Abstract
Rapid landscape changes as a result of anthropogenic development can result in increased hazards for nearby communities, including exposure of soils to runoff, pollution, and slope collapse. Elevation changes also complicate interpretations of remote sensing datasets, such as interferometric synthetic aperture radar (InSAR), which rely on accurate digital elevation models (DEMs). In this study, we assimilate satellite-based radar and optical imagery spanning several decades to determine a time series of elevation change at the Centralia Coal Mine in Centralia, Washington. We assess the errors associated with each observation type and explore methods for reducing potential bias. By combining these datasets, we are able to characterize elevation changes resulting from coal mining operations for most of the productive lifespan of the mine. This approach can be applied to any region of rapid elevation change, provided sufficient remote sensing data are available.
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Schedule a callMore From: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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