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郭庆华


职务/职称: 研究员
联系电话: 010-62836157
电子邮件: qguo@ibcas.ac.cn
个人网页: http://www.3decology.org/
课 题 组: 数字生态系统研究组

郭庆华,男,博士,研究员,国科大岗位教授,博士生导师。

北京大学获得学士和硕士学位;美国加州大学伯克利分校获得博士学位;回国前系加州大学默塞德分校环境工程学院创始教授;2012年创建中国科学院植物研究所数字生态研究组,现任美国内华达研究所兼职教授,中科院无人机管控中心副主任,中科院植物所植被与环境变化国家重点实验室学术委员会副主任。

在林学、生态学、地理信息及遥感科学的主流期刊Forest Ecol. Manag.Agric. For. Meteorol.EcologyRemote Sens. Environ.Global Biogeochem. Cy.J. Geophys. Res.等发表SCI论文90篇,发表在地理信息科学顶级刊物Int. J. Geogr. Inf. Sci.2篇论文分别入选该杂志2005~2010年间和近十年间引用前十名文章之列。撰写的激光雷达点云单木分割算法系列文章分别获评美国摄影测量学会“Talbert Abrams”奖(授予在摄影测量学中具有重大科学突破的研究)和“ERDAS最佳学术论文”奖,相关研究成果被美国自然科学基金会评为重要研究突破(Breaking News),同时被国内外多家知名媒体(如科学美国人、Science 360EurekAlert新闻中心、The New York TimesABC News、新华网、中科院之声等)先后报道。

出版专著《激光雷达森林生态应用——理论、方法及实例》一部,全书逾50万字,插图150幅,共351页。相关成果授权专利3项、软件著作权3项。

已培养多名硕士和博士,研究生多次获得国内外奖项,如“国家奖学金”、“北京大学校长奖”、“国家优秀自费留学生奖学金”、“美国地理学会最佳论文奖”、“美国自然科学基金论文奖”等,有两名博士生分别入选中山大学“百人计划”和中科院“百人计划”。

现为国际遥感SCI期刊Remote Sensing编委会成员,林学SCI期刊Forests特邀主编,组织出版“利用激光雷达进行森林植被资源制图”专辑;曾任或现任美国 NSFNASAUSDA 等机构的大会评审专家,及Ecology, Int. J. Geogr. Inf. Sci.,Remote Sens. Environ., Ecography, Glob. Change Biol.等国际刊物的审稿人。作为第一负责人和共同负责人主持完成多项美国自然科学基金会、联邦地质调查局、联邦森林局、联邦国家公园管理局、加州水利局、摩尔基金会等项目。

主要研究工作: 

主要从事遥感和地理信息系统方法及其在生态环境中的应用研究,目前研究工作主要围绕以下4个方向开展:

1)激光雷达技术在森林,农业,以及城市的应用;

2)物种分布模型算法研究(地理一类数据)及其在生物多样性方面的应用;

3)基于卫星遥感和海量地面数据的新一代植被图绘制研究

4)在区域、全球尺度上应用多源遥感数据结合生态模型,模拟和预测气候变化和土地利用 变化对陆地生态系统结构、功能(如碳循环,生物多样性等)的影响。

欢迎具有遥感和地理信息系统、数学、地理和生态学或计算机科学背景的学生联系报考硕士和博士!

主持和参加的科研项目: 

“植被遥感与生物多样性变化”,中国科学院战略性先导科技专项(A类),2018.01-2022.12,课题负责人

“示范区资源清查”,中科院科技服务网络计划(KFJ-STS-ZDTP-004),2017.01-2018.06,课题负责人

“基于地面观测与近地面遥感数据融合的生态系统评估参照系数据集构建”,国家重点研发计划(2016YFC0500202,2016/072020/12),课题负责人.

“森林群落精细结构提取及其内在规律研究”,中国科学院前沿科学重点研究项目(QYZDY-SSW-SMC011-12016/082020/12),课题负责人

“基于地面激光雷达的森林结构参数提取和真实景观三维建模整合性研究 , 国家自然科学基金面上项目( 41471363; 2015-2018 ), 课题负责人.

“全自动、高分辨率、高通量植物真三维影像分析系统(Plant 3D)”, 中国科学院科研装备 研制项目(条财字〔2014129 ;2015-2016 ), 课题负责人.

作物全生育期通量化无损表型分析技术研发 , 中国科学院战略性科技先导专项 (A ) ( XDA08040107; 20132017 ), 子课题负责人.

