Peer Reviewed Journal


[1]  Huang W*, Min W, Ding J, Liu Y, Hu Y, Shen H*. (2021). Forest height mapping using inventory and multi-source satellite data. Forest Ecosystem, 00253 (under review).

[2]  Chen S, Huang W*, Chen Y, Feng M. (2021). An adaptive thresholding approach to extract flood coverage from Sentinel-1 SAR imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (in revision).

[3]  Ding J, Huang W*, Hu Y, Liu Y. (2021). Estimation of Forest Aboveground Biomass in Northwest Hunan Province Based on Machine Learning and Multi-source Data. Scientia Silvae Sinicae (in Chinese). 2021, 57 (10) (in press)

[4]  Song XP, Huang W*, Hansen MC, Potapov P. (2021). An evaluation of Landsat, Sentinel-2, Sentinel-1 and MODIS data for crop type mapping. Science of Remote Sensing, 3, 100018.
DOI:
10.1016/j.srs.2021.100018.

[5]  Huang W*, Dolan K, Swatantran A, Johnson K, Tang H, O'Neil-Dunne J, Dubayah R, Hurtt G. (2019). High-Resolution Mapping of Aboveground Biomass for Forest Carbon Monitoring System in the Tri-State Region of Maryland,Pennsylvania and Delaware,USA. Environment Research Letters. 14(6): 095002.
DOI:
10.1088/1748-9326/ab2917.

[6]      Huang W*, DeVries B, Huang C, Jones J, Lang M, Creed I, undefinedamp; Carroll M. (2018). Automated Extraction of Surface Water Extent from Sentinel-1 data. Remote Sensing. 10 (5): 797-816. DOI: 10.3390/rs10050797.

[7]      Huang W*, Swatantran A, Duncanson L, Johnson K, Watkinson D, Dolan K, O-Neil Dune J, Hurtt G, and Dubayah R. (2017). County-Scale Biomass Map Comparison: a Case Study for Sonoma. Carbon Management. 1-18. DOI: 10.1080/17583004.2017.1396840.

[8]      Huang W*, Swatantran A#, Johnson K, Duncanson L, Tang H, O'Neil-Dunne J, Hurtt G, Dubayah R. (2015). Local Discrepancies in Continental Scale Biomass Maps: A Case Study over Forested and Non-Forested Landscapes in Maryland, USA. Carbon Balance and Management. 2015. 10-19.
DOI:
10.1186/s13021-015-0030-9.

[9]   Huang W*, Sun G, Ni W, Zhang Z, Dubayah R. (2015). Sensitivity of Multi-Source SAR Backscatter to Changes in Forest Aboveground Biomass, Remote Sens. 8 (7): 9587-9609. DOI: 10.3390/rs70809587.

[10]   Huang W*, Sun G, Montesano P, Ni W, Zhang Z. (2013). Mapping biomass change after forest disturbance: Applying LiDAR footprint-derived models at key map scales. Remote Sensing of Environment. 134: 319-332. DOI: 10.1016/j.rse.2013.03.017

 

[11]  Dou P, Shen H, Li Z, X. Guan and Huang W. (2021). Remote Sensing Image Classification Using Deep–Shallow Learning, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 3070-3083, 2021, DOI: 10.1109/JSTARS.2021.3062635.

[12]   Ma L, Hurtt G, Tang H, Lamb R, Campbell E, Dubayah R, Guy M, Huang W, Lister A, Lu J, O'Neil-Dunne J, Rudee1 J, Shen Q undefinedamp; Silva C. (2021). High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USA. Environmental Research Letters. 16 (4) 045014. DOI: 10.1088/1748-9326/abe4f4

[13]   Shen H, Li H*, Zeng C, Li Q, Huang W, Wu C, Zhang H. (2021). Design of teaching contents for introduction to remote sensing. Bull. Surv. Map (in Chinese). 2021, 0(1): 148-151. (CSCD)

