方宏，理学博士，硕士生导师，江苏海安人。毕业于南京大学（导师：杜培军教授，长江特聘），现为南京林业大学校聘副教授（水杉英才），主要从事城市遥感、遥感智能解译、地理空间智能等方向研究工作。主持南京林业大学水杉英才引进项目1项，参与国家自然科学基金重点项目2项、面上项目2项；以第一作者在Sustainable Cities and Society、IEEE TGRS等期刊发表SCI论文10篇，担任IEEE TGRS/JSTARS/GRSL等SCI期刊审稿专家，获国家地理信息科技进步奖一等奖（15/16），江苏省测绘地理信息科技进步一等奖（2/11）等奖励。
城市遥感
遥感智能解译
地理空间智能
2013.09-2017.06 南京师范大学，地理信息科学
2017.09-2020.06 南京师范大学，地图学与地理信息系统
2020.09-2024.06 南京大学，地理学
2024.07-至今 南京林业大学测绘工程系，校聘副教授
资源调查与监测技术
1. 南京林业大学水杉英才引进项目（163050254），主持，在研；
2. 国家自然科学基金面上项目：地理大数据支持的城市场景变化检测与智能解释研究，参与，在研；
3. 国家自然科学基金重点项目：时间序列遥感影像智能处理与地理过程时空分析，参与，结题。
[1] Hong Fang, Shanchuan Guo, Chenghan Yang, Bo Yuan, Chunqiang Li, Xiaoquan Pan, Pengfei Tang, Peijun Du[J]. Influence of urban functional zone change on land surface temperature using multi-source geospatial data: A case study in Nanjing City, China. Sustainable Cities and Society, 2024, 115: 105874.(中科院一区TOP)
[2] Hong Fang, Shanchuan Guo, Xin Wang, et al. Scene change detection by differential aggregation network and class probability-based fusion strategy[J]. IEEE Transactions on Geoscience and Remote Sensing,2023,61: 5406918. (中科院一区TOP)
[3] Hong Fang, Shanchuan Guo, Xin Wang, et al. Automatic urban scene-level binary change detection based on a novel sample selection approach and advanced triplet neural network [J]. IEEE Transactions on Geoscience and Remote Sensing,2023, 61: 5601518. (中科院一区TOP)
[4] Hong Fang, Peijun Du, Xin Wang. A novel unsupervised binary change detection method for VHR optical remote sensing imagery over urban areas[J]. International Journal of Applied Earth Observation and Geoinformation, 2022, 108: 102749. (中科院一区TOP)
[5] Hong Fang, Yuchun Wei, Hong Luo, et al. Detection of building shadow in remote sensing imagery of urban areas with fine spatial resolution based on saturation and near-infrared information[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019, 12(8): 2695-2706. (中科院二区TOP)
[6] Hong Fang, Chenghan Yang, Peng Zhang, Pengfei Tang, Shanchuan Guo[J]. Unsupervised Impervious Surface Change Detection Using a Coarse-to-Fine Hierarchical Approach. IEEE Geoscience and Remote Sensing Letters, doi: 10.1109/LGRS.2024.3485732.
[7] Hong Fang, Peijun Du, Xin Wang, et al. Unsupervised change detection based on weighted change vector analysis and improved Markov random field for high spatial resolution imagery [J]. IEEE Geoscience and Remote Sensing Letters, 2022, 19: 6002005.
[8] Hong Fang, Peijun Du, Xin Wang. A novel unsupervised multiple change detection method for VHR remote sensing imagery using CNN with hierarchical sampling[J]. International Journal of Remote Sensing, 2022, 43(13): 5006-5024.
[9] Hong Fang, Yuchun Wei, Qiuping Dai. A novel remote sensing index for extracting impervious surface distribution from Landsat 8 OLI imagery[J]. Applied Sciences, 2019, 9(13): 2631.
[10] Hong Fang, Shanchuan Guo, Cong Lin, et al. Scene-level change detection by integrating VHR images and POI data using a multiple-branch fusion network[J]. Remote Sensing Letters, 2023, 14(8): 808-820.
1. 地理信息科技进步奖一等奖（序15）
2. 江苏省测绘地理信息科技进步一等奖（序2）
手机/微信：15951970752；邮箱：fangh@njfu.edu.cn
欢迎测绘、遥感、GIS、计算机视觉等方向的有志青年报考研究生！
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