“碳循环——气候变化回馈作用及地球系统敏感性 ,国家重点基础研究发展计划 (973 计划) ( 2013CB956604; 20132017 ), 专题负责人.

“全球气候变化下物种分布模型的不确定性研究”, 国家自然科学基金面上项目 ( 31270563; 20122016 ), 项目主持人.

研究论文:(注*号为通讯作者)  

2018

Jin, S., Su, Y., Gao, S., Wu, F., Hu, T., Liu, J., Li, W., Wang, D., Chen, S., Jiang, Y., Pang, S., Guo, Q*. 2018. Deep Learning: Individual maize segmentation from terrestrial Lidar data using Faster R-CNN and regional growth algorithms. Frontiers in Plant Science. (accepted)

Li, Y., Su, Y., Hu, T., Xu, G, Guo, Q*. 2018. Retrieving two-dimensional leaf angle distributions from a terrestrial laser scanner data. IEEE Transactions on Geoscience and Remote Sensing. (accepted)

Zhao, X., Su Y., Li, W., Hu, T., Liu, J., Guo, Q*. 2018.A comparison of LiDAR filtering algorithms in vegetated mountain areas. Canadian Journal of Remote Sensing. (Accepted)

Luo, L., Zhai, Q., Su, Y., Ma, Q., Kelly, M., Guo., Q. 2018. A simple method for direct crown base height estimation of individual conifer trees using airborne LiDAR data. Optics Express. DOI: org/10.1364/OE.26.00A562.

Wang, D, Wan, B, Qiu, P, Su, Y, Guo, Q, Wu, X. 2018. Artificial mangrove species mapping using Pléiades-1: An evaluation of pixel-based and object-based classifications with selected machine learning algorithms. Remote Sensing. (Accepted).

Li, W., Guo, Q., Tao, S., Su, Y. 2018. VBRT: a novel voxel-based radiative transfer model for heterogeneous three-dimensional forest scenes. Remote Sensing of Environment. (Accepted).

Liu, R., Li, W., Liu, X., Lu, X., Li, T., Guo, Q. 2018. An ensemble of classifiers based on positive and unlabeled data inone-class remote sensing classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. (Accepted).

Deng, X., Li, W., Liu, X., Guo, Q. 2018. Newsam, S., One-class remote sensing classification: one-class vs. binary classifiers. International Journal of Remote Sensing. (Accepted).

Zhao, X., Su, Y., Hu, T., Chen, L., Gao, S., Wang, R., Jin, S., Guo, Q.*, 2018. A global corrected SRTM DEM product over vegetated areas. Remote Sensing Letters. 9(4): 393-402.

2017

Su, Y., Bales, R., Ma, Q., Nydick, K., Ray, R., Li, W., Guo, Q.*, 2017. Emerging stress and relative resiliency of Giant Sequoia groves experiencing multi-year dry periods in a warming climate. Journal of Geophysical Research: Biogeosciences. 122(11): 3063-3075.

Kelly, M., Su, Y., Tommaso, S., Collins, B., Fry, D., Sephens, S., Guo, Q. 2017. Impact of error in Lidar-derived canopy height and canopy base height on modeled wildfire behavior. Remote Sensing. 10 (1) :10.

Ao, Z., Su Y., Li, W., Guo, Q.*, Zhang, J. 2017. One-Class classification of airborne LiDAR data in urban areas using a resence and background learning algorithm. Remote Sensing. 2017, 9(10): 1-15.

Li, Y., Guo, Q.*, Su, Y., Tao, S., Zhao K., Xu, G. 2017. Retrieving the gap fraction, element clumping index, and leaf area index of individual trees using single-scan data from a terrestrial laser scanner. ISPRS Journal of Photogrammetry and Remote Sensing.130: 308-316.

Wang, R., Wan, B., Guo, Q., 2017. Hu, M., Zhou, S., Mapping regional urban extent using NPP-VIIRS DNB and MODIS NDVI data. Remot Sensing. 9(8): 862.

Ma, Q., Su, Y., Tao, S., Guo, Q.*, 2017. Quantifying individual tree growth and tree competition using bi-temporal ALS data: a case study in the Sierra Nevada mountains, California. International Journal of Digital Earth. 2017, 1(1): 1-19.

Ma, Q., Su, Y., Guo, Q.* 2017. Comparison of canopy cover estimations from airbornelidar, aerial imagery, and satellite imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 109: 4225-4326.