[14]   DeVries B*, Huang C, Armston J, Huang W, Jones J, Lang M. (2020). Rapid and robust monitoring of flood events using Sentinel-1 and Landsat data on the Google Earth Engine. Remote Sensing of Environment. 240. DOI: 10.1016/j.rse.2020.111664

[15]   Hu Y, Xu X, Wu F, Sun Z, Xia H, Meng Q, Huang W, Zhou H, Gao J, Li W, Peng D*, Xiao, X. (2020). Estimating Forest Stock Volume in Hunan Province, China, by Integrating in Situ Plot Data, Sentinel-2 Images, and Linear and Machine Learning Regression Models. Remote Sens. 2020, 12(1), 186;
DOI: doi.org/10.3390/rs12010186.

[16]   Hurtt G*, Zhao M, Sahajpal R, Armstrong A, Birdsey RA, Campbell K, Dolan K, Dubayah R, Fish JP, Huang C, Huang W, Johnson K, Lamb R, Ma L, Marks R, O'Leary III D, O'Neil-Dunne J, Swantaran A, undefinedamp; Tang H. (2019). Beyond MRV: High-resolution forest carbon modeling for climate mitigation planning over MD, USA. Environment Research Letters, 14 (4): 045013. DOI: 10.1088/1748-9326/ab0bbe.

[17]   Duncanson L*, Huang W, Johnson K, Swatantran A, O-Neil Dune J, Hurtt G, and Dubayah R. (2017). Implications of Allometric Equation Selection for County-level Biomass Mapping (2017). Carbon Balance and Management. 2017 Dec; 12: 18. DOI: 10.1186/s13021-017-0086-9.

[18]   Johnson K*, Domke GM, Russell MB, Walters B, Hom J, Peduzzi A, Birdsey R, Katelyn D undefinedamp; Huang W. (2017). Estimating understory vegetation carbon in the United States. Environmental Research Letters. 12, 125010. DOI: 10.1088/1748-9326/aa8fdb

[19]   DeVries B*, Huang C, Lang M, Jones J, Huang W undefinedamp; Creed I. (2017). Automated quantification of surface water fraction in wetlands using optical Landsat and Sentinel-2 imagery. Remote Sensing. 9(8), 807;
DOI:
10.3390/rs9080807.

[20]   Zhang Z.*, Ni, W., Sun, G., Huang, W., Ranson, K.J., Cook, B., undefinedamp; Guo, Z. (2017). Biomass Retrieval from L-band Polarimetric UAVSAR Backscatter and PRISM Stereo Imagery. Remote Sensing of Environment, 194, 331-346. DOI: 10.1016/j.rse.2017.03.034.

[21]   Implications of Allometric Equation Selection for County-Level Biomass Estimates. Carbon Balance and Management. 2017 Dec; 12: 18. DOI: 10.1186/s13021-017-0086-9.

[22]   Cheng X*, Huang W, undefinedamp; Gong J. (2015). Adaptive polarimetric decomposition using incoherent ground scattering models without reflection symmetry assumption. Geo-spatial Information Science, 18, 1-10.
DOI:
10.1080/10095020.2015.1016201.

[23]   Rosette J*, Cook B, Nelson R, Huang C, Masek JG, Tucker C, Sun G, Huang W, Montesano P, Rubio-Gil J, undefinedamp; Ranson J. (2015). Sensor Compatibility for Biomass Change Estimation Using Remote Sensing Data Sets: Part of NASA's Carbon Monitoring System Initiative. IEEE Geoscience and Remote Sensing Letter, 12 (7): 1511-1515. DOI: 10.1109/LGRS.2015.2411262.

[24]   Cheng X*, Huang W, Gong J. (2014). An Unsupervised Scattering Mechanism Classification Method for PolSAR Images. IEEE Geoscience and Remote Sensing Letter, 11: 1677-1681. 
DOI:
10.1109/LGRS.2014.2305655.

