Geographic Information Science Center of Excellence
South Dakota State University
SDSU Website
USGS Website

GIScCE Faculty
Dr. Matthew Hansen (Co-Director)
Dr. Tom Loveland (Co-Director)
Dr. Kwabena Asante
Dr. Mark Cochrane
Dr. Kevin Gallo
Dr. Geoffrey Henebry
Dr. Shuguang (Leo) Liu
Dr. David Roy
Dr. Gabriel Senay
Dr. Jim Vogelmann
Dr. Mike Wimberly
Dr. Chunsun Zhang
Dr. Zhiliang Zhu

Dr. Shuguang (Leo) Liu of EROS specializes in development and applications of complx modeling and decision-support systems to simulate human-land-atmosphere interactions and environmental consequences at the site to global scales. With funding from the US Geological Survey, NASA, Department of Defense, USAID and NSF, Dr. Liu's current research activities include (1)developing advanced data assimilation systems to enhance capability in monitoring and forecasting the status and trends of terrestrial ecosystems using models and observations from ground and space, (2)quantifying the spatial and temporal dynamics of CO2 exchange between the terrestrial biosphere and the atmosphere with a special emphasis on the impacts of land use and climate change for the United States and Africa, (3)investigating the impacts of soil erosion and deposition on ecosystem productivity, soil profile evolution, and atmospheric CO2 concentration, (4)developing a spatially distributed biogeochemical modeling system to support the sustainable management of a military installation, and (5)developing an integrated ecological and economic modeling system for estimating carbon sequestration supply in Costa Rica. Dr. Liu has a Ph.D. in Forestry with an emphasis on watershed management and hydrology from the University of Florida, a M.S. in Forest Ecology from Beijing Forestry University and a B.S. in Forest Science from Central-South Forestry College, Zhuzhou, China.

Fig. 1. Comparison of the simulated gross primary production (GPP) with eddy flux tower measurements. Figure shows data assimilation techniques can dramatically improve model performance. The driving forces of the models include remotely sensed vegetation and climate conditions.
Fig. 2. Spatial patterns of carbon stocks in soil (SOC) and biomass in 1974 and 2000 in a 10-km by 10-km block in the southeastern United States. Carbon stocks were simulated using the General Ensemble biogeochemical Modeling System (GEMS) at a spatial resolution of 60m.


Fig. 1
Fig. 2