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PUBLICATIONS Refereed Journal papers (* denotes advisee) *Xue, B. Guo, Q., Gong, Y., Hu, T., Liu, J., Ohta T., The influence of meteorology and phenology on net ecosystem exchange in an eastern Siberian boreal larch forest. Journal of Plant Ecology. (accepted) *Su Y., Ma Q., Guo Q., 2016. Fine-resolution forest tree height estimation across the Sierra Nevada through the integration of spaceborne LiDAR, airborne LiDAR and optical imagery. International Journal of Digital Earth. (In press) *Li Y., Guo Q., Tao S., Zheng G., Zhao K., Su Y., 2016. Derivation, validation, and sensitivity analysis of terrestrial laser scanning-based leaf area index. Canadian Journal of Remote Sensing. (In press) *Tao. S., Guo, Q., Li,C., Wang,Z., Fang, J. 2016 Global patterns and determinants of forest canopy height. Ecology. doi: 10.1002/ecy.1580. Guo, Q., Wu, F., Pang, S., Zhao, X., Chen, L., Liu, J., Xue, B., Xu, G., Li, L., Jing, H., Chu, C. 2016. Crop 3D:a platform based on LiDAR for 3D high-throughput crop phenotyping. Scientia Sinica Vitae. 46: 1–14, DOI: 10.1360/N052016-00009 (in Chinese). *Zhao X., Guo Q., Su Y., Xue B. 2016. Improved progressive TIN densification filtering algorithm for airborne LiDAR in forested areas. ISPRS Journal of Photogrammetry and Remote Sensing, 117, 79-91. *Tao, S., Guo, Q., Wu, F., Li, L., Wang, S., Tang, Z., Xue, B., Liu, J., Fang, J. 2016. Spatial scale and pattern dependences of aboveground biomass estimation from satellite images: a case study of the Sierra National Forest, California. Landscape Ecology. DOI: 10.1007/s10980-016-0357-y. *Hu T., Su Y., Xue B., Liu J., Zhao X., Fang J., Guo Q., 2016. Mapping global forest aboveground biomass with spaceborne LiDAR, optical imagery, and forest inventory data. Remote Sensing, 8, 565. *Su, Y, Guo Q, Xue B, Alvarez O, Tao S, Fang J. 2016. Spatial distribution of forest aboveground biomass in China: estimation through combination of spaceborne lidar, optical imagery, and forest inventory data. Remote Sensing of Environment. 173(2):187-199. Su, Y, Guo Q, Fry DL, Collins BM, Kelly M, Flanagan J, Battles J. 2016 A vegetation mapping strategy for conifer forests by combining airborne lidar data and aerial imagery, Canadian Journal of Remote Sensing 42: 1-15. Zapata-Rios, X., Brooks, P., Troch, P., McIntosh, J., Guo, Q., 2016. Influence of Terrain Aspect on Water Partitioning, Vegetation Structure, and Vegetation Greening in High Elevation Catchments in Northern New Mexico. Ecohydrology 9(5): 782 - 795. *Xue, B., Guo, Q., Otto, A., Xiao, J., Tao, S., Li, L., 2015. Global patterns, trends, and drivers of water use efficiency from 2000 to 2013. Ecosphere 6(10): 1 - 18. Tempel, D., Gutierrez, R.J., Battles, J., Fry, D., Su, Y., Guo, Q., Reetz, M., Whitmore, S., Jones, G., Collins, B., Stephens, S., Kelly, M., Berigan, W., Perry, Z. 2015. Evaluating Short- and Long-term Impacts of Fuels Treatments and Simulated Wildfire on an Old-forest Species. Ecosphere 6, 1–18. *Tao S., Fang J., Zhao X., Zhao S., Shen H., Hu H., Tang Z., Wang Z., Guo Q. 2015. Rapid loss of lakes on the Mongolian Plateau. Proc Natl Acad Sci USA 112:2281–2286. *Wan, B. Guo, Q., Fang, F., Su, Y., Wang, R. 2015. Mapping US Urban Extents from MODIS Data Using One-class Classification Method, Remote Sensing. 7(8), 10143-10163. *Tao, S., Guo, Q., Xu, S., Su, Y., Li, Y., Wu, F. 2015. A Geometric Method for Wood–Leaf Separation Using Terrestrial and Simulated LiDAR Data. Photogrammetric Engineering & Remote Sensing. 81: 767-776. Zhao, K., García, M., Liu, S., Guo, Q., Chen, G., Zhang, X., Zhou, Y., Meng, X. 2015. Terrestrial lidar remote sensing of forests: Maximum likelihood estimates of canopy profile, LAI, and leaf angle distribution. Agricultural and Forest Meteorolog. 