[25]   Ni W*, Sun G, Ranson KJ, Zhang Z, He Y, Huang W, undefinedamp; Guo, Z. (2014). Model-Based Analysis of the Influence of Forest Structures on the Scattering Phase Center at L-Band. IEEE Trans. Geos. Remote Sens., 52(9). DOI: 10.1109/TGRS.2013.2278171.

[26]   Cheng X, Huang W, Gong J. (2014). Improved van Zyl Polarimetric Decomposition Lessening the Overestimation of Volume Scattering Power. Remote Sensing. 6(7): 6365-6385. DOI: 10.3390/rs6076365 

[27]   Cheng X.*, Huang W, Gong J. (2013). A decomposition-free scattering mechanism classification method for PolSAR images with Neumann’s model. Remote Sensing Letter, 4:1176-1184.
DOI:
10.1080/2150704X.2013.858840.

[28]   Dou A*, Ma Z, Huang W, Wang X, Yuan X. (2013). Automatic identification approach of building damages caused by earthquake based on airborne LiDAR and multispectral imagery. Remote Sensing Information (in Chinese). 2013, 28 (4): 103-109.

[29]   Ni W*, Sun G, Guo Z, Zhang Z, He Y, Huang W. (2013). Retrieval of Forest Biomass from ALOS PALSAR Data Using a Lookup Table Method. IEEE J. Sel. Topics Applied Earth Observation and Remote Sensing. 6(2): 875-886. DOI: 10.1109/JSTARS.2012.2212701.

[30]  Wang D*, Wan Y, Xiao J, Lai X, Huang W, Xu J. (2012). Aerial Image Mosaicking with the Aid of Vector Roads. Photogrammetry Engineering and Remote Sensing. 78 (11): 1141-1150. DOI: 10.14358/PERS.78.11.1141.


Book Chapters

 

[1]      Pang Y, Ni W, Li Z, Huang W, Chen E undefinedamp; Sun G, (2019). Chapter 13 - Vegetation Height and Vertical Structure. Quantitative Remote Sensing – Theory and Method (2nd edition, in Chinese). Beijing: Science Press in Liang et al. 2019, ISBN: 978-7-03-063977-6.

[2]      Sun G, Pang Y, Ni W, Huang W; Li Z, (2013). Chapter 14 - Vegetation Height and Vertical Structure. Quantitative Remote Sensing – Theory and Method (in Chinese). Beijing: Science Press in Liang et al. 2013, ISBN: 978-7-03-035700-7.

[3]      Sun G, Pang Y, Ni W, Huang W undefinedamp; Li Z. (2012). Chapter 14 - Vegetation Height and Vertical Structure. Advanced Remote Sensing (pp. 439-466). Boston: Academic Press in Liang et al. 2012, Advanced Remote sensing, Elsevier Inc. ISBN: 978-0-12-385954-9. DOI: 10.1016/B978-0-12-385954-9.00014-9.

 

Scientific Dataset

 

[4]      Hurtt GC, Zhao M, Sahajpal R, Armstrong A, Birdsey R, Campbell E, Dolan K, Dubayah R, Fisk J, Flanagan S, Huang C, Huang W, Johnson K, Lamb R, Ma L, Marks R, O'Leary III D, O'Neil-Dunne J, Swatantran A, and Tang H. (2019). CMS: Forest Aboveground Biomass and Carbon Sequestration Potential for Maryland, USA. ORNL DAAC, Oak Ridge, Tennessee, USA.
DOI:
10.3334/ORNLDAAC/1660.

[5]      Dubayah R, Swatantran A, Huang W*, Duncanson L, Johnson K, Tang H, O'Neil-Dunne J, undefinedamp; Hurtt G. (2018). CMS: LiDAR-derived Aboveground Biomass, Canopy Height and Cover for Tri-State (MD, PA, DE) Region V2. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1538.

[6]      Dubayah R, Swatantran, A., Huang W*, Duncanson L, Johnson K, Tang H, O'Neil-Dunne J, undefinedamp; Hurtt G. (2017). CMS: LiDAR-derived Aboveground Biomass, Canopy Height and Cover for Sonoma County, California 2013. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1523.

