Rachel R Sleeter

I started my career with the U.S. Geological Survey (USGS) in 2000, directly after graduating with a B.S. in Geography from University of Oregon. I initially worked for the Earth Science Information Center in Menlo Park, CA. where I became an expert on USGS data products, outreach and public needs. At this time I continued on as a student and obtained my Masters Degree in Geography from San Jose State University. My thesis work motivated me to pursue Geographic Information Systems (GIS) and Remote Sensing as a platform for accomplishing research on new geographic mapping methods. Dasymetric mapping for population density became my primary focus in my graduate work and also for various USGS hazard vulnerability applications. We built a Dasymetric Mapping Tool, an ArcGIS enabled tool, that is publically available to download. This tool automates the interpolation process used to allocate census population to suitable urban land use and cover cells. I continue to integrate this tool into many USGS projects and work with the requests from the academic and professional community.

Currently, I am developing an integrated modeling framework for the Great Dismal Swamp ecosystem, where net ecosystem carbon balance, natural disturbance, and land management can be evaluated with scenarios. Multi-year, in situ field collection of the ecological and biological processes will be used to develop a baseline carbon budget. The baseline carbon budget for the Great Dismal Swamp is input into a state and transition simulation model coupled with a stock-flow model. Future scenarios will be modeled to evaluate priority ecosystem services and assist the U.S. Fish and Wildlife Service with land management decisions. This research is funded and led by the Climate and Land Use Change Mission Area as part of the LandCarbon program and represents one part of a multi-partner project with the U.S. Fish and Wildlife Service, The Nature Conservancy, and George Mason, Clemson, East Carolina, and Southern Methodist Universities.

I have also been involved with LandCarbon at the national scale. I worked as part of a team to develop modeling inputs to integrate the comprehensive results from 1970-2000 Land Cover Trends data with global climate scenarios to spatially represent land use and cover out to 2100. Since the release of the first LandCarbon assessment for the conterminous United States, we adopted a state and transition modeling framework that uses a stock-flow model to track carbon flows. The model is referred to as the Land Use and Carbon Scenario Simulator (LUCAS). The LUCAS model is highly flexible, capable of running on local desktop workstations or in supercomputing environments (we are running extensive Monte Carlo simulations using NASA AMES's Pleiades supercomputer). This work represents an exciting breakthrough in the ability to model future changes in LULC and ecosystem carbon dynamics.