Publications

Peer-reviewed Journal Articles and Book Chapters

Journal Publications:

  1. Chen, G., Zhou, Y., Voogt, J. A., & Stokes, E. C. (2024). Remote sensing of diverse urban environments: From the single city to multiple cities. Remote Sensing of Environment, 305, 114108.
  2. Chen, G., Hammelman, C., Anantsuksomsri, S., Tontisirin, N., Todd, A. R., Hicks, W.W., Robinson, H. M., Calloway, M.G., Bell, G.M., & Kinsey, J. E., III (2024). Fine-Scale (10 m) Dynamics of Smallholder Farming through COVID-19 in Eastern Thailand. Remote Sensing, 16, 1035.
  3. Xie, K., Zhu, J., Ren, H., Wang, Y., Yang, W., Chen, G., Lin, C., & Zhai, R. (2024). Delving into the Potential of Deep Learning Algorithms for Point Cloud Segmentation at Organ Level in Plant Phenotyping. Remote Sensing, 16, 3290.
  4. Anantsuksomsri, S., Positlimpakul, K., Chatakul, P., Janpathompong, D., Chen, G., & Tontisirin, N. (2024). Carbon sequestration analysis of the university campuses in the Bangkok Metropolitan Region. Journal of Infrastructure, Policy and Development, 8(6), 3385.
  5. Wang, T., Zhou, C., Qian, Y., Chen, G., Zhu, D., Zhu, Y., & Liu, Y. (2023). Basal Channel System and Polynya Effect on a Regional Air-Ice-Ocean-Biology Environment System in the Prydz Bay, East Antarctica. Journal of Geophysical Research: Earth Surface, 128, e2023JF007286.
  6. Hu, J., Zhou, Y., Yang, Y., Chen, G., Chen, W., & Hejazi, M. (2023). Multi-city assessments of human exposure to extreme heat during heat waves in the United States. Remote Sensing of Environment, 295, 113700.
  7. Shukla, T., Tang, W., Trettin, C.C., Chen, G., Chen, S., Allan, C. (2023). Quantification of Microtopography in Natural Ecosystems Using Close-Range Remote Sensing. Remote Sensing, 15, 2387.
  8. Zhang, T., Zhou, Y., Zhao, K., Zhu, Z., Chen, G., Hu, J., & Wang, L. (2022). A global dataset of daily maximum and minimum near-surface air temperature at 1km resolution over land (2003–2020). Earth System Science Data, 14, 5637–5649.
  9. Nickerson, S., Chen, G., Fearnside, P.M., Allan, C.J., Hu, T., de Carvalho, L.M.T., & Zhao, K. (2022). Forest loss is significantly higher near clustered small dams than single large dams per megawatt of hydroelectricity installed in the Brazilian Amazon. Environmental Research Letters, 17, 084026.
  10. Zhang, Y., Chen, G., Myint, S.W., Zhou, Y., Hay, G.J., Vukomanovic, J., & Meentemeyer, R.K. (2022). UrbanWatch: A 1-meter resolution land cover and land use database for 22 major cities in the United States. Remote Sensing of Environment, 278, 113106.
  11. Zhou, Y., Chen, G., & Zhou, W. (2022). Sustainable urban systems: from landscape to ecological processes. Ecological Processes, 11, 26.
  12. Chen, W., Y. Zhou, Y. Xie, G. Chen, K. J. Ding, & D. Li (2022). Estimating spatial and temporal patterns of urban building anthropogenic heat using a bottom-up city building heat emission model. Resources, Conservation and Recycling, 177, 105996.
  13. Hu, T., Toman, E. M., Chen, G., Shao, G., Zhou, Y., Li, Y., Zhao, K., & Feng, Y. (2021). Mapping fine-scale human disturbances in a working landscape with Landsat time series on Google Earth Engine. ISPRS Journal of Photogrammetry and Remote Sensing, 176: 250-261.
  14. He, Y., Chen, G., Cobb, R.C., Zhao, K., & Meentemeyer, R.K. (2021). Forest landscape patterns shaped by interactions between wildfire and sudden oak death disease. Forest Ecology and Management, 486: 118987.
  15. Dutta, D., Chen, G., Chen, C., Gagné, S.A., Li, C., Rogers, C., & Matthews, C. (2020). Detecting Plant Invasion in Urban Parks with Aerial Image Time Series and Residual Neural Network. Remote Sensing, 12: 3493.
