Desheng Liu

Desheng Liu

Desheng Liu


(614) 247-2775

1056 Derby Hall
154 North Oval Mall
Columbus OH 43210

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Areas of Expertise

  • Remote Sensing
  • Spatial Statistics
  • GIScience
  • Land Cover Change


  • Ph.D., 2006 Environmental Science, University of California, Berkeley
  • M.A., 2004 Statistics, University of California, Berkeley
  • M.S., 2003 Environmental Science, University of California, Berkeley
  • B.E., 2001 GIS, Wuhan University, China

Current CV:


Interests: Remote Sensing, Spatial Statistics, GIScience, Land Cover Change.

Current Research: My research focuses on developing geo-spatial data analysis methodologies for monitoring and modeling environmental and ecological processes. It draws upon an array of geo-spatial and statistical approaches, particularly remote sensing and spatial statistics. While I have brought these approaches to bear on numerous research problems, a central theme in my research is the statistical modeling of the spatial or spatial-temporal dimension of the processes under study.

Courses Taught:
Geography 5100-Quantitative Geographical Methods
Geography 5270-Geographic Applications of Remote Sensing
Geography 8102-Application of Quantitative Methods in Geography
Statistics 6530-Introduction to Spatial Statistics

Select Publications:
Liu, D. and S. Cai. 2012. A spatial-temporal modeling approach to reconstructing land-cover change trajectories from multi-temporal satellite imagery. Annals of the Association of American Geographers (DOI: 10.1080/00045608.2011.596357).

Liu, D. and X. Zhu. 2012. An enhanced physical method for downscaling thermal infrared radiance. IEEE Geoscience and Remote Sensing Letters 9(4): 690-694.

Liu, D. and F. Xia. 2010. Assessing object-based classification: advantages and limitations. Remote Sensing Letters 1(4): 187-194.

Kang, E.L., D. Liu, and N. Cressie. 2009. Statistical analysis of small-area data based on independence, spatial, non-hierarchical, and hierarchical models. Computational Statistics and Data Analysis 53: 3016-3032.

Liu, D., K. Song, J.R. Townshend, and P. Gong. 2008. Using local transition probability models in Markov random fields for forest change detection. Remote Sensing of Environment 112(5): 2222-2231.