Guo, Q.*, Wu, F., Pang, S., Zhao, X., Chen, L., Liu, J., Xue, B., Xu, G., Li, L., Jing, H., and Chu, C. 2017. Crop 3Da LiDAR based platform for 3D high-throughput crop phenotyping. Science China Life Sciences. 60, DOI: 10.1007/s11427-017-9056-0.

Zhu, J., Su, Y., Guo, Q.*, Harmon, T., 2017. Unsupervised object-based differencing for land-cover change detection. Photogrammetric Engineering and Remote Sensing. 83(3): 225-236.

Xue, B., Guo, Q.*, Hu, T., Xiao, J., Yang, Y., Wang, G., Tao, S., Su, Y., Liu, J. and Zhao, X. 2017. Global patterns of woody residence time and its influence on model simulation of aboveground biomass. Global Biogeochemical Cycles. 31(5): 821-835.

Xue, B., Guo, Q.*, Hu, T., Wang, G., Wang, Y., Tao S., Su, Y., Liu, J. and Zhao, X. 2017. Evaluation of modeled global vegetation carbon dynamics: analysis based on global carbon flux and above-ground biomass data. Ecological Modelling. 3584-96

Guo, Q.*, Su Y., Hu, T., Zhao, X., Wu, F., Li, Y., Liu, J., Chen, L., Xu, G., Lin, G., Zheng, Y., Lin, Y., Mi, X., Fei, L., Wang X. 2017. An integrated UAV-borne lidar system for 3D habitat mapping in three forest ecosystems across China. International Journal of Remote Sensing. 388-10: 2954-2972.

2016

Su Y., Ma Q., Guo Q. *, Kean J.J., Gerrard R., Gallagher C. V. 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. 10(3): 307-323

Li, Y., Guo, Q. *, Tao, S., Zheng, G., Zhao, K., Xue, B., Su, Y. 2016. Derivation, validation, and sensitivity analysis of terrestrial laser scanning-based leaf area index. Canadian Journal of Remote Sensing. 42(6): 719-729

郭庆华*, 吴芳芳, 胡天宇, 陈琳海, 刘瑾, 赵晓倩, 高上, 庞树鑫. 2016.无人机在生物多样性遥感监测中的应用现状与展望,生物多样性, 24(11):1267-1278.

郭庆华*, 刘瑾, 李玉美, 翟秋萍, 王永财, 吴芳芳, 胡天宇, 万华伟, 刘慧明, 申文明. 2016. 生物多样性近地面遥感监测中的应用现状与展望. 生物多样性. 24(11): 1-20.

郭庆华*, 吴芳芳, 庞树鑫, 赵晓倩, 陈琳海, 刘瑾, 薛宝林, 徐光彩, 李乐, 景海春, 储成才. 2016. Crop 3D—基于激光雷达技术的作物高通量三维表型测量平台. 中国科学:生命科学. 46(10):1210 -1221.

Tao, S., Guo, Q.,Li, C., Wang, Z., Fang, J. 2016. Global patterns and determinants of forest canopy height.

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. 31(8): 1711-1723.

Xue, B., Guo, Q.*, Gong, Y., Hu, T., Liu, J., Ohta T. 2016. The influence of meteorology and phenology on net ecosystem exchange in an eastern Siberian boreal larch forest. Journal of Plant Ecology. 9(5): 520-530.

Su, Y., Guo, Q.*, Collins, B., Fry, D., Kelly, M. 2016. Forest fuel treatment detection using multi-temporal airborne LiDAR data and high-resolution aerial imagery - A case study at Sierra Nevada Mountains, California. International Journal of Remote Sensing. 37(14), 3322-3345.

Su, Y., Guo, Q.*, Fry, D. L., Collins, B. M., 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): 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.

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(7): 1-27.

Su, Y., Guo, Q., Xue, B., Hu, T., 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.

Zhao, X., Guo, Q. *, Su, Y., Xue, B. 2016. Improved progressive TIN densification filtering algorithm for airborne LiDAR data in forested areas. ISPRS Journal of Photogrammetry and Remote Sensing. 117(7): 79-91.

2015

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.

Xue, B., Li, Z., Yin, X., Zhang, T., Iida, S., Otsuki, K., Ohta, T., Guo, Q. * 2015. Canopy conductance in a two-storey Siberian boreal larch forest, Russia. Hydrological Processes. 29(6): 1017-1026.

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(12): 1-19.

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.

Su, Y., Guo, Q. *, Ma, Q., Li, W. 2015. SRTM DEM correction in vegetated mountain areas through the integration of spaceborne LiDAR, airborne LiDAR, and optical imagery. Remote Sensing. 7(9): 11202-11225.