[7]      Dubayah R, Swatantran A, Huang W*, Duncanson L, Johnson K, Tang H, O'Neil-Dunne, J, undefinedamp; Hurtt G. (2016). CMS: LiDAR-derived Aboveground Biomass, Canopy Height and Cover for Maryland, 2011. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1320.

 

Conference Presentation and Proceedings

 

[1]      Min W, Huang W*, Ding J, Liu Y, Hu Y. (2021) Mapping of Forest Height in Northwest Hunan, China Using Multi-Source Satellite Data. IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium. (EI)

[2]      Chen S, Huang W*, Chen Y*. (2020). Automatic Extraction of Flood Coverage based on Dynamic Surface Water Extent and SAR Data. IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium. pp. 4746-4749, DOI: 10.1109/IGARSS39084.2020.9323267 (EI)

[3]      Huang W*, DeVries B, Huang C, Jones J, Lang M, undefinedamp; Creed I. (2017). Automated Extraction of Inland Surface Water Extent from Sentinel-1 data. IGARSS 2017 - 2017 IEEE International Geoscience and Remote Sensing Symposium. Fort Worth, Texas, USA. DOI: 10.1109/IGARSS.2017.8127439. (EI) 

[4]      Huang W*, Sun G, Zhang Z, undefinedamp; Ni W. (2013). Sensitivity of multi-source SAR backscatter to changes of forest aboveground biomass. IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2013 (pp. 2457-2460). DOI: 10.1109/IGARSS.2013.6723318. (EI).

[5]      Huang W*, Sun G, Dubayah R, Zhang Z, Ni W. (2012). Mapping Forest Above-ground Biomass and its Changes from LVIS Waveform Data. IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2012. DOI: 10.1109/igarss.2012.6352096. (EI).

[6]      Huang W*, Liu H, Bai M. (2009). Urban Expansion Simulation based on Constrained Artificial Neural Network Cellular Automata Model. Fairfax, VA, USA. Proc. of SPIE. Geoinformatics 2009. DOI: 10.1109/GEOINFORMATICS.2009.5293544. (EI).

[7]      Huang W*, Liu H, Luan Q, Jiang Q. (2008). Detection and Prediction of Land Use Change in Beijing Based on Remote Sensing and GIS. Beijing, China. Proc. of ISPRS, vol. XXXVII. Part B6b. Available online: [http://www.isprs.org/proceedings/XXXVII/congress/6b_pdf/13.pdf]

[8]      Huang W*, Liu H, Luan Q. (2007). Design and Construction of Spatial Decision Support System Database based on Metadata, Geoinformatics 2008. Proc of SPIE, Nanjing, China. (EI).

[9]      Huang W*, Dolan K, Johnson K, O'Neil Dunne J, Dubayah R, Hurtt G. (2016). High-Resolution Mapping of Aboveground Biomass for Forest Carbon Monitoring - A Case Study in Three Mid-Atlantic States, USA. San Francisco, CA, AGU 2016. Available from here.

[10]   Huang W*, Swatantran A, Hurtt G, Zhao M, Duncanson L, Tang H, Dubayah R. (2015). Local Discrepancies in Continental Scale Biomass Maps: A Case Study over Forested and Non-Forested Landscapes in Maryland, USA. San Francisco, CA, AGU 2015.

[11]   Huang W*, Sun, G., Dubayah R, Zhang Z, Ni W. (2014). Mapping Change of Forest Above-ground Biomass from Multi-source SAR Backscatter. Tampa, Florida, AAG 2014.

[12]   Huang W*, Sun G, Dubayah R, undefinedamp; Ni W. (2011). Forest Biomass Estimation from Small and Medium Footprint Airborne LiDAR. 2011 AAG Annual Meeting. Seattle, Washington.

[13]   Huang W*, Sun G. (2010). Forest Biomass Mapping Using Lidar-derived Canopy Height Metrics at Maine in USA. San Francisco, CA, AGU 2010.