Publications

Peer-Reviewed Articles (*: Corresponding author; †:student co-author) 

Remote Sensing for mapping/monitoring land use and land cover change 

1. Zhu, Z., Zhou, Y., Seto, K. C., Stokes, E. C., Deng, C., Pickett, S. T. A., Taubenböck, H. (2019) Understanding an urbanizing planet: Strategic directions for remote sensing. Remote Sensing of Environment, 228, 164-182.

2. Deng, C.*, and Zhu, Z. Continuous subpixel monitoring of urban impervious surface using Landsat time series. (2018) Remote Sensing of Environment.

3. Deng, C.*, Li, C.†, Zhu, Z., Lin, W.†, & Xi, L.†. (2017) Subpixel urban impervious surface mapping: the impact of input Landsat images. ISPRS Journal of Photogrammetry and Remote Sensing, 133, 89-103.

4. Deng, C.* (2016). Automated construction of multiple regional libraries for neighborhoodwise local multiple endmember unmixing. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(9), 4232-4246.

5. Deng, C.* (2015). Incorporating endmember variability into linear unmixing of coarse resolution imagery: Mapping large-scale impervious surface abundance using a hierarchically object-based spectral mixture analysis. Remote Sensing, 7(7), 9205-9229.

6. Deng, C.*, Wu, C., and Jia, X. (2014). Spatial-constrained multiple endmember spectral mixture analysis for quantifying sub-pixel urban impervious surfaces. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(6), 1976-1984. 

7. Deng, C., and Wu, C. (2013). A spatially adaptive spectral mixture analysis method for mapping subpixel urban impervious surface distribution. Remote Sensing of Environment, 133, 62-70.

8. Deng, C., and Wu, C. (2013). The use of single-date MODIS imagery for estimating large-scale urban impervious surface fraction with spectral mixture analysis and machine learning techniques. ISPRS Journal of Photogrammetry and Remote Sensing, 86, 100-110. (Top 25 Most Downloaded Arcticle)

9. Deng, C., and Wu, C. (2013). Examining the impacts of urban biophysical compositions on surface urban heat island: a spectral unmixing and thermal mixing approach. Remote Sensing of Environment, 131, 262-274.

10. Deng, C., and Wu, C. (2013). Estimating very high resolution land surface temperature using a spectral unmixing and thermal mixing approach. International Journal of Applied Earth Observation and Geoinformation, 23, 155-164.

11. Deng, C., and Wu, C. (2012). BCI: a biophysical composition index for remote sensing of urban environments. Remote Sensing of Environment, 127, 247-259. (Top 25 Most Downloaded Arcticle)

GIS and Remote Sensing for Sustainable Urban Developmet 

1. Deng, C.*, Lin, W.†, and Chen, S.† (2018) Use of smart meter readings and nighttime light images to track pixel-level electricity consumption. Remote Sensing Letter, 10:3, 205-213.

2. Deng, C., Lin, W.†, Ye, X., Li, Z., Zhang, Z., and Xu, G. Social media data as a proxy for hourly fine-scale power consumption estimation. Environment and Planning A: Economy and Space. (Accepted, 2018)

3. Xu, Y., Ho, H. C., Wong, M. S., Deng, C., Shi, Y., Chan, T. C., Knudby, A. (2018) Evaluation of machine learning techniques with multiple remote sensing datasets in estimating monthly concentrations of ground-level PM2.5. Environment Pollution, 242, 1417-1426.

4. Deng, C.* (2015). Integrating multi-source remotely sensed datasets to examine the impact of tree height and pattern information on crimes in Milwaukee, Wisconsin. Applied Geography, 65, 38-48. 

5. Deng, C.*, & Ma, J. † (2015). Viewing urban decay from the sky: A multi-scale analysis of residential vacancy in a shrinking U.S. city. Landscape and urban planning, 141, 88-99. 

6. Huang, W., and  Deng, C. (2015). A geographic approach to carbon accounting of Wisconsin. Journal of Maps. DOI:10.1080/17445647.2015.1020892

7. Deng, C., and Wu, C.(2013). Improving small-area population estimation: an integrated geographic and demographic approach. Annals of the Association of American Geographers, 103(5), 1123-1141.

8. Deng, C., Wu, C., and Wang, L. (2010). Improving housing unit method for small area population estimation using remote sensing and GIS Information. International Journal of Remote Sensing, 31(21), 5673-5688.

