姓名:吴小丹
职称:
性别:女
毕业院校:中国科学院遥感与数字地球研究所
学历:研究生
学位:博士
在职信息:在职
所在单位:遥感与GIS研究所
入职时间:2017.09
办公地点:观云楼1617
电子邮箱:wuxd@lzu.edu.cn
学习经历
2012年-2017年: 中国科学院,遥感与数字地球研究所,博士; 2016年-2017年: 瑞士苏黎世大学,地理学院遥感实验室,联合培养博士; 2008年-2012年: 中国石油大学(华东), 地球科学与技术学院, 理学学士;
研究方向
地面优化采样、尺度转换、定量遥感真实性检验、遥感产品应用的不确定性分析等
工作经历
2019/12-至今 兰州大学 资源环境学院 教授 2017/09-2019/12 兰州大学 资源环境学院 副教授 2018/09-2019/09 瑞士伯尔尼大学 地理系遥感实验室 博后
主讲课程
《微波遥感》 《遥感数字图像处理》
学术兼职
《遥感学报》编委 《遥感技术与应用》青年编委 教育部学位与研究生教育发展中心通讯评审人; 遥感著名期刊 Remote Sensing of Environment、IEEE Transactions on Geoscience and Remote Sensing,IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,IEEE Geoscience and Remote Sensing Letters等审稿人。
研究成果
国家在对地观测系统建设方面投入巨大,但海量遥感数据和产品精度无法得到准确评价,极大限制了遥感在各领域的应用。在此背景下,本人的研究方向主要围绕定量遥感产品的真实性检验: ①发展了异质性地表像元尺度地面观测理论与方法:提出了地面观测-卫星像元之间的几何位置匹配方法,阐释了空间异质性、采样位置和数目与地面观测不确性之间的定量关系,发展了基于时空代表度的时空优化采样方法,降低了像元尺度地面观测的不确定性; ②构建了耦合地表时空动态变化特征的升尺度转换模型,填补了异质性地表单个站点升尺度模型的缺失,将传统的、适用于单一时相的“多点—面”和“面—面”升尺度转换方法扩展到长时间序列上,显著提高了关键参量时空尺度转换的能力与精度; ③在国际上率先开展了真实性检验不确定性分析,构建了各主要环节的误差量化及误差传递模型,阐明了不确定性因素的影响机制,建立了不确定性最小准则的真实性检验理论与方法,开展了异质性地表BRDF、反照率、土壤水分、积雪产品等的真实性检验实践。
获得荣誉
博士学位论文《异质性地表定量遥感产品真实性检验方法研究-以地表反照率为例》被评为2018年度 “中国科学院优秀博士学位论文奖” 2018年 “瑞士政府卓越奖学金” 2017年 “李小文遥感科学青年奖” 2017年 “中国科学院院长奖”
在研项目
1. 国家自然科学基金-面上项目“中低分辨率遥感产品真实性检验不确定性研究”(42071296), 2021-2024, 主持人 2. 国家自然科学基金-青年基金项目“异质性地表反照率产品真实性检验中的尺度效应研究”(41801226),2019-2021,主持人 3. 国家重点研发计划项目:北极快速变化的机理、影响及其气候效应研究(2019YFA0607003),2019/11-2024/10,项目骨干 4. 自由探索项目-优秀青年教师科研创新项目“遥感数据时间尺度对地理要素时变分析的影响 ”,2020-2021, 主持人
发表论文
以第一/通讯作者发表论文: [1]. Xiaodan Wu, Jianguang Wen, Rongqi Tang, Jingping Wang, et al. 2023. Quantification of the uncertainty in multiscale validation of coarse-resolution satellite albedo products: A study based on airborne CASI data. Remote Sensing of Environment, 287 (113465). (JCR-1, TOP) [2]Rongqi Tang, Xiaodan Wu*, Jingping Wang, et al. 2023 A geometric location matching method for validation of satellite products: a case study for albedo. IEEE Geoscience and Remote Sensing Letters, 20(3001405) [3]. Xiaodan Wu, Jianguang Wen, Qing Xiao, et al. 2022. Spatial heterogeneity of albedo at subpixel satellite scales and its effect in validation: airborne remote sensing results from HiWATER. IEEE Transactions on Geoscience and Remote Sensing, 60(4407114): 1-14. (JCR-1, TOP) [4]. Jingping Wang, Xiaodan Wu*, Rongqi Tang, Qicheng Zeng, Zheng Li, Jianguang Wen, Qing Xiao, 2022. Evaluation of three error- correction models based on the matched pixel scale ground “truth”: A case study of MCD43A3 V006 over the Heihe River Basin, China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, VOL. 15, 8785-8797. (JCR-1) [5]. Jingping Wang, Xiaodan Wu*, Rongqi Tang, Dujuan Ma, Qicheng Zeng, Qing Xiao, Jianguang Wen. 2022. The first assessment of coarse-pixel soil moisture products within the multi-scale validation framework over Qinghai-Tibet Plateau, Journal of Hydrology,Volume 613, Part B, 128454 (JCR-1, TOP) [6]. Jianguang Wen, Xiaodan Wu*, Jingping Wang, et al., 2022. Characterizing the effect of spatial heterogeneity and the deployment of sampled plots on the uncertainty of ground “truth” on a coarse grid scale: Case study for near-infrared (NIR) surface reflectance. Journal of Geophysical Research: Atmospheres, 127, e2022JD036779. (IF=3.63, Nature index, TOP) [7]. Rongqi Tang, Xiaodan Wu*, Jingping Wang, Qicheng Zeng, Zheng Li, Jianguang Wen. 2022. Evaluation of several recently developed sampling strategies within the coarse pixel scale for validation of coarse-resolution satellite albedo products. International Journal of Digital Earth. 