Remotely-sensed phenology pattern regionalization for land cover classification of natural scenes: A case study in China

被引：0
作者：
Liu, Xiaoliang [1 ,2 ]
Wang, Zhihua [1 ,2 ]
Yang, Xiaomei [1 ,2 ]
Cheng, Weiming [1 ,2 ]
Zhang, Junyao [1 ,2 ]
Liu, Yueming [1 ,2 ]
Liu, Bin [1 ,2 ]
Meng, Dan [1 ,2 ]
Zeng, Xiaowei [1 ,2 ]
机构：
[1] State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing
[2] University of Chinese Academy of Sciences, Beijing
来源：
Dili Xuebao/Acta Geographica Sinica | 2024年 / 79卷 / 09期
关键词：
China; classification; land cover; phenology; regionalization; remote sensing;
D O I：
10.11821/dlxb202409004
中图分类号：
学科分类号：
摘要：
Selection of appropriate geographic boundaries for zoning the study area or images can effectively improve the accuracy and efficiency of land cover classification by reducing the complexity of land cover within the regions and the variability of its features in the images. At present, the regionalization data used in land cover mapping based on stratified classification strategies, such as ecological regionalization, lack targeted objectives, which limits its applicability and effectiveness in remote sensing classification. Vegetation phenology is the main cause of spectral heterogeneity within the land cover of natural scenes. To address this issue, this study proposed a remotely-sensed phenology pattern regionalization scheme for land cover classification of natural scenes. The regionalization scheme is implemented by constructing a zoning index system using vegetation indices, which reflect the greenness status of vegetation, and key phenological periods, which reflect the growth and development rhythm of vegetation. Small geomorphic regions are used as the zoning units, and a data-driven spatially constrained hierarchical clustering algorithm is employed in the regionalization. The evaluation results based on statistical tests and multi-source land cover products indicate that the remotely-sensed phenology pattern regionalization in this study effectively reduces the complexity of land cover within the region and the intra-class feature heterogeneity caused by vegetation phenology, and shows high potential in constructing representative land cover sample libraries and implementing stratified classification strategies. © 2024 Science Press. All rights reserved.
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页码：2206 / 2229
页数：23
相关论文
共 81 条
  • [1] Ma Y., Wu H.P., Wang L.Z., Et al., Remote sensing big data computing: Challenges and opportunities, Future Generation Computer Systems, 51, pp. 47-60, (2015)
  • [2] Chi M., Plaza A., Benediktsson J.A., Et al., Big data for remote sensing: Challenges and opportunities, Proceedings of the IEEE, 104, 11, pp. 2207-2219, (2016)
  • [3] Bing Z., Xiaomei Y., Lianru G., Et al., Geo-cognitive models and methods for intelligent interpretation of remotely sensed big data, Acta Geodaetica et Cartographica Sinica, 51, 7, pp. 1398-1415, (2022)
  • [4] Xiaomei Y., Zhihua W., Yueming L., Et al., Development and technical prospect of remote sensing intelligent information processing, Journal of Tongji University (Natural Science), 51, 7, pp. 1025-1032, (2023)
  • [5] Radoux J., Lamarche C., Van Bogaert E., Et al., Automated training sample extraction for global land cover mapping, Remote Sensing, 6, 5, pp. 3965-3987, (2014)
  • [6] Zhihua W., Xiaomei Y., Chenghu Z., Geographic knowledge graph for remote sensing big data, Journal of Geo-Information Science, 23, 1, pp. 16-28, (2021)
  • [7] Zhihua W., Xiaomei Y., Yueming L., Et al., Geographical principles of remote sensing object-based image analysis and an analysis framework, National Remote Sensing Bulletin, 28, 6, pp. 1412-1424, (2023)
  • [8] Zhihua W., Xiaomei Y., Junyao Z., Et al., A remote sensing intelligent interpretation framework through geoscience zoning for complex nature scenes and its preliminary experiments, Journal of Geo-information Science, pp. 1-26
  • [9] Bojie F., Liding C., Guohua L., The objectives, tasks and characteristics of China ecological regionalization, Acta Ecologica Sinica, 19, 5, pp. 591-595, (1999)
  • [10] Du Z., Yang O., Chenghu Z., Understanding of and thinking over geographical regionalization methodology, Acta Geographica Sinica, 63, 6, pp. 563-573, (2008)
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