  16. Chen, W., Zhou, Y., Wu, Q., Chen, G., Huang, X., & Yu, B. (2020). Urban Building Type Mapping Using Geospatial Data: A Case Study of Beijing, China. Remote Sensing, 12: 2805.
  17. Zhang, Y., Chen, G., Vukomanovic, J., Singh K.K., Liu, Y., Holden, S., & Meentemeyer, R.K. (2020). Recurrent Shadow Attention Model (RSAM) for shadow removal in high-resolution urban land-cover mapping. Remote Sensing of Environment, 247: 111945.
  18. Chen, G., Singh, K.K., Lopez, J., Zhou, Y. (2020). Tree canopy cover and carbon density are different proxy indicators for assessing the relationship between forest structure and urban socio-ecological conditions. Ecological Indicators, 113: 106279.
  19. He, Y., G. Chen, C. Potter, and R.K. Meentemeyer (2019). Integrating multi-sensor remote sensing and species distribution modeling to map the spread of emerging forest disease and tree mortality. Remote Sensing of Environment, 231: 11238.
  20. Lopez, J., Branch, J. W., Chen, G. (2019). Line-based image segmentation method : a new approach to segment VHSR remote sensing images automatically. European Journal of Remote Sensing, 52: 613–631.
  21. Wei, Y., X. Tong, G. Chen, D. Liu, Z. Han (2019). Remote Detection of Large-Area Crop Types: The Role of Plant Phenology and Topography. Agriculture, 9: 150.
  22. Whiteman, A., Gomez, C., Rovira, J., Chen, G., McMillan W.O., and Loaiza, J. (2019). Aedes Mosquito Infestation in Socioeconomically Contrasting Neighborhoods of Panama City. EcoHealth, 16: 210-221.
  23. Chen, S., A. Whiteman, A. Li, T. Rapp, E. Delmelle, G. Chen, C.L. Brown, P. Robinson, M.J. Coffman, D. Janies, and M. Dulin (2019). An operational machine learning approach to predict mosquito abundance based on socioeconomic and landscape patterns. Landscape Ecology, 34: 1295-1311.
  24. He, Y., G. Chen, A. De Santis, D. A. Roberts, Y. Zhou, R. K. Meentemeyer (2019). A Disturbance Weighting Analysis Model (DWAM) for Mapping Wildfire Burn Severity in the Presence of Forest Disease. Remote Sensing of Environment, 221: 108-121.
  25. Chen, G., J.-C. Thill, S. Anantsuksomsri, N. Tontisirin, R. Tao (2018). Stand age estimation of rubber (Hevea brasiliensis) plantations using an integrated pixel- and object-based tree growth model and annual Landsat time series. ISPRS Journal of Photogrammetry and Remote Sensing, 144: 94-104.
  26. Whiteman, A., E. Delmelle, T. Rapp, S. Chen, G. Chen, M. Dulin (2018). A novel sampling method to measure socioeconomic drivers of Aedes albopictus distribution in Mecklenburg County, North Carolina. International Journal of Environmental Research and Public Health, 15: 2179.
  27. Liu, D., E. Thoman, Z. Fuller, G. Chen, A. Londo, X. Zhang, K. Zhao (2018). Integration of historical map and aerial imagery to characterize long-term land-use change and landscape dynamics: An object-based analysis via Random Forests. Ecological Indicators, 95: 595-605.
  28. Chen, G., Q. Weng, G.J. Hay, Y. He (2018). Geographic Object-based Image Analysis (GEOBIA): Emerging trends and future opportunities. GIScience & Remote Sensing, 55: 159-182.
  29. Chen, G., Q. Weng (2018). Special issue: Remote sensing of our changing landscapes with Geographic Object-based Image Analysis (GEOBIA). GIScience & Remote Sensing, 55: 155-158. (Editorial)
  30. Li, W., Y. Zhou, K. Cetin, J. Eom, Y. Wang, G. Chen, X. Zhang (2017). Modeling urban building energy use: A review of modeling approaches and procedures. Energy, 141: 2445-2457.
  31. Chen, G., Y. He, A. De Santis, G. Li, R. Cobb, R.K. Meentemeyer (2017). Assessing the impact of emerging forest disease on wildfire using Landsat and KOMPSAT-2 data. Remote Sensing of Environment,195: 218-229.
  32. Cai, Y., G. Chen, Y. Wang, and L. Yang (2017). Impacts of land cover and seasonal variation on maximum air temperature estimation using MODIS imagery. Remote Sensing, 9: 233.