15:1, 2319-2334. [8]. Dujuan Ma, Xiaodan Wu*, Jingping Wang, Cuicui Mu. 2022. The spatiotemporal scale effect on interannual trend estimates of vegetation change based on long-term satellite products: A case study in Qinghai–Tibet Plateau. Journal of Geographical Sciences. Accepted. [9]. Jianguang Wen, Xiaodan Wu*, Dongqin You, Xuanlong Ma, Dujuan Ma, Jingping Wang, and Qing Xiao. 2023. The main inherent uncertainty sources in trend estimation based on satellite remote sensing data. Theoretical and Applied Climatology. 151(1-2), 915-934. (JCR-2) [10]. Jingping Wang, Xiaodan Wu*, Jianguang Wen, et al., 2022. Upscaling in Situ Site-Based Albedo Using Machine Learning Models: Main Controlling Factors on Results. IEEE Transactions on Geoscience and Remote Sensing, 60(4403516). (JCR-1, TOP) [11]. Xiaodan Wu, Jianguang Wen, Qing Xiao, et al. 2022. Quantification of the Uncertainty Caused by Geometric Registration Errors in Multiscale Validation of Satellite Products. IEEE Geoscience and Remote Sensing Letters, 19(8017905). (JCR-1) [12]. Xiaodan Wu, Kathrin Naegeli, Valentina Premier, et al. 2021. Evaluation of snow extent time series derived from AVHRR GAC data (1982-2018)in the Himalaya-Hindukush. The Cryosphere, 15: 4261-4279. (JCR-1) [13]. Xiaodan Wu, Jianguang Wen, Qing Xiao, et al. 2021. A Multiscale Nested Sampling Method for representative albedo observations at various pixel scales. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14: 8193-8207. (JCR-1) [14]. Dujuan Ma, Xiaodan Wu*, Xuanlong Ma, et al. 2021. Spatial, Phenological, and Inter-Annual Variations of Gross Primary Productivity in the Arctic from 2001 to 2019. Remote Sensing, 13, 2875. (JCR-1, TOP) [15]. Xiaodan Wu, Dujuan Ma, Jingping Wang et al., 2021. Temporal scale effects on trend estimates for solar radiation, thermal and snow conditions and their feedbacks:the case from China. Theoretical and Applied Climatology, 146, 869–882. (JCR-2) [16]. Xiaodan Wu, Kathrin Naegeli, Stefan Wunderle. 2020. Geometric accuracy assessment of coarse resolution satellite data sets: a study based on AVHRR GAC data at the subpixel level. Earth System Science Data, 12, 539–553. (IF=10.95, JCR-1, TOP) [17]. Xiaodan Wu, Jianguang Wen, Qing Xiao, et al. 2020. Upscaling of single site-based measurements for validation of long-term coarse-pixel albedo products. IEEE Transactions on Geoscience and Remote Sensing. 