Multidecadal Landsat Time Series Reveals the Nature and Magnitude of Mining's Impact on Agriculture and Natural Vegetation in the Peruvian Highlands (1986-2011)

Authors: Nicholas Cuba*, Brown University
Topics: Remote Sensing, Land Use and Land Cover Change, Cultural and Political Ecology
Keywords: Remote Sensing, Landsat, Time Series, Extractive Industries, Mining, Peru
Session Type: Paper
Day: 4/11/2018
Start / End Time: 1:20 PM / 3:00 PM
Room: Iberville, Marriott, River Tower Elevators, 4th Floor
Presentation File: No File Uploaded

Accelerated global expansion of mining, driven by growing demand for resources and facilitated by technological innovation, has transformed landscapes to an unprecedented degree and poses significant challenges to environmental sustainability. Extractive operations occupy a small area relative to other land uses such as agriculture or forestry, yet they may trigger tremendous, diffuse changes to land systems and compete for land or resource access with other anthropogenic drivers of change such as agriculture. Mining may impact agricultural production through a number of pathways, including: restricted access to land or water, outmigration, and intensification prompted by reduction in the amount of available cropland. These dynamics are well illustrated by development in Peru during that country's mining boom of the past 30 years. During this span, the regions of Cajamarca and La Libertad in the North-Central Peruvian highlands have seen the development of multiple productive mines, exploration activities and widespread expansion of mineral concessions, all near, or upstream from, large areas of agriculture. This paper uses temporally dense Landsat (1985-2011) and MODIS data series (2000-2011) to characterize the spatial extent and intensity of agricultural practices in La Libertad during these decades, to measure change of land cover as well as of vegetation condition attributable to mining, and to gauge the impact of extraction and of legal concessions to subsurface resources on agriculture. This long-term time series of moderate spatial resolution data offers the opportunity to test hypotheses about the relative strength of potential pathways through which mining impact agriculture.

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