ABSTRACT Characterizing landscape patterns and revealing their underlying processes are critical for studying climate change and environmental problems. Previous methods for mapping land cover changes largely focused on the classification of remote sensing images. Therefore, they could not provide information about the evolutionary process of land cover changes. In this paper, we developed a spatiotemporal structural graph (STSG) technique for a comprehensive analysis of land cover changes. First, a land cover neighborhood graph was generated for each snapshot to quantify the spatial relationship between adjacent land cover objects. Then, an object-based temporal tracking algorithm was designed to monitor the temporal changes between land cover objects over time. Finally, land cover evolutionary trajectories, pixel-level land cover change trajectories, and node-wise connectivity changes over time were characterized. We applied the proposed method to analyze land cover changes in Suffolk County, New York from 1996 to 2010. The results demonstrated that STSG can not only characterize and visualize detailed land cover changes spatially but also maintain the temporal sequence and relations of land cover objects in an integrated space-time environment. The proposed STSG provides a useful framework for analyzing land cover changes and can be adapted to characterize and quantify other spatiotemporal phenomena.

中文翻译：

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用于表征土地覆盖变化的时空结构图

摘要 表征景观模式并揭示其潜在过程对于研究气候变化和环境问题至关重要。以前绘制土地覆盖变化的方法主要集中在遥感图像的分类上。因此，他们无法提供有关土地覆盖变化演变过程的信息。在本文中，我们开发了一种时空结构图 (STSG) 技术，用于综合分析土地覆盖变化。首先，为每个快照生成土地覆盖邻域图，以量化相邻土地覆盖对象之间的空间关系。然后，设计了一种基于对象的时间跟踪算法来监控土地覆盖对象之间随时间的时间变化。最后，土地覆盖演化轨迹，描述了像素级土地覆盖变化轨迹，以及节点连接随时间的变化。我们应用所提出的方法来分析 1996 年至 2010 年纽约萨福克县的土地覆盖变化。结果表明，STSG 不仅可以在空间上表征和可视化详细的土地覆盖变化，还可以保持土地覆盖对象的时间序列和关系。一个综合的时空环境。拟议的 STSG 为分析土地覆盖变化提供了一个有用的框架，可用于表征和量化其他时空现象。结果表明，STSG不仅可以在空间上表征和可视化详细的土地覆盖变化，而且可以在综合时空环境中保持土地覆盖对象的时间序列和关系。拟议的 STSG 为分析土地覆盖变化提供了一个有用的框架，可用于表征和量化其他时空现象。结果表明，STSG不仅可以在空间上表征和可视化详细的土地覆盖变化，而且可以在综合时空环境中保持土地覆盖对象的时间序列和关系。拟议的 STSG 为分析土地覆盖变化提供了一个有用的框架，可用于表征和量化其他时空现象。