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. Proceedings of the National Academy of Sciences of the United States of America. 112(7): 2281-2286.

Tao, S., Guo, Q. *, Xu, S., Su, Y., Li, Y., Wu, F. 2015. A geometric method for woodleaf separation using terrestrial and simulated Lidar data. Photogrammetric Engineering and Remote Sensing. 81(10): 767-776.

Tao, S., Wu, F., Guo, Q. *, Wang, Y., Li, W., Xue, B., Hu, X., Li, P., Tian, D., Li, C., Yao, H., Li, Y., Xu, G., Fang, J. 2015. Segmenting tree crowns from terrestrial and mobile LiDAR data by exploring ecological theories. ISPRS Journal of Photogrammetry and Remote Sensing. 110(12): 66-76.

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 Meteorology. 209(9): 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(4): 198-208.

2014

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(7): 2258-2268.

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. 28(5): 910-927.

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(1): 99-110.

郭庆华*, 刘瑾, 陶胜利, 薛宝林, 李乐, 徐光彩, 李文楷, 吴芳芳, 李玉美, 陈琳海, 庞树鑫. 2014. 激光雷达在森林生态系统监测模拟中的应用现状与展望. 科学通报. 59(6), 459-478.

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(3): 2749-2755.

Kirchner, P. B., Bales, R. C., Molotch, N. P., Flanagan, J., Guo, Q. 2014. LiDAR measurement of seasonal snow accumulation along an elevation gradient in the southern Sierra Nevada, California. Hydrology and Earth System Sciences. 18(18): 4261-4275.

Li, W., Guo, Q. * 2014. A new accuracy assessment method for one-class remote sensing classification. IEEE Transactions on Geoscience and Remote Sensing. 52(8): 4621-4632.

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(8): 1-12.

Su, Y., Guo, Q. *2014. A practical method for SRTM DEM correction over vegetated mountain areas. ISPRS Journal of Photogrammetry and Remote Sensing. 87(1): 216-228.

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(12): 24-32.

Xu, S., Yang, S., Sun, F., Guo, Q. 2014. Method research on cultivated land extraction based on object one-class classification of high-spatial-resolution images. Bulletin of Surveying and Mapping. (10): 78-81 (in Chinese).

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 Transactions on Geoscience and Remote Sensing. 52(1): 313-328.

2013

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 Sensing. 5(9): 4163-4186.

Li, W., Guo, Q.* 2013. How to assess the prediction accuracy of species presence-absence models without absence data? Ecography. 36(7): 788-799.

Jakubowski, M., Guo, Q., Kelly, M. 2013. Tradeoffs between Lidar pulse density and forest measurement accuracy. Remote Sensing of Environment. 130(3): 245-253.

Jakubowski, M., Guo, Q., Collins, B., Stephens, S., Kelly, M. 2013. Predicting surface fuel models and fuel metrics using Lidar and CIR imagery in a dense, mountainous forest. Photogrammetric Engineering and Remote Sensing. 79(1): 37-49.

2012

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(8): 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. 65(30): 466-481.

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(1747): 60-67.

Guo, Q. *, Li, W., Liu, D., Chen, J. 2012. A framework for supervised image classification with incomplete training samples. Photogrammetric Engineering and Remote Sensing. 78(6): 595-604.

Liu, Y., Guo, Q., Tian, Y. 2012. A software framework for classification models of geographical data. Computers & Geosciences. 42(3): 47-56.

Li, W., Guo, Q. *, Kelly, M., Jakubowski, M. 2012. A new method for segmenting individual trees from the Lidar point cloud. Photogrammetric Engineering and Remote Sensing. 78(1): 75-84.

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(16): 4902-4918.

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(9): 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(6): 64-72.

祝锦霞, 郭庆华, 王珂. 2012. 湿地高分辨率遥感影像的变化检测. 中国农业科学, 45(21), 4369-4376.

2011

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. 15(6): 775-793.

Li, W., Guo, Q.*, Elkan, C. 2011. Can we model the probability of presence of species without absence data? Ecography. 34(6): 1096-1105.

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. 25(10): 1697-1715.

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(9): 2563-2579.

Zhu, J., Guo, Q.*, Harmon, T. 2011. Reducing mis-registration and shadow effects on change detection in wetlands. Photogrammetric Engineering and Remote Sensing. 77(4): 325-334.

Li, W., Guo, Q.*, Elkan, C. 2011. A positive and unlabeled Learning algorithm for one-class classification of remote sensing data. IEEE Transactions on Geoscience and Remote Sensing. 49(2): 717-725.