  33. Chen, G., E. Ozelkan, K. K. Singh, J. Zhou, M. R. Brown, and R. K. Meentemeyer (2017). Uncertainties in mapping forest carbon in urban ecosystems. Journal of Environmental Management,187: 229-238.
  34. Singh, K.K., R. Bianchetti, G. Chen, and R.K. Meentemeyer (2017). Assessing effect of dominant land-cover types and pattern on urban forest biomass estimated using LiDAR metrics. Urban Ecosystems, 20: 265-275.
  35. Singh, K.K., G. Chen, J.B. Vogler and R.K. Meentemeyer (2016). When Big Data are Too Much: Effects of LiDAR Returns and Point Density on Estimation of Forest Biomass. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9: 3210-3218.
  36. Ozelkan, E., G. Chen, and B.B. Ustundag (2016). Spatial Estimation of Wind Speed: A New Integrative Model Using Inverse Distance Weighting and Power Law. International Journal of Digital Earth, 9: 733-747.
  37. Ozelkan, E., G. Chen, and B.B. Ustundag (2016). Multiscale object-based drought monitoring and comparison in rainfed and irrigated agriculture from Landsat 8 OLI imagery. International Journal of Applied Earth Observation and Geoinformation, 44: 159-170. 
  38. Chen, G., R.P. Powers, L. M. T. de Carvalho and B. Mora (2015). Spatiotemporal patterns of tropical deforestation and forest degradation in response to the operation of the Tucuruí hydroelectric dam in the Amazon basin. Applied Geography, 63: 1-8.
  39. Lu, J., J. Li, G. Chen, L. Zhao, B. Xiong and G. Kuang (2015). Improving Pixel-Based Change Detection Accuracy Using an Object-Based Approach in Multitemporal SAR Flood Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8: 3486-3496.
  40. Zhao, K., M. García, S. Liu, Q. Guo; G. Chen, X. Zhang, Y. Zhou and X. Meng (2015). Terrestrial lidar remote sensing of forests: Maximum likelihood estimates of canopy profile, LAI, and leaf angle distribution. Agricultural and Forest Meteorology, 209-210: 100-113. 
  41. Chen, G., M.R. Metz, D.M. Rizzo and R.K. Meentemeyer (2015). Mapping burn severity in a disease-impacted forest landscape using Landsat and MASTER imagery. International Journal of Applied Earth Observation and Geoinformation, 40: 91-99.
  42. Chen, G., M.R. Metz, D.M. Rizzo, W.W. Dillon and R.K. Meentemeyer (2015). Object-based assessment of burn severity in diseased forests using high-spatial and high-spectral resolution MASTER airborne imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 102: 38-47.
  43. Singh, K.K., G. Chen, J.B. McCarter and R.K. Meentemeyer (2015). Effects of LiDAR point density and landscape context on estimates of urban forest biomass. ISPRS Journal of Photogrammetry and Remote Sensing, 101:310-322.
  44. Godwin, C., G. Chen, K. K. Singh (2015). The impact of urban residential development patterns on forest carbon density: An integration of LiDAR, aerial photography and field mensuration. Landscape and Urban Planning, 136: 97-109.
  45. Powers, R.P., T. Hermosilla, N.C. Coops and G. Chen (2015). Remote sensing and object-based techniques for mapping fine-scale industrial disturbances. International Journal of Applied Earth Observation and Geoinformation, 34: 51-57.
  46. Hultquist, C., G. Chen and K. Zhao (2014). A Comparison of Gaussian Process Regression, Random Forests and Support Vector Regression for Burn Severity Assessment in Diseased Forests. Remote Sensing Letters, 5:723-732.
  47. Chen, G., K. Zhao and R. Powers (2014). Assessment of the Image Misregistration Effects on Object-based Change Detection. ISPRS Journal of Photogrammetry and Remote Sensing, 87:19-27.
  48. Wulder, M.A., J.C. White, C.W. Bater, N.C. Coops, C. Hopkinson, and G. Chen. (2012). Lidar plots-a new large-area data collection option: context, concepts, and case study. Canadian Journal of Remote Sensing, 38:600-618.
  49. Chen, G., M.A. Wulder, J.C. White, T.H. Hilker, and N.C. Coops. (2012). Lidar calibration and validation for geometric-optical modeling with Landsat imagery. Remote Sensing of Environment, 124:384-393.
  50. Chen, G., G. J. Hay, L. M. T. Carvalho and M. A. Wulder (2012). Object-Based Change Detection. International Journal of Remote Sensing, 33:4434-4457.
