Research

Peer-reviewed Publications ( denotes student or postdoc coauthors)

Zhang, T. and D. Liu. 2024. Estimating fractional vegetation cover from multispectral unmixing modeled with local endmember variability and spatial contextual information. ISPRS Journal of Photogrammetry and Remote Sensing.

Zhou, W., L. Zhang, A. Sheshukov, J. Wang, M. Zhu, K. Sargsyan, D. Xu, D. Liu, T. Zhang, V. Mazepa, A. Sokolov, V. Valdayskikh, V. Ivanov. 2024. Surface ground heat flux reconstruction using Bayesian uncertainty quantification machinery and surrogate modeling.  Earth and Space Science.

Mukherjee, R., and D. Liu. 2023. Spatial and spectral translation of Landsat 8 to Sentinel-2 using conditional generative adversarial networks. Remote Sensing 15 (23), 5502.

Wang, J. and D. Liu. 2023. Models overestimate ecosystem water use efficiency for northern permafrost regions. Agricultural and Forest Meteorology, 339, 109594.

Zhao, Y., E. Bonello, and D. Liu. 2023. Mapping the environmental risk of beech leaf disease in the northeastern United States. Plant Disease.

Zhang, T. and D. Liu. 2023. Improving ICESat-2 based boreal forest height estimation by a multivariate sample quality control approach. Methods in Ecology and Evolution.

Zhang, T. and D. Liu. 2023. Reconstructing digital terrain models from ArcticDEM and WorldView-2 imagery in Livengood, Alaska. Remote Sensing, 15 (8), 2061.

Wang, J. and D. Liu. 2023. Larger diurnal temperature range undermined later autumn leaf senescence with warming in Europe. Global Ecology and Biogeography, 32: 734-746.

Wang, J., D. Liu, S. Quiring, and R. Qin. 2023. Estimating canopy height change using machine learning by coupling WorldView-2 stereo imagery with Landsat-7 data. International Journal of Remote Sensing, 44 (2), 631-645.

Liang, X., D. Liu, Z. Wang, and J. Wang. 2022. Characterizing the dynamics of wildland-urban interface and the potential impacts on fire activity in Alaska from 2000 to 2010. Landscape and Urban Planning 228, 104553.

Liu, D. and X. Zhu. 2022. Dense satellite image time series analysis: opportunities, challenges, and future directions. New Thinking in GIScience, Li et al (eds). Springer, Singapore.

Kafy, A.A., M. Saha, A.A. Faisal, Z.A. Rahaman, D. Liu, M.T. Rahman, M.A. Fattah, A.A. Rakib, S.N. Rahaman, M.Z. Hasan, and M.A.K. Ahasan. 2022. Predicting the impacts of land use/land cover changes on seasonal urban thermal characteristics using machine learning algorithms. Building and Environment, 217, 109066.

Li, Y., H. Miller, E. Root, H. Ayaz, and D. Liu. 2022. Understanding the role of urban social and physical environment in opioid use disorder using found geospatial data. Health and Place, 75, 102792.

Zhao, Y. and D. Liu. 2022. A robust and adaptive spatial-spectral fusion model for PlanetScope and Sentinel-2 imagery. GIScience and Remote Sensing, 59 (1), 520-546.

Berezina, P. and D. Liu. 2022. Hurricane damage assessment using coupled convolutional neural networks: A case study of Hurricane Michael. Geomatics, Natural Hazards and Risk, 13 (1), 414-431.

Wang, J., D. Liu, P. Ciais, and J. Peñuelas. 2022. Decreasing rainfall frequency contributes to earlier leaf onset in northern ecosystems. Nature Climate Change, 1-7.

Zhou, W., V. Mazepa, S. Shiyatov, T. Zhang, D. Liu, A. Sheshukov, J. Wang, H.E. Sharif, V. Ivanov, and Y. Shalaumova. 2022. Spatiotemporal dynamics of encroaching tall vegetation in timberline ecotone of the polar Urals region, Russia. Environmental Research Letters.

Wang, J. and D. Liu. 2022. Vegetation green‐up date is more sensitive to permafrost degradation than climate change in spring across the northern permafrost region. Global Change Biology, 28(4): 1569-1582.

Mukherjee, R. and D. Liu. 2021. Downscaling MODIS spectral bands using deep learning. GIScience & Remote Sensing, 58(8): 1300-1315.

Park, Y., J.M. Guldmann, and D. Liu. 2021. Impacts of tree and building shades on the urban heat island: combining remote sensing, 3-D digital city and spatial regression approaches. Computers, Environment and Urban Systems, 88: 101655 .

Liang, J. and D. Liu. 2021. Automated estimation of daily surface water fraction from MODIS and Landsat images using Gaussian process regression. International Journal of Remote Sensing, 42(11): 4261-4283.

Zhao, Y., B. Huang, D. Liu, and Q. He. 2021. A sparse representation-based fusion model for improving daily MODIS C6.1 aerosol products on a 3 km grid. International Journal of Remote Sensing, 42(3): 1077-1095.

Zhao, Y., D. Liu, and X. Wei. 2020. Monitoring harmful algal blooms at high spatiotemporal resolution by fusing Landsat and MODIS imagery. Environmental Advances,  100008.

