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资源与环境遥感团队学术论文在SCI期刊International Journal of Applied Earth Observation and Geoinformation上发表

日期:2024-05-16 点击量: 174

2024515日,云南省高校资源与环境遥感重点实验室2022级硕士研究生黄祥为第一作者、程峰老师为通讯作者,王成研究员、王金亮教授等为共同作者撰写的“Urban building height extraction accommodating various terrain scenes using ICESat-2/ATLAS data”论文(DOI: https://doi.org/10.1016/j.jag.2024.103870)在SCI期刊International Journal of Applied Earth Observation and Geoinformation(中科院1TOP,影响因子7.5)上发表。

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该论文基于ICESat-2/ATLAS光子点云发展了一种地形自适应的方法框架,其面向不同的城市地形场景均能提取高精度、高密度的建筑高度数据。其中,基于“夜间-平坦地形、夜间-起伏地形、日间-平坦地形、日间-起伏地形”四个场景验证了算法的通用性。研究结果显示,所提出算法能消除建筑光子漏检、建筑光子与地面光子混检等问题,并从原始光子中准确提取建筑光子与地形线,最终保障了不同城市场景下的建筑高度估算精度,尤其是起伏地形下得以显著提升。该研究可为大尺度城市建筑高度反演工作提供重要的理论依据。

该论文得到国家自然科学基金项目(42361065/U22A20566/32160280)、云南省科技重大专项(西南联合研究生院科技专项-基础研究与应用基础研究重大专项,202302AO370003)、云南省自然科学基金项目(202201AT070040)、中国科学院热带森林生态学重点实验室开放基金项目(22-CAS-TFE-04)、河北省自然科学基金项目(D2021106002)、云南省教育厅科学研究基金项目(2024Y172)的支持。

上述文章是黄祥同学硕士期间以第一作者发表的第3SCI学术论文(详见附录12),让我们恭喜黄祥同学!希望他再接再厉!也热烈祝贺团队取好成绩!

附录1论文相关信息

标题:Urban building height extraction accommodating various terrain scenes using ICESat-2/ATLAS data

作者:Xiang Huang a, Feng Cheng a,*, Yinli Bao b, Cheng Wang a, e, Jinliang Wang a, Junen Wu a, Junliang He c, Jieying Lao d

通讯作者:Feng Cheng; chengfeng_rs@163.com

作者单位:

a. Faculty of Geography, Yunnan Normal University, Kunming 650500, China.

b. Kunming Surveying and Mapping Management Center, Kunming 650506, China;

c. College of Resources and Environmental Science, Shijiazhuang University, Shijiazhuang 050035, China.

d. School of Earth Sciences, Yunnan University, Kunming 650091, China.

e. Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China.

出版刊物:International Journal of Applied Earth Observation and Geoinformation

摘要:Although the photon point cloud data acquired from ICESat-2/ATLAS can be efficiently employed in urban building height extraction, its universal applicability in undulating terrain scenarios is constrained, and there are noticeable issues of false positives and false negatives. This research establishes a terrain-adaptive methodological framework based on ICESat-2/ATLAS photon point cloud to extract high-precision, high-density building height data across varied urban topographical conditions. First, a terrain-adaptive elevation buffer is utilized to coarse denoise the photon point cloud, involving the removal of the majority of noise photons in the scene, thereby enhancing the efficiency of subsequent algorithms. Second, urban signal photons are extracted from the remaining original photons using the Adaptive Method Based on Single-Photon Spatial Distribution (SPSD-AM). This approach demonstrates high universality across various urban scenes, while simultaneously ensuring a stable accuracy of urban signal photon extraction. Subsequently, ground photons are extracted from the urban signal photons and fit the ground curve based on the Adaptive Method Based on Spatial Differences of Urban Signal Photons (USPSD-AM), which addresses the challenge of the potential mixing of ground and building photons in complex terrain scenarios. A precise ground curve is then employed to extract building photons from urban signal photons. In order to mitigate issues such as false positives and negatives, post-processing steps, including completion and denoising of building photons, are implemented. Finally, the acquired building photons and ground curve are adopted to extract accurate building height parameters. The precision verification results show that the extracted building heights are considerably consistent with the reference building heights. The mean RMSE and MAE are 0.273 m and 0.202 m for flat terrains and 1.168 m and 0.759 m for undulating terrains, respectively. The proposed method demonstrates superior applicability across diverse urban scenarios, providing a robust theoretical foundation for large-scale urban building height retrieval efforts.

关键字:ICESat-2, Terrain-adaptive, Photon point cloud classification, Urban building height

附录2黄祥硕士期间发表论文清单

[1]      Huang, X., Cheng, F. *, Wang, J., Duan, P., & Wang, J. (2023). Forest Canopy Height Extraction Method Based on ICESat-2/ATLAS Data. IEEE Transactions on Geoscience and Remote Sensing, 61, 1-14. (中科院SCI一区,IF 8.2)

[2]      Huang, X., Cheng, F. *, Wang, J., Yi, B., Bao, Y. (2023). Comparative Study on Remote Sensing Methods for Forest Height Mapping in Complex Mountainous Environments. Remote Sensing, 15(9), 2275. (中科院SCI二区,IF 5.0)

Huang, X., Cheng, F. *, Bao, Y., Wang, C., Wang, J., Wu, J., He, J., & Lao, J.(2024). Urban building height extraction accommodating various terrain scenes using ICESat-2/ATLAS data. International Journal of Applied Earth Observation and Geoinformation, 130, 103870. (中科院SCI一区TOPIF 7.5)