检索
E-mail
RSS

作者投稿 主编审稿 专家审稿 远程编辑

热带海洋学报

• • 上一篇    

近四十年江苏省海岸带植被时空变化遥感研究

吕硕1, 陈超1, 陈智康1, 沈淼1, 杨晓燕2   

  1. 1. 苏州科技大学地理科学与测绘工程学院, 江苏 苏州 215009

    2. 内蒙古自治区测绘地理信息中心, 内蒙古自治区 呼和浩特 750306



  • 收稿日期:2025-11-05 修回日期:2026-01-06 接受日期:2026-01-15
  • 通讯作者: 陈超
  • 基金资助:
    国家自然科学基金项目(42171311)

A Remote Sensing Investigation of the Spatiotemporal Dynamics of Coastal Vegetation in Jiangsu Province over the Past Four Decades

LYU Shuo1, CHEN Chao1, CHEN Zhikang1, SHEN Miao1, YANG Xiaoyan2   

  1. 1. School of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou 215009, China;

    2. Institution: Inner Mongolia Autonomous Region Surveying and mapping Geographic Information Center, Hohhot 750306, China



  • Received:2025-11-05 Revised:2026-01-06 Accepted:2026-01-15
  • Supported by:
    National Natural Science Foundation of China(42171311)

PDF (PC)

赞

摘要： 受围垦开发、生物入侵和周期性水淹等影响，江苏省海岸带植被遥感信息提取面临着空间范围界定不准、时空演变特征不清等挑战。本研究基于GEE（Google Earth Engine）云平台和Landsat长时序数据，构建了一种面向海岸带植被的遥感信息提取与时空演变分析模型，明确了四十年江苏省海岸带植被覆盖的时空变化规律。结果表明：（1）所构建的模型充分考虑了潮汐淹没、水陆交互及季节变化等因素影响，在复杂动态环境中显著提升了植被信息提取精度与时空演变特征监测的稳定性；（2）1985—2024年间，江苏省海岸带植被覆盖总面积整体呈轻微收缩态势，由90,678.40 km²减少至88,599.71 km²，但植被覆盖度有所增加，NDVI均值由0.64升至0.69；（3）NDVI等级转移结果显示，较高植被覆盖区向高植被覆盖区的正向跃迁面积最大，达29,769.76 km²，表明植被覆盖格局呈现由较高等级向高等级集聚的优化演化特征。研究成果可为海岸带生态动态监测、植被恢复评估及区域生态安全管控提供技术支撑，并为推进生态修复与实现“碳达峰—碳中和”目标提供科学参考。

关键词: 植被覆盖, NDVI, 时空格局, 海岸带

Abstract: Affected by reclamation and development, biological invasion, and periodic inundation, remote sensing-based vegetation extraction in the coastal zone of Jiangsu Province faces challenges such as inaccurate spatial delineation and unclear spatiotemporal evolution characteristics. Using the Google Earth Engine (GEE) cloud platform and long-term Landsat time series, this study develops a remote-sensing framework for vegetation extraction and spatiotemporal evolution analysis, and elucidates the four-decade dynamics of vegetation cover in the Jiangsu coastal zone. The results show that: (1) by explicitly accounting for tidal inundation, land-sea interactions, and seasonal variability, the proposed model markedly improves the accuracy of vegetation extraction and the robustness of change monitoring in highly dynamic coastal environments; (2) from 1985 to 2024, the total vegetation-covered area in the Jiangsu coastal zone exhibited a slight overall contraction, decreasing from 90,678.40 km² to 88,599.71 km², whereas vegetation density increased, with the mean NDVI rising from 0.64 to 0.69; (3) NDVI transition analysis indicates that the largest positive shift occurred from the relatively high vegetation cover class to the high vegetation cover class, totaling 29,769.76 km², indicating an optimized evolution toward aggregation at higher vegetation levels. These findings provide technical support for coastal ecological monitoring, vegetation restoration assessment, and regional ecological security management, and offer scientific evidence for promoting ecological restoration and achieving carbon peaking and carbon neutrality targets.

Key words: vegetation cover, NDVI, spatiotemporal pattern, coastal zone