Dai, X., G. Yang, D. Liu, and R. Wan. 2020. Vegetation carbon sequestration mapping in herbaceous wetlands by using a MODIS EVI time-series data set: a case in Poyang Lake wetland, China. Remote Sensing, 12(18): 3000.

Liang, J. and D. Liu. 2020. Estimating daily inundation probability using remote sensing, riverine flood, and storm surge models: a case of hurricane Harvey. Remote Sensing, 12(9): 1495.

Liang, J. and D. Liu. 2020. A local thresholding approach to flood water delineation using Sentinel-1 SAR imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 159: 53-62.

Albanwan, H., R. Qin, X. Liu, M. Li, D. Liu, and J.M. Guldmann. 2020. 3D iterative spatiotemporal filtering for classification of multitemporal satellite data sets. Photogrammetric Engineering & Remote Sensing, 86(1): 23-31.

Zhu, X. and D. Liu. 2019. Investigating the impact of land parcelization on forest composition and structure in southeastern Ohio using multi-source remotely sensed data. Remote Sensing, 11(19): 2195.

Su, W., J. Huang, D. Liu, and M. Zhang. 2019. Retrieving corn canopy leaf area index from multitemporal Landsat imagery and terrestrial LiDAR data. Remote Sensing, 11(5): 572.

Kim, R.S., M. Durand, and D. Liu. 2018. Spectral analysis of airborne passive microwave measurements of alpine snowpack: Colorado, USA. Remote Sensing of Environment 205: 469-484.

Zhu, X., H. Eileen, J. Chen, and D. Liu. 2018. An automatic system for reconstructing high-quality seasonal Landsat time series. Remote Sensing: Time Series Image Processing. Qihao Weng (eds). CRC Press/Taylor & Francis Group.

Cai, S. and D. Liu. 2018. Mapping land cover change trajectories with monthly MODIS time series from 2001 to 2010. Remote Sensing: Time Series Image Processing. Qihao Weng (eds). CRC Press/Taylor & Francis Group.

He, L., A. Páez, and D. Liu. 2017. Built environment and violent crime: An environmental audit approach using Google Street View. Computers, Environment and Urban Systems 66: 83-95.

Pan, J., M. Durand, B. Vander Jagt, and D. Liu. 2017. Application of a Markov Chain Monte Carlo algorithm for snow water equivalent retrieval from passive microwave measurements. Remote Sensing of Environment 192: 150-165.

He, L., A. Páez, and D. Liu. 2017. Persistence of crime hot spots: an ordered probit analysis. Geographical Analysis 49: 3-22.

Gangodagamage, C., E. Foufoula-Georgiou, S.P. Brumby, R. Chartrand, A. Koltunov, D. Liu, M. Cai, and S.L. Ustin. 2016. Wavelet-compressed representation of landscapes for hydrologic and geomorphologic applications. IEEE Geoscience and Remote Sensing Letters 13(4): 480-484.

Wang, H., D. Liu, D.K. Munroe, K. Cao, and C. Biermann. 2016. Study on selecting environmental variables in modeling species spatial distribution. Annals of GIS 22(1): 165-177.

Zhu, X., E.H. Helmer, F. Gao, D. Liu, J. Chen, and M.A. Lefsky. 2016. A flexible spatiotemporal method for fusing satellite images with different resolutions. Remote Sensing of Environment 172:165-177.

Wehmann, A. and D. Liu. 2015. A spatial-temporal contextual Markovian kernel method for multi-temporal land cover mapping. ISPRS Journal of Photogrammetry and Remote Sensing 107: 77-89.

Cai, S. and D. Liu. 2015. Detecting change dates from dense satellite time series using a sub-annual change detection algorithm. Remote Sensing 7:8705-8727.

Wainwright, J., K. Mercer, S. Jiang, and D. Liu. 2015. The political ecology of a highway through Belize’s forested borderlands. Environment and Planning A 47: 833-849.

Wang, H., D. Liu, H. Lin, A. Montenegro, and X. Zhu. 2015. NDVI and vegetation phenology dynamics under the influence of sunshine duration on the Tibetan Plateau. International Journal of Climatology 35(5): 687-698.

Wang, J., Y. Zhao, C. Li, L. Yu, D. Liu, and P. Gong. 2015. Mapping global land cover in 2001 and 2010 with spatial-temporal consistency at 250m resolution. ISPRS Journal of Photogrammetry and Remote Sensing 103: 38-47.

Zhu, X. and D. Liu. 2015. Improving forest aboveground biomass estimation using seasonal Landsat NDVI time-series. ISPRS Journal of Photogrammetry and Remote Sensing 102: 222-231.

He, L., A. Páez, D. Liu, and S. Jiang. 2015. Temporal stability of model parameters in crime rate analysis: An empirical examination. Applied Geography 58: 141-152.

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 forest 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.

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.

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.

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.

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.

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.

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.

Guo, Q., W. Li, D. Liu, and J. Chen. 2012. A framework for supervised image classification with incomplete training samples. Photogrammetric Engineering & Remote Sensing 78: 595-604.

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.

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.

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.

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.Van Meirvenne. 2010. Predicting the spatial variation of the 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.

Mishra, U., R. Lal, B. Slater, F. Calhoun, D. Liu, and M.Van Meirvenne. 2009. Predicting soil organic carbon stock using profile depth distribution functions and ordinary kriging. Soil Science Society of America Journal 73(2): 614-621.

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.

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., 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.

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.

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.