58(5), 3411-3425 (IF=5.63, JCR-1, TOP) [18]. Xiaodan Wu, Qing Xiao, Jianguang Wen, et al. 2019. Advances in quantitative remote sensing product validation: Overview and current status. Earth-Science Reviews, 102875. (IF=9.53, JCR-1, TOP) [19]. Xiaodan Wu, Jianguang Wen, Qing Xiao, et al. 2019. Impacts and contributors of representativeness errors of in situ albedo measurements for the validation of remote sensing products. IEEE Transactions on Geoscience and Remote Sensing, 57(12), 9740- 9755 (IF=5.63, JCR-1, TOP) [20]. Xiaodan Wu, Qing Xiao, Jianguang Wen, et al. 2019. Direct Comparison and Triple Collocation: Which Is More Reliable in the Validation of Coarse‐Scale Satellite Surface Albedo Products. Journal of Geophysical Research: Atmospheres. 124, 5198–5213 (IF=3.63, Nature index, TOP) [21]. Xiaodan Wu, Jianguang Wen, Qing Xiao, et al. 2018. Accuracy Assessment on MODIS (V006), GLASS and MuSyQ Land-Surface Albedo Products: A Case Study in the Heihe River Basin, China. Remote Sensing, 10(12), 2045. (IF=4.12, JCR-1, TOP) [22]. Xiaodan Wu, Jianguang Wen, Qing Xiao, et al. 2018. Forward a spatio-temporal trend surface for long-term ground-measured albedo upscaling over heterogeneous land surface. International Journal of Digital Earth, 11(5), 470-484. (IF=3.98, JCR-1) [23]. Xiaodan Wu, Jianguang Wen, Qing Xiao, et al. 2017. Assessment of NPP VIIRS albedo over heterogeneous crop land in northern China. Journal of Geophysical Research: Atmospheres, 122(24),13,138–13,154. (IF=3.63, Nature index, TOP) [24]. Xiaodan Wu, Qing Xiao, Jianguang Wen, et al. 2017. Upscaling Albedo over Heterogeneous Surfaces Using In Situ Measurements and High-Resolution Imagery. International Journal of Digital Earth. 10(6), 604-622. (IF=3.98, JCR-1) [25]. Xiaodan Wu, Jianguang Wen, Qing Xiao, et al. 2016. Coarse scale in situ albedo observations over heterogeneous snow-free land surfaces and validation strategy: A case of MODIS albedo products preliminary validation over northern China[J]. Remote Sensing of Environment, 184: 25-39. (IF=8.218, JCR-1, TOP) [26]. Xiaodan Wu, Qing Xiao, Jianguang Wen, et al. 2015. Optimal Nodes Selectiveness from WSN to Fit Field Scale Albedo Observation and Validation in Long Time Series in the Foci Experiment Areas, Heihe. Remote Sensing. 7(11), 14757-14780. (IF=4.12, JCR-1, TOP) [27]. 汪静平,吴小丹*, 马杜娟,闻建光,肖青. 2023.基于机器学习的遥感反演:不确定性因素分析. 遥感学报, DOI:10.11834/jrs.20221172. [28]. 李红艳, 马杜娟, 吴小丹*,等. 2023. 青藏高原GPP时空变化特征及影响因素分析. 遥感技术与应用,已接收. [29]. 吴小丹, 肖青, 闻建光, 游冬琴. 2019. 异质性地表反照率遥感产品真实性检验研究现状及挑战. 遥感学报, 23(1), 11-23. [30]. 万昌君, 吴小丹*, 林兴稳. 2019. 遥感数据时空尺度对地理要素时空变化分析的影响:回顾和展望. 遥感学报, 23(6):1022–1035 [31]. 吴小丹,闻建光,肖青等. 2015. 关键陆表参数遥感产品真实性检验方法研究进展[J].遥感学报, 19(1):75-92. [32]. 吴小丹,肖青,闻建光等. 2014. 遥感数据产品真实性检验不确定性分析研究进展.遥感学报, 18(5):1011-1023. [33]. Xiaodan Wu, Qing Xiao, Jianguang Wen, et al. Evaluation of the MODIS and GLASS albedo products over the Heihe river Basin, China[C]// IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2016:3493-3495. [34]. Xiaodan Wu, Jianguang Wen, Qing Xiao, et al. Remote sensing albedo product validation over heterogenicity surface based on WSN: preliminary results and its uncertainty[J]. Proceedings of SPIE - The International Society for Optical Engineering, 2014, 9260:92603P- 92603P-7.
出版著作
肖青,闻建光,唐伯惠,吴小丹. 定量遥感实验. 2023. 科学出版社.