代表性学术论文: [1] Kaifeng Peng, Beibei Si, Weiguo Jiang, et al. (2025). Exploring the Annual Dynamics of China’s Rivers From 2016 to 2023 Based on Sentinel-Derived Datasets. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 18, 16694-16706. (SCI二区) [2] Kaifeng Peng, Weiguo Jiang, Peng Hou, et al. (2024). Detailed wetland-type classification using Landsat-8 time-series images: a pixel- and object-based algorithm with knowledge (POK), GIScience & Remote Sensing, 61:1, 2293525. (SCI一区,ESI高被引) [3] Kaifeng Peng, Weiguo Jiang, Peng Hou, et al. (2024). Exploring the long-term dynamics of detailed wetland types and their driving forces in coastal metropolitan areas from 1990 to 2020. International Journal of Applied Earth Observation and Geoinformation, 132, 104012. (SCI一区) [4] Kaifeng Peng, Weiguo Jiang, Xuejun Wang, et al. (2023). Evaluation of future wetland changes under optimal scenarios and land degradation neutrality analysis in the Guangdong-Hong Kong-Macao Greater Bay Area. Science of the Total Environment, 879(March), 163111. (SCI一区) [5] Kaifeng Peng, Weiguo Jiang, Peng Hou, et al.(2023). Continental-scale wetland mapping: a novel algorithm for detailed-type wetland classification based on time series Sentinel-1 /2 images. Ecological Indicators.148, 110113. (SCI二区) [6] Kaifeng Peng, Weiguo Jiang, Ziyan Ling Z, et al. (2021) Evaluating the potential impacts of land use changes on ecosystem service value under multiple scenarios in support of SDG reporting: A case study of the Wuhan urban agglomeration. Journal of Cleaner Production, 307: 127321. (SCI一区,ESI高被引) [7] Kaifeng Peng, Weiguo Jiang, Yue Deng, et al. (2020). Simulating wetland changes under different scenarios based on integrating the random forest and CLUE-S models: A case study of Wuhan Urban Agglomeration. Ecological Indicators, 117: 106671. (SCI二区) [8] 彭凯锋, 蒋卫国, 侯鹏, 凌子燕, 牛振国, 毛德华, 黄卓. 结合多源专题数据和目视解译的大区域密集湿地样本数据生产. 遥感学报, 2024, 28(2): 334-345.(EI,中文核心) [9] 彭凯锋, 蒋卫国, 侯鹏, 等. 三江源国家公园植被时空变化及其影响因子[J]. 生态学杂志, 2020, 39(10): 3388-3396. (中文核心) [10] 彭凯锋, 蒋卫国, 邓越. 武汉城市圈湿地受损程度识别及驱动因素分析[J]. 自然资源学报, 2019, 34(8): 1694-1707. (中文核心) 发明专利 [1] 彭凯锋, 蒋卫国, 侯鹏, 王强, 王雪君. 基于密集时序遥感影像的长时序地物样本自动生产方法[P]. 天津市: CN117292154B, 2024-02-06. [2] 蒋卫国,王晓雅,凌子燕, 彭凯锋. 城市湿地精细类型逐级遥感提取方法、系统、设备及介质[P]. 北京市: CN 117197673 B, 2024-06-07 |
获得的奖励或荣誉: 担任“GIScience & Remote Sensing”、“International Journal of Applied Earth Observation and Geoinformation”、“Ecological Indicators”等期刊审稿人,同时获得多项荣誉和奖励,部分列表如下: [1] 国际数字地球学会中国国家委员会-数字湿地专业委员会,委员 [2] 中国自然资源学会研学工作委员会,委员 [3] 2025年,中国湿地遥感大会“优秀青年学者” [4] 彭凯锋(7/8), 2022年度中国遥感优秀成果一等奖, 粤港澳大湾区湿地资源精细化遥感监测与评估. 2023. (吴志峰, 蒋卫国, 宋松, 邓雅文, 张棋斐, 郑子豪, 彭凯锋, 黄晓峻) [5] 2020年,中国生态文明与可持续发展学术论坛,优秀报告奖 |