOS combination produced more accurate classification results (95% overall accuracy with SVM) compared to Landsat-only bands for all ML models. Inclusion of LiDAR CHM (which is a proxy for vertical canopy heights) improved the overall accuracy to 98%. The research establishes that majority of PKNP is dominated by cashew plantations and the nearly intact forests are concentrated in the more inaccessible parts of the park. The findings demonstrate how different RS datasets can be used in conjunction with different ML models to map forests that had undergone varying levels of degradation and plantations.
Highlights
Conversion of forests to plantations for commodity production is a leading cause of permanent forest loss globally
We evaluate the ability of some common Remote sensing (RS) data and machine learning (ML) algorithms tools in mapping human modified forest-plantation tropical ecosystems, focusing on the cashew plantations that have encroached in an IUCN Category II protected forests of Phnom Kulen National Park (PKNP) in Cambodia
The problem of cashew plantation encroachment in PKNP is a microcosm of the challenges faced by the protected areas of SE Asia
Summary
Conversion of forests to plantations for commodity production is a leading cause of permanent forest loss globally. Southeast Asia, are the worst affected by the global demand for commodities (such as oil palm and rubber) and the subsequent conversion of forests to agricultural plantations (Koh & Wilcove, 2008; Edwards et al, 2010; Edwards et al, 2013). Commercial agricultural plantations such as rubber and acacia are encroaching in the forests of continental Asia (Torbick et al, 2017; Zeng et al, 2018). Plantations for commodity crops exist in Laos, China, Vietnam and Myanmar (Phompila et al, 2014; Grogan et al, 2015; Chen et al, 2016)
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