个人简况:
许剑辉，博士，现任广州地理研究所遥感与GIS研究部副研究员。2007年于武汉理工大学获地理信息系统学士学位，2011年于汕头大学获防灾减灾与防护工程硕士学位，2015年于武汉大学测绘遥感信息工程国家重点实验室获摄影测量与遥感博士学位。近年来主要从事基于机器学习与地统计学理论的时空数据统计分析与多源数据融合、遥感数据质量评价、城市遥感、陆面过程模拟与数据同化等方面的研究，主持及参与国家和地方科技项目20多项，发表中英文论文50余篇，SCI论文30余篇，获得授权发明专利6项，获得软件著作权3项。
研究领域与研究方向:
遥感数据降尺度与多源数据融合；时空统计分析；陆面过程模拟与数据同化；城市不透水面提取及其环境效应
近年主持/参与的科研项目:
[1]国家自然科学基金“基于FY-3C热红外和被动微波遥感的高分辨率地表温度融合方法研究”，2020.1-2022.12，主持。
[2]南方海洋科学与工程广东省实验室（广州）人才团队引进重大专项-子课题“大湾区不透水面规模及其热环境效应”，粤2019.9-2022.8，主持。
[3]广东省科技计划项目“广东省气象大数据科技协同创新中心”子课题“多源气象大数据要素融合”，2019.1-2021.12，主持。
[4]广东省引进“珠江人才计划”地理空间智能与大数据创新创业团队项目子课题“多源遥感数据质量评价和多源异构时空信息融合方法研究”，2017.1-2021.12，主持。
[5]广东省科学院实施创新驱动发展能力建设专项资金项目“结合地统计学与多源遥感数据时空融合的高时空分辨率城市地表温度反演研究”，2017.1-2018.12，主持。
[6]广东科技计划项目“基于GIS和SWAT水文模型的农业干旱实时监测与评价系统”，2016.1-2017.12，主持。
[7]国家自然科学基金“时空交互的统计建模”，2012.1-2015.12，主要参与。
[8]国家重点基础研究发展计划（973计划）项目“对地观测传感网一体化数据融合与同化方法”，2011.1-2015.12，参与。
主要成果:
发表论文
[1] Xu J, Zhao Y, Sun C*, Liang H, Yang J, Zhong K, Li Y, Liu X. Exploring the Variation Trend of Urban Expansion, Land Surface Temperature, and Ecological Quality and Their Interrelationships in Guangzhou, China, from 1987 to 2019. Remote Sens. 2021, 13, 1019.
[2]Xu J, Zhang F*, Ruan H, Hu H, Liu Y, Zhong K, Jing W, Yang Ji, Liu X. High-resolution urban brightness temperature determination by hybrid modeling of random forest and Kriging with Sentinel-2A multispectral imagery [J]. International Journal of Remote Sensing, 2021, 42(6): 2174-2202
[3]Xu J, Zhang F, Jiang H*, Hu H, Zhong K, Jing W, Yang J, Jia B. Downscaling Aster Land Surface Temperature over Urban Areas with Machine Learning-Based Area-To-Point Regression Kriging , Remote Sensing, 2020, 12(7): 0-1082.
[4]Xu J, Zhao Y, Zhong K, Zhang F, Liu X, Sun C. Measuring spatio-temporal dynamics of impervious surface in Guangzhou, China, from1988 to 2015, using time-series Landsat imagery [J]. Science of the Total Environment, 2018, 627, 264-281.
[5] Jiang H, Li D, Jing W, Xu J*, Huang J, Yang J, Chen S. Early Season Mapping of Sugarcane by Applying Machine Learning Algorithms to Sentinel-1A/2 Time Series Data: A Case Study in Zhanjiang City, China [J]. Remote Sensing, 2019, 11, 861.
[6] Hu H, Hu Z, Zhong K, Xu J*, Zhang F, Zhao Y, Wu P. Satellite-based high-resolution mapping of ground-level PM2.5 concentrations over East China using a spatiotemporal regression kriging model [J]. Science of the Total Environment, 2019, 672, 479-490.
[7] Liu Y, Zhang P, Nie L, Xu J*, Lu X, Li S. Exploration of the Snow Ablation Process in the Semiarid Region in China by Combining Site-Based Measurements and the Utah Energy Balance Model—A Case Study of the Manas River Basin[J]. Water, 2019, 11, 1058.