GIS and Remote Sensing for Physical Environment: 

1. Wu, Q., Liu, H., Wang, L., and Deng, C. (2015). Evaluation of AMSR2 soil moisture products over the contiguous United States using in situ data from the International Soil Moisture Network. International Journal of Applied Earth Observation and Geoinformation.

2. Wu, Q., Deng, C., and Chen Z. (2016) Automated delineation of karst sinkholes from LiDAR-derived digital elevation models. Geomorphology, 266, 1-10.

3. Huang, W., Deng, C., and Day, M.J.(2014). Differentiating tower karst (fenglin) and cockpit karst (fengcong) using DEM contour, slope, and centroid. Environmental Earth Sciences, 72, 407-416. 

4. Huang, C., Ye, X., Deng, C., Zhang, Z., and Wang, Z. (2016) Mapping above-ground biomass by integrating optical and SAR imagery: A case study of Xixi National Wetland Park, China. Remote Sensing, 8 (8), 647.

Conference Proceedings

1. Deng, C., and Tao, H. (2008). "Agent-based modeling to simulate the dengue spread". The 16th International Conference on Geoinformatics & Joint Conference on GIS and Built Environment, Guangzhou, China, June 28-29.

2. Tao, H., Li, X., Chen, X., and Deng, C. (2008). "Multi-agent simulation of the von The von Thunen model formation mechanism". The 16th International Conference on Geoinformatics & Joint Conference on GIS and Built Environment, Guangzhou, China, June 28-29.

3. Ye, Z. and Deng, C. (2008). "Acquiring height distribution information about high-rises in Beijing using shadow in SPOT-5". The 16th International Conference on Geoinformatics & Joint Conference on GIS and Built Environment, Guangzhou, China, June 28-29.

4. Pan, M., Tao, H., and Deng, C. (2008). "Analysis of Neighborhood Radii Influence on Segregation". ICSC'2008-the 7th International Conference on System Simulation and Scientific Computing, 

Conference Presentations

1. Deng, C. Small-area household size estimation using remote sensing, GIS and demographic information, Association of American Geographers Annual Meeting, Las Vegas, NV, March 22-27, 2009

2. Deng, C. The use of very-high-resolution remote sensing imagery for population estimation.The American Society for Photogrammetry and Remote Sensing, Milwaukee, WI, May 1-5, 2011

3. Deng, C. Development of a biophysical composition index (BCI) for urban remote sensing. Association of American Geographers Annual Meeting, Los Angeles, CA, April 9-13, 2013

4. Wu, C. and Deng, C. .GIS datasets for improving small Area housing unit estimation, Association of American Geographers Meeting, Las Vegas, NV, March 22-27, 2009

5. Deng, C. Improving small-area housing unit and population estimation using remote sensing and GIS datasets, Association of American Geographers Annual Meeting, Seattle, WA, April 12-17, 2011

6. Deng, C. Examining socioeconomic and environmental impacts on obesity in two different counties. Association of American Geographers Annual Meeting, Chicago, IL, April 21-25, 2015

7. Deng, C. “Modelling residential vacancy in a shrinking city by integrating high resolution remote sensing and gis datasets”. Middle States AAG Annual Meeting, Binghamton, NY, October 2-3, 2015. 

8. Wu, Y. and Deng, C. “Mapping urban extent by combining nighttime light and Landsat imagery”. Middle States AAG Annual Meeting, Binghamton, NY, October 2-3, 2015.

9. Deng, C. “Modelling residential vacancy in a shrinking city by integrating high resolution remote sensing and GIS datasets”. Middle States AAG Annual Meeting, Binghamton, NY, October 2 – 3, 2015. 

10. Wu, Y. and Deng, C. “Mapping urban extent by combining nighttime light and Landsat imagery”. Middle States Association of American Geographers Annual Meeting, Binghamton, NY, October 2 – 3, 2015. 

11. Deng, C. “Mapping subpixel urban cover distribution by linear unmixing of MODIS 1-km time series”, Association of American Geographers Annual Meeting, San Francisco, CA, March 29 – April 2, 2016.

12. Xin Hong, Jay Lee, and Deng, C. “Geographical Variations of Livestock Production in Northern China”. ASPRS IGTF2017, Baltimore, MD, March 13 – 17, 2017.

13. Deng, C. “Mapping subpixel urban impervious surface area using machine learning technique”, AAG Annual Meeting, Boston, MA, April 5-9, 2017.

14. Deng, C. “The impacts of input Landsat images for subpixel urban impervious surface mapping: Status and Solution”, AAG Annual Meeting, New Orleans, LA, April 10-14, 2018.