| A. Elmes, J.G. Yarlequé Ipanaqué, J. Rogan, N.Cuba, A. Bebbington | Published by Remote Sensing Letters 5(10): 882-891. |
Since the early 2000s, the Madre de Dios Region of southern Peru has experienced rapid expansion of both licit and illicit mining activities, in the form of artisanal and small-scale mining (ASM). ASM typically takes place in remote, inaccessible locations and is therefore difficult to monitor in situ . This paper explores the utility of Landsat-5 imagery via decision tree classification to determine ASM locations in Madre de Dios. Spectral mixture analysis was used to unmix Landsat imagery, using WorldView and QuickBird l imagery to aid spectral endmember selection and validate AMS maps. The ASM maps had an overall area-weighted accuracy of 96% and indicated a large proportion of illicit ASM activity (~65% of all ASM in the study area) occurring outside the permitted concessions. Holistic visual comparison of ASM output maps with reference imagery showed that these methods produce reasonable, realistic maps of mined area extent.