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    2020—2023年全国大陆地区沿海区域变化图斑高频次时空演变分析

    Analysis of high-frequency spatiotemporal evolution of patches reflecting 2020—2023 changes in coastal areas of the Chinese mainland

    • 摘要: 我国大陆地区的沿海区域变化图斑分析往往存在影像分辨率低、时间间隔久、区域范围小等问题。为获取高频次、准确的全国沿海区域变化信息,辅助我国海洋资源动态监管和沿海区域相关保护政策的执行,该文利用15 d一个周期的国产高分辨率遥感数据,采用迭代加权多元变化检测算法(iteratively reweighted multivariate alteration detection,IR-MAD)结合目视解译的方法,提取全国大陆地区11个沿海省市2020—2023年的沿海区域变化图斑,并对其进行时空特征分析、景观格局分析和空间相关性分析研究。结果表明: 我国大陆地区沿海区域变化图斑存在明显的定向变化,各研究区的围海到填海的变化图斑面积均为最高值,并且除海南省以外该类型的变化图斑面积均大于1 000 km2; 各类变化图斑占比逐渐趋于均衡,在2022年冬季,填海变化图斑的占比首次低于50%; 各类变化图斑的聚集度都处于逐渐增加的趋势,未来变化图斑分布将较为集中,各区域的变化图斑质心均发生了方向各异的迁移,且变化图斑在20 km之内存在显著的空间相关性。

       

      Abstract: The analysis of patches showing changes in coastal areas of the Chinese mainland tends to encounter challenges such as low image resolution, long time intervals, and limited spatial coverage. This study aims to obtain high-frequency, accurate information on changes in coastal areas nationwide. This will facilitate the dynamic monitoring of marine resources and the implementation of relevant protection policies for coastal areas in China. To this end, using domestic high-resolution remote sensing data of 15 days (i.e., one cycle), as well as the iteratively reweighted multivariate alteration detection (IR-MAD) algorithm combined with visual interpretation, this study extracted patches reflecting 2020—2023 changes along the coasts of 11 provinces and cities in the Chinese mainland. Accordingly, this study analyzed their spatiotemporal characteristics, landscape patterns, and spatial correlation. The results indicate distinct directional changes in the patches. The patches reflecting changes from sea enclosure to reclamation exhibited the largest areas across various investigated areas. Except for Hainan Province, the area of this type of patches exceeded 1 000 km2. The proportions of patches reflecting different types of changes gradually tended to be balanced. In the winter of 2022, the proportion of patches showing changes in the reclamation dropped below 50% for the first time. The aggregation degree of patches reflecting various types of changes showed increasing trends, suggesting that patches reflecting various changes will become more concentrated in the future. The centroids of these patches of various regions shifted in varying directions, and these patches exhibited significant spatial correlation within a 20 km range.

       

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