Gang Chen

• Associate Professor
McEniry 304
704-687-5947

Teaching and Research Interests

  • Remote Sensing and GIScience
  • Environmental Modeling
  • GEOgraphic Object-Based Image Analysis (GEOBIA)
  • Lidar (Light Detection and Ranging)
  • Machine Learning
  • Landscape Ecology

Recent Publications

 

*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.

 

Chen, G., Q. Weng, G.J. Hay and *Y. He (2018). Geographic Object-based Image Analysis (GEOBIA): Emerging trends and future opportunities. GIScience & Remote Sensing. DOI: 10.1080/15481603.2018.1426092.

Chen, G., *Y. He, A. De Santis, G. Li, R. Cobb and 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.

Li, W., Y. Zhou, K. Cetin, J. Eom, Y. Wang, G. Chen and X. Zhang (2017). Modeling urban building energy use: A review of modeling approaches and procedures. Energy, 141: 2445-2457.

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.

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.ii.

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.iii.

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.iv.

Singh, K.K., R. Bianchetti, G. Chen, and R.K. Meentemeyer (2016). Assessing effect of dominant land-cover types and pattern on urban forest biomass estimated using LiDAR metrics. Urban Ecosystems .DOI 10.1007/s11252-016-0591-8.v.

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.

Chen, G., R.P. Powers, L. M. T. de Carvalhoand, 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Powers, R., G. J. Hay and G. Chen (2012). How wetland type and area change through scale? A case study of Alberta's Boreal Plains. Remote Sensing of Environment, 15: 135-145.

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.

Presentations
*He, Y., and G. Chen (2017). A Weighted Spectral Signature Approach to Map Burn Severity in a Disease-impacted Forest Landscape. American Association of Geographers (AAG) Annual Meeting, Boston, MA, April 5-9. Narron, C.*, W. Sun*, and G. Chen (2017). Analyzing the Impact of Hydropower Scale on Tropical Forests in the Brazilian Amazon. American Association of Geographers (AAG) Annual Meeting, Boston, MA, April 5-9. He, Y. *, and G. Chen (2016). Integrating spectral, spatial and temporal information to map long-term forest disease progression. American Association of Geographers (AAG) Annual Meeting, San Francisco, California, March 29-April 2. (AAG Landscape Specialty Group Student Presentation First Place Award) Chen, G. Workshop: Satellite and Airborne Remote Sensing to Support Social Science Research”, The 14th Pacific Regional Science Conference Organization (PRSCO) Summer Institute, Bangkok, Thailand, June 27, 2016. Chen, G. “Multi-sensor Remote Sensing of Compound Disturbances in Forests”, AAG Remote Sensing Specialty Group Meeting, San Francisco, CA, March 31, 2016(Presented at the AAG Early Career Scholar in Remote Sensing Award reception). Chen, G. and R.K. Meentemeyer (2015). Assessing the influence of forest disease on wildfire burn severity using multi-sensor remote sensing. ASPRS (American Society for Photogrammetry and Remote Sensing) 2015 Annual Conference, Tampa, Florida, May4-8. Chen, G. and C. Godwin* and K.K. Singh(2015). How do urban residential patterns affect forest carbon density? An integration of high-resolution remote sensing and field mensuration. American Association of Geographers (AAG) Annual Meeting, Chicago, Illinois, April 21-25. Chen, G., Object-based change detection: how do image-objects mitigate the negative impact of misregistration on change accuracy? GEOBIA (GEOgraphic Object-Based Image Analysis) 2014, Thessaloniki, Greece, May 21 –23. Chen, G., M.R. Metz, D.M. Rizzo and R.K. Meentemeyer (2014). Assessing the impact of forest disease on burn severity: Integrating MASTER airborne simulator and Landsat TM data. ASPRS 2014 Annual Conference, Louisville, Kentucky, USA, March 23-27. Chen, G. (2013). Large-area forest height estimation using Landsat imagery calibrated by lidar plots. American Association of Geographers (AAG) Annual Meeting, Los Angeles, California, April 9-13.