209: 100-113. *Li, L., Guo, Q., Tao, S., Kelly, M., Xu, G., 2015. Lidar with multi-temporal MODIS provide a means to upscale predictions of forest biomass, ISPRS Journal of Photogrammetry and Remote Sensing. 102: 198 - 208. *Tao, S., Guo, Q., Li, L., Xue, B., Kelly, M., Li W., Xu, G., Su Y. 2014. Airborne Lidar-derived volume metrics for aboveground biomass estimation: a comparative assessment for conifer stands, Agricultural and Forest Meteorology. 198: 24–32 *Xue, B.-L., Li, Z., Yin, X.-A., Zhang, T., Iida, S., Otsuki, K., Ohta, T. and Guo, Q. 2014, Canopy conductance in a two-storey Siberian boreal larch forest, Russia. Hydrol. Process.. doi: 10.1002/hyp.10213. Kirchner, P. B., Bales, R. C., Molotch, N. P., Flanagan, J., and Guo, Q. 2014. LiDAR measurement of seasonal snow accumulation along an elevation gradient in the southern Sierra Nevada, California, Hydrol. Earth Syst. Sci., 11, 5327-5365, doi:10.5194/hessd-11-5327-2014. *Lu, X., Guo, Q., Li, W., Flanagan, J. 2014. A Bottom-Up Approach to Segment Individual Deciduous Trees Using Leaf-off Lidar Point Cloud Data, ISPRS Journal of Photogrammetry and Remote Sensing. 94: 1- 12. Harpold, A.A., Guo, Q., Molotch, N., Brooks, P., Bales, R., Fernandez-Diaz, J.C., Musselman, K.N., Swetnam, T.L., Kirchner, P., Meadows, M., Flanagan,J., Lucas, R. 2014. LiDAR-Derived Snowpack Datasets From Mixed Conifer Forests Across the Western U.S. Water Resources Research. 50, 2749 - 2755. *Doherty, P., Guo, Q., Li, W. Doke, J. 2014. Space-Time analyses for forecasting future incident occurrence: a case-study from Yosemite National Park using the presence and background learning algorithm, International Journal of Geographical Information Science. 5, 910-927. *Alvarez, O., Guo,Q., Klinger, R. Li, W., Doherty, P. 2014. Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation, International Journal of Climatology. 34: 2258 - 2268. *Li, W., Guo, Q. 2014. A new accuracy assessment method for one-class remote sensing classification, IEEE Transactions on Geoscience and Remote Sensing.52, 4621 – 4632. Zhou, Y., Chen, J., Guo,Q., Cao, R., Zhu, X. 2014. Restoration of Information Obscured by Mountainous Shadows through Landsat TM/ETM+ Images without the Use of DEM Data: A New Method. IEEE Trans. on Geoscience and Remote Sensing. 52, 313-328 . *Su, Y., Guo, Q. 2014. A Practical Method for SRTM DEM Correction over Vegetated Mountain Areas, ISPRS Journal of Photogrammetry and Remote Sensing. 87, 216-228. *Doherty, P., Guo, Q., Doke, J., Ferguson.D., 2014. An analysis of probability of area techniques for missing persons in Yosemite National Park. Applied Geography: 47: 99-110. *Li, W., Guo, Q. 2013. How to assess the prediction accuracy of species presence-absence models without absence data? Ecography. 36: 788–799. Berlow, E., Knapp, R., Ostoja, S., Williams, R., McKenny, H., Matchett, J., Guo, Q, Fellers, G., Kleeman, P., Brooks, M. . 2013, A Network Extension of Species Occupancy Models in a Patchy Environment Applied to the Yosemite Toad (Anaxyrus canorus),PloS one,8,8,e72200 Jakubowski, M.K., Li, W., Guo, Q., Kelly, M. 2013. Delineating Individual Trees from Lidar Data: A Comparison of Vector- and Raster-based Segmentation Approaches. Remote Sens. 5, 4163-4186. Jakubowski, M., Guo, Q., Kelly, M. 2013. Tradeoffs between lidar pulse density and forest measurement accuracy. Remote Sensing of Environment. 130: 245-253. Jakubowski, M., Guo., Q., Collins, B., Stephens, S., Kelly, M. 2013. Prediction of fuel models and stand structure metrics using lidar and optical remote sensing in dense mixed conifer forest. Photogrammetric Engineering & Remote Sensing. 