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Person

Terry L Sohl

RESEARCH PHYSICAL SCIENTIST

Earth Resources Observation and Science (EROS) Center

Email: sohl@usgs.gov
Office Phone: 605-594-6537
ORCID: 0000-0002-9771-4231

Location
EROS - Mundt Federal Building
47914 252nd Street
Sioux Falls , SD 57198-9801
US

Supervisor: Peter J Doucette
Information on future land-use and land-cover (LULC) change is needed to analyze the impact of LULC change on ecological processes. The U.S. Geological Survey has produced spatially explicit, thematically detailed LULC projections for the conterminous United States. Four qualitative and quantitative scenarios of LULC change were developed, with characteristics consistent with the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES). The four quantified scenarios (A1B, A2, B1, and B2) served as input to the forecasting scenarios of land-use change (FORE-SCE) model. Four spatially explicit data sets consistent with scenario storylines were produced for the conterminous United...
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Scientists, planners, policy makers and other decision-makers in the South Central U.S. want to understand the potential impacts of changes in climate, precipitation, and land-use patterns on natural and cultural resources. Though the potential impacts of climate change can be modeled to help decision-makers plan for future conditions, these models rarely incorporate changes in land-use that may occur. Climate change and land-use change are often linked, as shifts in precipitation and temperature can alter patterns in human land-use activities, such as agriculture. This project sought to address this gap by developing new software tools that enable stakeholders to quickly develop custom, climate-sensitive land-use...
Categories: Project; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: 2016, CASC, Completed, Completed, Completed, All tags...
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The USGS Forecasting Scenarios of Land-use Change (FORE-SCE) model was used to produce an agricultural biofuel scenarios for the Northern Glaciated Plains, from 2012 to 2030. The modeling used parcel data from the USDA's Common Land Unit (CLU) data set to represent real, contiguous ownership and land management units. A Monte Carlo approach was used to create 50 unique replicates of potential landscape conditions in the future, based on a agricultural scenario from the U.S. Department of Energy's Billion Ton Update. The data are spatially explicit, covering the entire Northern Glaciated Plains ecoregions (an EPA Level III ecoregion), with a spatial resolution of 30-meters and 22 unique land-cover classes (including...
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The USGS’s FORE-SCE model was used to produce land-use and land-cover (LULC) projections for the conterminous United States. The projections were originally created as part of the "LandCarbon" project, an effort to understand biological carbon sequestration potential in the United States. However, the projections are being used for a wide variety of purposes, including analyses of the effects of landscape change on biodiversity, water quality, and regional weather and climate. The year 1992 served as the baseline for the landscape modeling. The 1992 to 2005 period was considered the historical baseline, with datasets such as the National Land Cover Database (NLCD), USGS Land Cover Trends, and US Department of Agriculture's...
Abstract (from ScienceDirect): The Land Change Monitoring, Assessment, and Projection (LCMAP) initiative uses temporally dense Landsat data and time series analyses to characterize landscape change in the United States from 1985 to present. LCMAP will be used to explain how past, present, and future landscape change affects society and natural systems. Here, we describe a modeling framework for producing high-resolution (spatial and thematic) landscape projections at a national scale, using a unique parcel-based modeling framework. The methodology was tested by modeling 11 land use scenarios and 3 climate realizations for the U.S. Great Plains. Results demonstrate 1) an ability to balance competing land-use demands...
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