Feasibility of multi-spectral and radar data fusion for mapping Artisanal Small-Scale Mining: A case study from Indonesia

Abstract

Artisanal small-scale mining (ASM) is an environmentally damaging activity in many developing countries, particularly in the wet tropics, yet serves as a crucial economic resource for millions of people. The lack of effective mapping methods hinders quantifying the spatial extent of ASM and management efforts. This study presents a novel approach to integrate multi-spectral and imaging radar datasets within the Google Earth Engine (GEE) platform to map ASGM in a tropical rainforest. We used a case study of gold mining in central Kalimantan and diverse training and validation data sources. The methodology involved pre-processing multispectral and radar imagery, generating and standardizing covariates, applying feature-level data fusion for the Random Forest algorithm in GEE, and training and classifying data with optimized parameters through iterative loops. This approach achieved a classification accuracy of 81% in detecting ASM activities, surpassing the accuracy of a map constructed solely from Sentinel-2 multispectral data by 14%. Through the inclusion of evaluation metrics such as the f(β) score and Matthews Correlation Coefficient (MCC), our approach demonstrates its robustness in accurately identifying target instances, while reducing false positives and addressing imbalanced class sizes by 6.25% and 60%, respectively. Our model’s efficacy underscores its potential to accurately map ASM at larger regional scales (104 – 10⁶ km2) in wet-tropical forests, while being scalable and resource-efficient. Opportunities to further improve this approach by mitigating false-positive errors involve integrating texture filtering with optical and radar data sets. Despite some inherent limitations, our approach overcomes some current challenges of mapping small-scale, but extensive, environmental changes in the wet tropics and thus advances improvements in the continual surveillance, management, and regulation of ASM and other activities that involve selective clearing.

Keywords

• Artisanal small-scale gold mining
• Data fusion
• Multi-spectral
• SAR
• Surveillance