· Remote Sensing Methods and Applications
· Spatial Statistics and Environmental Statistics
· Geographic Information Systems and Science
· Land Use and Land Cover Change
· Ph.D. in Environmental Science, University of California, Berkeley, 2006
· M.A. in Statistics, University of California, Berkeley, 2004
· M.S. in Environmental Science, University of California, Berkeley, 2003
· B.E. in GIS, Wuhan University, China, 2001
· Associate Professor, Department of Geography (100% FTE) and Department of Statistics (0% FTE), The Ohio State University, Since 2013.
· Associate Professor, Department of Geography (75% FTE) and Department of Statistics (25% FTE), The Ohio State University, 2012-2013.
· Associate Professor, Environmental Science Graduate Program, The Ohio State University, Since 2012.
· Assistant Professor, Department of Geography (75% FTE) and Department of Statistics (25% FTE), The Ohio State University, 2006-2012.
· Geography 5100 – Quantitative Geographical Methods
· Geography 5270 – Geographic Applications of Remote Sensing
· Geography 8102 – Spatial Data Analysis
· Geography 8104 – Advanced Remote Sensing
· Statistics 3450 – Basic Statistics for Engineers
· Statistics 6530 – Introduction to Spatial Statistics
· Zhu, X. and D. Liu. In Press. Improving forest aboveground biomass estimation using seasonal Landsat NDVI time-series. ISPRS Journal of Photogrammetry and Remote Sensing.
· Wang, H., D. Liu, H. Lin, A. Montenegro, and X. Zhu. In Press. NDVI and vegetation phenology dynamics under the influence of sunshine duration on the Tibetan Plateau. International Journal of Climatology.
· Wang, J., Y. Zhao, C. Li, L. Yu, D. Liu, and P. Gong. In Press. Mapping global land cover in 2001 and 2010 with spatial-temporal consistency at 250m resolution. ISPRS Journal of Photogrammetry and Remote Sensing.
· Kwan, M.P., D. Liu, and J. Vogliano. 2015. Assessing dynamic exposure to air pollution. In Space-Time Integration in Geography and GIScience: Research Frontiers in the US and China. Mei-Po Kwan, Douglas Richardson, Donggen Wang and Chenghu Zhou (eds). Dordrecht: Springer.
· Zhu, X. and D. Liu. 2014. Accurate mapping of forest types using dense seasonal Landsat time-series. ISPRS Journal of Photogrammetry and Remote Sensing 96: 1-11.
· Wang, H., H. Lin, and D. Liu. 2014. Remotely sensed drought index and its responses to meteorological drought in southwest China. Remote Sensing Letters 5(5): 413-422.
· Liu, J.K., D. Liu, and D. Alsdorf. 2014. Extracting ground-level DEM from SRTM DEM in forested environments based on mathematical morphology. IEEE Transactions on Geoscience and Remote Sensing 52(10): 6333-6340.
· Cai, S., D. Liu, D. Sulla-Menashe, and M. Friedl. 2014. Enhancing MODIS land cover product with a spatial-temporal modeling algorithm. Remote Sensing of Environment 147: 243-255.
· Zhang, F., X. Zhu, and D. Liu. 2014. Blending MODIS and Landsat images for urban flood mapping. International Journal of Remote Sensing 35(9): 3237-3253.
· Zhu, X. and D. Liu. 2014. MAP-MRF approach to Landsat ETM+ SLC-off image classification. IEEE Transactions on Geoscience and Remote Sensing 52(2): 1131-1141.
· Wainwright, J., S. Jiang and D. Liu. 2013. Deforestation and the world-as-representation: the Maya forest of southern Belize. In Land Change Science, and Political Ecology and Sustainability: Synergies and Divergences. Brannstrom, C. and Vadjunec, J. Eds. Springer.
· Wan, R., D. Liu, D. Munroe, and S. Cai. 2013. Modeling the potential hydrological impact of abandoned underground mines in Monday Creek Watershed, Ohio. Hydrological Processes 27(25): 3607-3616.
· Cai, S. and D. Liu. 2013. A comparison of object-based and contextual pixel-based classifications using high and medium spatial resolution images. Remote Sensing Letters 4(10): 998-1007.
· Kumar, S., R. Lal, and D. Liu. 2013. Estimating the spatial distribution of organic carbon density for the soils of Ohio, USA. Journal of Geographical Sciences 23(2): 280-296.
· Jiang, S. and D. Liu. 2012. Box-counting dimension of fractal urban form: stability issues and measurement design. International Journal of Artificial Life Research 3(3), 521-525.