79: 37–49. Cisneros, R., Schweizer, D., Zhong, S., Hammond, K., Perez, M., Guo, Q., Traina, S., Bytnerowicz, A., Bennett, D. 2012. Analysing the effects of the 2002 McNally fire on air quality in the San Joaquin Valley and southern Sierra Nevada, California. International Journal of Wildland Fire. 21: 1065-1075. *Doherty, P., Guo., Q., Alvarez, O. 2012. Expert versus machine: A comparison of two suitability models for emergency helicopter landing areas in Yosemite National Park. Professional Geographer. DOI:10.1080/00330124.2012.697857. Zhao, F., Sweitzer, R., Guo, Q., Kelly, M. 2012. Characterizing habitats associated with fisher den structures in southern Sierra Nevada forests using discrete return lidar. Forest Ecology and Management. 280: 112 – 119. Zhao, F., Guo., Q., Kelly, M. 2012. Allometric equation choice impacts lidar-based forest biomass estimates: A case study from the Sierra National Forest, CA. Agricultural and Forest Meteorology. 165: 64-72. *Fernandez, M., Hamilton, H., *Alvarez, O., Guo, Q. 2012. Does adding multi-scale climatic variability improve our capacity to explain niche transferability in invasive species? Ecological Modelling 246: 60 - 67. Guo, Q., Li, W., Liu, D., Chen, J. 2012. A framework for supervised image classification with incomplete training samples. Photogrammetric Engineering & Remote Sensing 78: 595 – 604. Liu, Y., Guo, Q., Tian, Y. 2012. A software framework for classification models of geographical data. Computers & Geosciences 42: 47–56. Rahilly, P., *Li, D., Guo, Q., Zhu, J., Ortega, R., Quinn, N., Harmon, T. 2012. Mapping swamp timothy (Crypsis schoenoides) seed productivity using spectral values and vegetation indices in managed wetlands, International Journal of Remote Sensing 33:4902-4918. *Li, W., Guo, Q., Jakubowski, M., Kelly, M. 2012. A New Method for Segmenting Individual Trees from the Lidar Point Cloud. Photogrammetric Engineering & Remote Sensing 78: 75 - 84. *Doherty, P., Guo., Q., Liu, Y., Wieczorek, J., Doke, J. 2011. Georeferencing incidents from locality descriptions and its applications: a case study from Yosemite National Park Search and Rescue. Transactions in GIS. 6:775 – 793. *Li, W., Guo, Q., Elkan, C. 2011. Can we model the probability of presence of species without absence data? Ecography DOI: 10.1111/j.1600-0587.2011.06888.x. Guo, Q., Li, W., Liu, Y., Tong, D. 2011. Predicting Potential Distributions of Geographic Events Using One-class Data: Concepts and Methods. International Journal of Geographical Information Science: DOI: 10.1080/13658816.2010.546360. *Li, D., Guo, Q., Rahilly, P., Phelps, G., Harmon, T. 2011. Correlation between soil apparent electroconductivity and plant hyperspectral reflectance in a managed wetland, International Journal of Remote Sensing 32: 2563 - 2579. *Zhu J., Guo, Q., Li, D., Harmon, T. 2011. Reducing mis-registration and shadow effects on change detection in wetlands. Photogrammetric Engineering & Remote Sensing 77: 325 - 334. *Li, W., Guo, Q., Elkan, C. 2011. A Positive and Unlabeled Learning Algorithm for One-Class Classification of Remote Sensing Data, IEEE Trans.on Geoscience and Remote Sensing 49: 717-725. (PDF) Xiao C., Tian Y, Shi W, Guo Q, Wu L. 2010. A new method of pseudo absence data generation in landslide susceptibility mapping with a case study of Shenzhen. Science China-Technological SCiences 54:75-84. Guo, Q., Li, W., Yu, H., Alvarez, O. 2010. Effects of Topographic Variability and Lidar Sampling Density on Several DEM Interpolation Methods. Photogrammetric Engineering and Remote Sensing. Vol. 76, No. 6, pp. 701–712. (PDF) Guo, Q., Liu, Y. 2010. ModEco: An integrated software package for ecological niche modeling. Ecography. 33: 637-642. doi: 10.1111/j.1600-0587.2010.06416.x. (PDF) *Li, W., Guo, Q. 2010. A Maximum Entropy Approach to One-Class Classification of Remote Sensing Imagery. International Journal of Remote Sensing. 