[8] Zhao Y, Zhong K, Xu J, Sun C, Wang Y. Directional Analysis of Urban Expansion Based on Sub-pixel and Regional Scale: A Case Study of Main Districts in Guangzhou, China[J]. Chinese Geographical Science, 2019.
[9] Xu R, Liu J, Xu J. Extraction of High-Precision Urban Impervious Surfaces from Sentinel-2 Multispectral Imagery via Modified Linear Spectral Mixture Analysis[J]. Sensors, 2018, 18(9).
[10] Liu X, Deng R, Xu J, Zhang F. Coupling the modified linear spectral mixture analysis and pixel-swapping methods for improving subpixel water mapping: application to the Pearl River Delta, China[J]. Water, 2017, 9(9):658.
[11] Jiang H, Shu H, Lei L, Xu J. Estimating soil salt components and salinity using hyperspectral remote sensing data in an arid area of China[J]. Journal of Applied Remote Sensing, 2017, 11(1): 016043-016043.
[12] Hu D, Shu H, Hu H, Xu J. Spatiotemporal regression Kriging to predict precipitation using time-series MODIS data[J]. Cluster Computing, 2017, 20(1): 347-357.
[13] Xu J, Zhao Y, Zhong K, Ruan H, Liu X. Coupling Modified Linear Spectral Mixture Analysis and SCS-CN Models to Simulate Surface Runoff: Application to the Main Urban Area of Guangzhou, China[J]. Water, 2016, 8, 550, doi:10.3390/w8120550.
[14] Xu J, Zhang F, Shu H, et al. Improvement of the Snow Depth in the Common Land Model by Coupling a Two-Dimensional Deterministic Ensemble Model with a Variational Hybrid Snow Cover Fraction Data Assimilation Scheme and a New Observation Operator[J]. Journal of Hydrometeorology, 2017, 18(1): 119-138.
[15] Xu J , Zhang F , Zhao Y , et al. Joint DEnKF-albedo assimilation scheme that considers the common land model subgrid heterogeneity and a snow density-based observation operator for improving snow depth simulations[J]. Journal of Applied Remote Sensing, 2016, 10(3):036001.
[16] Hu H, Shu H, Hu Z, Xu J. Using compute unified device architecture-enabled graphic processing unit to accelerate fast Fourier transform-based regression Kriging interpolation on a MODIS land surface temperature image[J]. Journal of Applied Remote Sensing, 2016, 10(2):026036.
[17] Xu J, Shu H. DEnKF-based assimilation of MODIS-derived snow cover products into common land model considering the model sub-grid heterogeneity[J]. Geomatics & Information Science of Wuhan University, 2016.
[18] Xu J, Shu H, Dong L. DEnKF–Variational Hybrid Snow Cover Fraction Data Assimilation for Improving Snow Simulations with the Common Land Model[J]. Remote Sensing, 2014, 6(11):10612-10635.
[19] Xu J , Shu H . Assimilating MODIS-based albedo and snow cover fraction into the Common Land Model to improve snow depth simulation with direct insertion and deterministic ensemble Kalman filter methods[J]. Journal of Geophysical Research: Atmospheres, 2014, 119(18):10,684-10,701.
[20] Xu J, Shu H, Jiang H , et al. Sobol’ sensitivity analysis of parameters in the common land model for simulation of water and energy fluxes[J]. Earth Science Informatics, 2012, 5(3-4):167-179.
[21] 许剑辉, 舒红. 基于 Triple-Collocation 的地面观测与卫星遥感数据融合的雪深反演. 武汉大学学报(信息科学版), 2015, 40(4): 469-473.
专利
[1]一种地表温度降尺度方法及系统，专利号: ZL201911198692.4，已授权
[2]空间自相关的机器学习卫星降水数据降尺度方法、系统, 专利号: ZL201910971041.8，已授权
[3]一种基于人流密度的流行病疫情风险等级评估方法，专利号: ZL202010236407.X，已授权
[4]一种基于人口迁徙大数据的流行病感染人数估算方法，专利号: ZL202010236392.7，已授权
[5]基于人口迁徙大数据的流行病疫区返程人群规模预测方法，专利号: ZL202010236402.7，已授权
[6]一种三维模型单体化方法、系统、存储介质及设备，专利号: ZL201911093728.2，已授权
招生专业与方向:
硕士生招生方向：多源大数据融合、地理大数据与空间智能
联系方式:
地址：广州市先烈中路100号大院广州地理研究所
邮编：510070
邮箱：xujianhui306@gdas.ac.cn
