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Owen P. Parker

Publications and source records attributed to Owen P. Parker.

2 recordsLinked to original sources

Mapping extent and change in surface mines within the United States for 2001 to 2006

A complete, spatially explicit dataset illustrating the 21st century mining footprint for the conterminous United States does not exist. To address this need, we developed a semi-automated procedure to map the country's mining footprint (30-m pixel) and establish a baseline to monitor changes in mine extent over time. The process uses mine seed points derived from the U.S. Energy Information Administration (EIA), U.S. Geological Survey (USGS) Mineral Resources Data System (MRDS), and USGS National Land Cover Dataset (NLCD) and recodes patches of barren land that meet a “distance to seed” requirement and a patch area requirement before mapping a pixel as mining. Seed points derived from EIA coal points, an edited MRDS point file, and 1992 NLCD mine points were used in three separate efforts using different distance and patch area parameters for each. The three products were then merged to create a 2001 map of moderate-to-large mines in the United States, which was subsequently manually edited to reduce omission and commission errors. This process was replicated using NLCD 2006 barren pixels as a base layer to create a 2006 mine map and a 2001–2006 mine change map focusing on areas with surface mine expansion. In 2001, 8,324 km 2 of surface mines were mapped. The footprint increased to 9,181 km 2 in 2006, representing a 10·3% increase over 5 years. These methods exhibit merit as a timely approach to generate wall-to-wall, spatially explicit maps representing the recent extent of a wide range of surface mining activities across the country.

Land Degradation and Development

Downscaling global land-use/land-cover projections for use in region-level state-and-transition simulation modeling

Global land-use/land-cover (LULC) change projections and historical datasets are typically available at coarse grid resolutions and are often incompatible with modeling applications at local to regional scales. The difficulty of downscaling and reapportioning global gridded LULC change projections to regional boundaries is a barrier to the use of these datasets in a state-and-transition simulation model (STSM) framework. Here we compare three downscaling techniques to transform gridded LULC transitions into spatial scales and thematic LULC classes appropriate for use in a regional STSM. For each downscaling approach, Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathway (RCP) LULC projections, at the 0.5 × 0.5 cell resolution, were downscaled to seven Level III ecoregions in the Pacific Northwest, United States. RCP transition values at each cell were downscaled based on the proportional distribution between ecoregions of (1) cell area, (2) land-cover composition derived from remotely-sensed imagery, and (3) historic LULC transition values from a LULC history database. Resulting downscaled LULC transition values were aggregated according to their bounding ecoregion and “cross-walked” to relevant LULC classes. Ecoregion-level LULC transition values were applied in a STSM projecting LULC change between 2005 and 2100. While each downscaling methods had advantages and disadvantages, downscaling using the historical land-use history dataset consistently apportioned RCP LULC transitions in agreement with historical observations. Regardless of the downscaling method, some LULC projections remain improbable and require further investigation.

AIMS Environmental Science