· Cressie, N. and D. Liu. 2012. Geographic Information Systems (GIS), spatial statistics in. Encyclopedia of Environmetrics, 2nd eds, A. H. El-Shaarawi and W. W. Piegorsch. Wiley, New York.
· Kumar, S., R. Lal, and D. Liu. 2012. A geographically weighted regression kriging approach for mapping soil organic carbon stock. Geoderma 189-190: 627-634.
· Zhu, X., D. Liu, and J. Chen. 2012. A new geostatistical approach for filling gaps in Landsat ETM+ SLC-off images. Remote Sensing of Environment 124: 49-60.
· 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.
· Guo, Q., W. Li, D. Liu, J. Chen. 2012. A framework for supervised image classification with incomplete training samples. Photogrammetric Engineering & Remote Sensing 78: 595-604.
· Durand, M.T. and D. Liu. 2012. The need for prior information in characterizing snow water equivalent from microwave brightness temperatures. Remote Sensing of Environment 126: 248-257.
· Li, W., J. Radke, D. Liu, and P. Gong. 2012. Measuring detailed urban vegetation with multi-source high-resolution remote sensing imagery for environmental design and planning. Environment and Planning B, Planning and Design 39(3): 566-585.
· Zhu, X., F. Gao, D. Liu, and J. Chen. 2012. A modified neighborhood similar pixel interpolator approach for removing thick clouds in Landsat images. IEEE Geoscience and Remote Sensing Letters 9(3): 521-525.
· 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 102(6): 1329-1347.
· Pu, R. and D. Liu. 2011. Segmented canonical discriminant analysis of in situ hyperspectral data for identifying thirteen urban tree species. International Journal of Remote Sensing 32(8): 2207-2226.
· Liu, D. and F. Xia. 2010. Assessing object-based classification: advantages and limitations. Remote Sensing Letters 1(4): 187-194.
· Mishra, U., R. Lal, D. Liu, and M.V. Meirvenne. 2010. Predicting the spatial variation of soil organic carbon pool at a regional scale. Soil Science Society of America Journal 74(3): 906-914.
· Liu, D., and Y. Chun. 2009. The effects of different classification models on error propagation in land cover change detection. International Journal of Remote Sensing 30(20): 5345-5364.
· 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.
· Mishra, U., R. Lal, B. Slater, F. Calhoun, D. Liu, and M.V. Meirvenne. 2009. Predicting soil organic carbon stock within different depth intervals using profile depth distribution functions and ordinary kriging. Soil Science Society of America Journal 72(2): 614-621.
· Kelly, M., D. Liu, B. McPherson, D. Wood, and R. Standiford. 2008. Spatial pattern dynamics of oak mortality and associated disease symptoms in a California hardwood forest affected by sudden oak death. Journal of Forest Research 13:312-319.
· Liu, D., and R. Pu. 2008. Downscaling thermal infrared radiance for subpixel land surface temperature retrieval. Sensors 8: 2695-2706.
· 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.
· Liu, D., M. Kelly, P. Gong, and Q. Guo. 2007. Characterizing spatial-temporal tree mortality patterns associated with a new forest disease. Forest Ecology and Management 253: 220-231.
· Kelly, M., Q. Guo, D. Liu, and D. Shaari. 2007. Modeling the risk of a new invasive forest disease in the United States: an evaluation of five environmental niche models. Computers, Environment and Urban Systems 31(6): 689-710.
· Guo, Q., M. Kelly, P. Gong, and D. Liu. 2007. An object-based classification approach in mapping tree mortality using high spatial resolution imagery. GIScience and Remote Sensing 44(1): 24-47.
· Liu, D., M. Kelly, and P. Gong. 2006. A spatial-temporal approach to monitoring forest disease spread using multi-temporal high spatial resolution imagery. Remote Sensing of Environment 101(2): 167-180.
· Liu, D., P. Gong, M. Kelly, and Q. Guo. 2006. Automatic registration of airborne images with complex local distortion. Photogrammetric Engineering and Remote Sensing 72(9): 1049-1059.
· Kim, A., D. Liu, and P. Gong. 2004. Change detection from SPOT-Panchromatic imagery at the urban-rural fringe of Ho Chi Minh City, Vietnam. Annals of GIS 10(1): 42-48.
· Kelly, M. and D. Liu. 2004. Mapping diseased oak trees using ADAR imagery. Geocarto International 19(1): 57-64.
· Kelly, M., D. Shaari, Q. Guo, and D. Liu. 2004. A comparison of standard and hybrid classifier methods for mapping hardwood mortality in areas affected by sudden oak death. Photogrammetric Engineering and Remote Sensing 70(11): 1229-1239.