31: 2227–2235. (PDF) de la Peña, S.,Nienow,P.,Shepherd, A.,Helm, V.,Mair,D.,Hanna, E.,Huybrechts, P.,Guo, Q.,Cullen, R., Wingham, D.. 2010. Spatially extensive estimates of annual accumulation in the dry snow zone of the Greenland Ice Sheet determined from radar altimetry. The Cryosphere, 4: 467-474, *Liu, Y., Guo, Q., Wieczorek, J., Goodchild, M. 2009. Positioning localities based on spatial assertions. International Journal of Geographical Information Science. 23:11, 1471-1501.(PDF) Bales, R., Guo, Q., Shen, D., McConnell, J., Du, G., Burkhart, J., Spikes, V., Hanna, E., Cappelen, 2009. J. Annual accumulation for Greenland updated using ice-core data developed during 2000-2006 and analysis of daily coastal meteorological data. Journal of Geophysical Research - Atmospheres. VOL. 114, D06116, doi:10.1029/2008JD011208. (PDF) *Fernandez, M., Blum, S., Reichle, S., Guo, Q., Holzman, B., Hamilton, H., 2009. Locality Uncertainty and the Differential Performance of Four Common Niche-based Modeling Techniques. Biodiversity Informatics, 6: 36-52. (PDF) Guo, Q., Liu, Y., Wieczorek, J. 2008. Georeferencing Locality Descriptions and Computing Associated Uncertainty Using a Probabilistic Approach. International Journal of Geographical Information Science 22:1067-1090. (PDF) ( top 10 most cited articles in 2006-2010 from IJGIS) *Liu, Y., Guo, Q., Kelly, M. 2008. A framework of region-based spatial relations for non-overlapping features and its application in object based image analysis. ISPRS Journal of Photogrammetry and Remote Sensing 63:461-474. (PDF) *Liu, Y., Goodchild, M., Guo, Q., Tian, Y., Wu, L. 2008 Towards a General Field model and its order in GIS. International Journal of Geographical Information Science 6: 623-643. (PDF) Liu, D., Kelly, M., Gong, P., Guo, Q. 2007. Characterizing Spatial-temporal Tree Mortality Patterns Associated with A New Forest Disease. Forest Ecology and Management. 253: 220-231.(PDF) Kelly, M., Guo, Q., Liu, D., Shaari, D. 2007. Modeling the risk of a new invasive forest disease in the United Sates: an evaluation of five environmental niche models. Computer, Environment and Urban System. 31: 689 - 710. (PDF) Guo, Q., Kelly, M., Gong, P., Liu, D. 2007. An object-based classification approach in mapping tree mortality using high spatial resolution imagery. GIScience; Remote Sensing. 44: 24 - 47. (PDF) Kim, J., Guo, Q., Baldocchi, D., Xu, L., Leclerc, M. 2006. Upscaling CO2 fluxes from tower to landscape: overlaying tower flux footprint calculations on high resolution (IKONOS) vegetation density images. Agricultural and Forest Meteorology. 136: 132 - 146. (PDF) Liu D., P. Gong, M. Kelly, Q. Guo, 2006. Automatic registration of airborne images by combining area-based methods with local transformation models. Photogrammetric Engineering and Remote Sensing. 72: 1049 - 1059 (PDF). Guo, Q., Kelly, M., Graham, C. 2005. Support vector machines for predicting distribution of Sudden Oak Death in California Ecological Modelling. 182:75-90. (PDF) Guo, Q., Kelly, M. 2004. Interpretation of scale in paired quadrat variance methods. Journal of Vegetation Science. 15: 763-770. (PDF) Wieczorek,J., Guo, Q., Hijmans, R. 2004. The Point-Radius method for georeferencing locality and calculating associated uncertainty. International Journal of Geographical Information Science. 18: 745-767. (PDF)( top 10 most cited articles of the last decade in IJGIS) Kelly, M., Sharri, D., Guo, Q., Liu, D. 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: 1229-1239. (PDF) Piao, S., Fang, J., Ji, W., Guo, Q., Ke, J., Tao, S. 2004. Variation in a satellite-based vegetation index in relation to climate in China. Journal of Vegetation Science. 15: 219-226. (PDF) Fang, J., Piao, S., Field, C., Pan, Y., Guo, Q., et. al. 2003. Increasing net primary production in China from 1982 to 1999. Frontiers in Ecology and the Environment. 