  2010年及以前

Guo, Q.*, Liu, Y. 2010. ModEco: An integrated software package for ecological niche modeling. Ecography. 33(4): 637-642.

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. 53(3): 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. 76(6): 701-712.

Li, W., Guo, Q.* 2010. A maximum entropy approach to one-class classification of remote sensing imagery. International Journal of Remote Sensing. 31(8), 2227-2235.

Bales, R., Guo, Q., Shen, D., McConnell, J., Du, G., Burkhart, J., Spikes, V., Hanna, E., Cappelen, J. 2009. Annual accumulation for Greenland updated using ice-core data developed during 20002006 and analysis of daily coastal meteorological data. Journal of Geophysical Research-Atmospheres. 114(3): 1-14.

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.

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.

Guo, Q.*, Liu, Y., Wieczorek, J. 2008. Georeferencing locality descriptions and computing associated uncertainty using a probabilistic approach. International Journal of Geographic Information Science. 22(10): 1067-1090. (One of the top 10 most cited papers in IJGIS in the past 5 years).

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(4): 461-475.

Liu, Y., Goodchild, M., Guo, Q., Tian, Y., Wu, L. 2008. Towards a general field model and its order in GIS. International Journal of Geographic Information Science. 22(6): 623-643.

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(1-3): 220-231.

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(7): 689-710.

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(1): 24-47.

Liu, D., Gong. P, Kelly, M, Guo, Q. 2006. Automatic registration of airborn images by combining area-based methods with local transformation models. Photogrammetric Engineeering and Remote Sensing. 72(9): 1049-1059.

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(2006): 132-146.

Guo, Q., Kelly, M., Graham, C. 2005. Support vector machines for predicting distribution of Sudden Oak Death in California. Ecological Modeling. 182(1): 75-90.

Guo, Q., Kelly, M. 2004. Interpretation of scale in paired quadrat variance methods. Journal of Vegetation Science. 15(2): 763-770.

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(8): 745-767 (One of the top 10 most cited papers in IJGIS in the past decade).

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(11): 1229-1239.

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(2): 219-226.

Fang, J., Piao, S., Field, C., Pan, Y., Guo, Q., Zhou, L., Peng, C., Tao, S. 2003. Increasing net primary production in China from 1982 to 1999. Frontiers in Ecology and the Environment. 1(6): 293-297.

Piao, S., Fang, J., Zhou, L., Guo, Q., Mark, H., Wei, J., Yan, L., Shu, T. 2003. Interannual variation of monthly and seasonal normalized difference vegetation index (NDVI) in China from 1982 to 1999. Journal of Geophysical Research. 108(D14), 4401.

朴世龙, 方精云, 郭庆华. 2001. 利用CASA模型估算我国植被净第一性生产力植物生态学报, 25(5), 603-608+644.

朴世龙, 方精云, 郭庆华. 2001. 1982-1999年我国植被净第一性生产力及其时空变化. 北京大学学报(自然科学版), 37(4), 563-569.

曾辉, 喻红, 郭庆华. 2000. 深圳市龙华地区城镇用地动态模型建设及模拟研究. 生态学报, 20(4), 545-551.

郭庆华, 喻红, 曹艳丽, 张泽浦. 1999. 北方森林草原生态过渡带的遥感研究. 北京大学学报(自然科学版) , 35(4), 550-557.

方精云, 郭庆华, 刘国华. 1999. 我国水青冈属植物的地理分布格局及其与地形的关系. 植物学报, 41(7), 766-774.

曾辉, 郭庆华, 喻红. 1999. 东莞市风岗镇景观人工改造活动的空间分析. 生态学报, 19(3), 298-303.

曾辉, 邵楠, 郭庆华. 1999. 珠江三角洲东部常平地区景观异质性研究. 地理学报, 54(3), 253-262 .

曾辉, 唐江, 郭庆华. 1999. 珠江三角洲东部地区常平镇景观组分转移模式及动态变化研究. 地理科学, 19(1), 73-77.

曾辉, 郭庆华, 刘晓东. 1998. 景观格局空间分辨率效应的实验研究──以珠江三角洲东部地区为例. 北京大学学报(自然科学版), 34(6), 820-826.

曾辉, 唐江, 郭庆华. 1998. 珠江三角洲东部地区小城镇景观动态变化研究──以东莞市常平镇为例. 应用基础与工程科学学报, 6(2), 21-29.

曾辉, 郭庆华, 刘静艳. 1997. 东莞市景观生态演化特征的分析. 中国环境科学, 17(5), 422-425.


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