  51. Chen, G., G. J. Hay and B. St-Onge (2012). A GEOBIA framework to estimate forest parameters from lidar transects, Quickbird imagery and machine learning: a case study in Quebec, Canada. International Journal of Applied Earth Observation and Geoinformation, 15:28-37.
  52. Powers, R., G. J. Hay and G. Chen (2012). How wetland type and area differ through scale? A case study of Alberta’s Boreal Plains. Remote Sensing of Environment, 15: 135-145.
  53. Chen, G., K. Zhao, G. J. McDermid and G. J. Hay (2012). The influence of sampling density on geographically weighted regression: a case study using forest canopy height and optical data. International Journal of Remote Sensing, 33:2909-2924.
  54. Hay, G. J., C. D. Kyle, B. Hemachandran, G. Chen, M. M. Rahman and T. S. Fung (2011). Geospatial Technologies to Improve Urban Energy Efficiency. Remote Sensing, 3: 1380-1405.
  55. Chen, G. and G. J. Hay (2011). A support vector regression approach to estimate forest biophysical parameters at the object level using airborne lidar transects and Quickbird data. Photogrammetric Engineering and Remote Sensing, 77:733-741.
  56. Chen, G. and G. J. Hay (2011). An airborne lidar sampling strategy to model forest canopy height from Quickbird imagery and GEOBIA. Remote Sensing of Environment, 115:1532-1542.
  57. Chen, G., G. J. Hay, G. Castilla, B. St-Onge and R. Powers (2011). A multiscale geographic object-based image analysis (GEOBIA) to estimate lidar-measured forest canopy height using Quickbird imagery. International Journal of Geographic Information Science, 25:877-893.
  58. Shen, Q., G. Chen, D. E and C. Zhou (2011). Recent elevation changes on the Lambert-Amery system in East Antarctica from ICESat crossover analysis. Chinese Journal of Geophysics, 54: 1983-1989. (In Chinese)
  59. E, D., Q. Shen, Y. Xu and G. Chen (2009). High-accuracy topographical information extraction based on fusion of ASTER stereo-data and ICESat/GLAS data in Antarctica. Science in China Series D: Earth Sciences, 52: 714-722.
  60. Chen, G. and D. E (2007). Support Vector Machines for Cloud Detection over Ice-Snow Areas. Geo-spatial Information Science, 10: 117-120.
  61. Chen, G. and D. E (2006). Cloud Detection Based on Texture Analysis and SVM over Ice-snow Covered Areas. Geomatics and Information Science of Wuhan University, 31: 403-406. (In Chinese)
  62. E, D. and G. Chen (2005). Detection of Cloud, Snow and Ice Based on ETM+ Thermal Infrared Imagery in Antarctica. Geomatics and Information Science of Wuhan University, 30: 913-916. (In Chinese)
  63. E, D. and G. Chen (2005). Cloud Detection of Multispectral Images in Antarctica Based on Wide Thresholds and A Gradient Algorithm. Chinese Journal of Polar Research, 17: 93-98. (In Chinese)
  64. Chen, G. and D. E (2005). Digital Orthographic Mapping of Antarctic Areas. Journal of Geomatics, 30: 7-8. (In Chinese)

Book Chapters:

  1. Reeves, M., I. Ibáñez, D. Blumenthal, G. Chen, Q. Guo, C. Jarnevich, J. Koch, F. Sapio, M. Schwartz, R.K. Meentemeyer, B. Wylie, and S. Boyte (2021). Chapter 11: Tools and Technologies for Quantifying Spread and Impacts of Invasive Species. In Poland, Therese M.; Patel-Weynand, Toral; Finch, Deborah M.; Ford Miniat, Chelcy; Hayes, Deborah C.; Lopez, Vanessa M. (Ed.), Invasive Species in Forests and Rangelands of the United States: A Comprehensive Science Synthesis for the United States Forest Sector. Heidelberg, Germany: Springer International Publishing. 455p.
  2. Singh, K. K., L. Smart, and G. Chen (2018). LiDAR and optical data integration for coastal wetland assessment. In Q. Weng, Y. He (Ed.), High Spatial Resolution Remote Sensing: Data, Techniques, and Applications (pp. 71-88). Boca Raton, Florida: CRC Press, Taylor & Francis Group.
  3. Chen, G., and R.K. Meentemeyer (2016). Remote Sensing of Forest Damage by Diseases and Insects. In Q. Weng (Ed.), Remote Sensing for Sustainability (pp. 145-162). Boca Raton, Florida: CRC Press, Taylor & Francis Group.