1: 293-297. (PDF) Piao, S., Fang, J., Zhou, L., Guo, Q., et. al. 2003. Interannual variation of monthly and seasonal normalized difference vegetation index (NDVI) in China from 1982 to 1999. Journal of Geophysical Research. 108(D14), 10.1029/2002JD002848. (PDF) Piao, S., Fang, J., Guo, Q. 2001. Terrestrial net primary production and its spatio-temporal patterns in China during 1982 - 999. Acta Scientiarum Naturalium Universitatis Pekinensis (in Chinese). 37: 536-569. Piao, S., Fang, J., Guo, Q. 2001. Estimation of net primary production in China Acta Phytoecologica Sinica (in Chinese). 25: 603-609. Zeng, H. Yu, H., Guo, Q. 2000. Simulation
of urban growth based on a Cellular Automata model in Guo, Q., Yu, H., Cao, Y., Zhang, Z. 1999. The remote sensing study on the characteristics of Forest-Steppe Ecotone. Univesitatis Pekinensis (in Chinese). 35: 550-557. Fang, J. Guo, Q., Liu, G. 1999. Distribution pattern of Chinese Beech
(Fagus L.) species in relation to topology. Acta Botanica Sinica (in Chinese). 41: 766-774. Zeng, H., Guo, Q., Yu, H. 1999.
Spatial analysis of landscape human transforming in Zeng, H., Shao, N., Guo, Q.
1999. A Study of landscape heterogeneity in the Eastern Pearl River
Delta. Acta Geographica Sinica (in
Chinese). 54: 255-262. Zeng, H., Tan, J., Guo, Q.
1999. Landscape change in Eastern Pearl River Delta: a case study of Zeng, H., Guo, Q., Liu, X. 1998. Effects of spatial resolution on landscape pattern: a case study of Eastern Pearl River Delta. Univesitatis Pekinensis (in Chinese). 34: 820-826. Zeng, H., Tan, J., Guo, Q. 1998. A landscape study of element transferring
pattern and changing of Zeng, H., Guo, Q., Liu, J. 1997. Analyses of landscape ecological-changing
characteristics of Conference Papers and Abstracts Kelly, M., Guo, Q., Allen-Diaze, B. Mapping the historic range of Quercus species in California using one-class Support Vector Machines and BIOCLIM models, San Francisco, April, 2007. Guo, Q., Liu, Y., Kelly, M. From land cover to land use mapping: an
object-based perspective. ASPRS Annual Conference, Guo, Q., Liu, Y, Kelly, M. Use of object based classification methods in
land use mapping. AAG Annual Meeting, Kelly, M., Shaari, Q., Guo, Q., Liu, D. 2005. Modelling risk for SOD nationwide: what are the effects of model choice on risk predictions? Forthcoming in the proceedings of the second Sudden Oak Death Science Symposium. January 18 - 21, 2005. Kim, J., Guo, Q., Baldocchi, D., Xu, L., Leclerc, M., Schmid, H. P.
Upscaling fluxes from tower to landscape: Overlaying flux footprints on high
resolution (IKONOS) images of vegetation cover. The 26th Conference on
Agricultural and Forest Meteorology, Guo, Q., Kelly, M. An object-based classification method in detecting
Sudden Oak Death. The 100th AAG Annual Meeting, Kelly, M., Guo, Q. Shaari, D., Liu, D. Classification of 1-m ADAR imagery
for mapping hardwood mortality. The 100th AAG Annual Meeting, Guo, Q., Kelly, M., Graham, C. 2003. Predicting distribution of a new forest disease using one-class SVMs. Proceedings of the Third IEEE International Conference on Data Mining, 719-722. Guo, Q., Wei, L. Qi, Y. Comparing semivariogram with Ripley’s K for
point pattern analysis. The 16th Annual Symposium of the Xu. M., Guo, Q., Qi, Y. Application of high-resolution remote sensing to
detect soil temperature and soil respiration. The 16th Annual Symposium of
the Guo, Q., Qi, Y., Xu, M. The relationship between temperature,
precipitation and NDVI in Xu, M., Qi, Y., Debiase, T., Guo, Q., Tang, J, Henderson, M. Soil CO2
Efflux in a Young Ponderosa Pine Zeng, H., Guo, Q., Yu, H. A study of landscape changing in Shenzhen area.
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