This paper proposes a method for automatically monitoring and analyzing the evolution of complex geographic objects. The objects are modeled as a spatiotemporal graph, which separates filiation relations, spatial relations, and spatiotemporal relations, and is analyzed by detecting frequent sub-graphs using constraint satisfaction problems (CSP). The process is divided into four steps: first, the identification of complex objects in each satellite image; second, the construction of a spatiotemporal graph to model the spatiotemporal changes of the complex objects; third, the creation of sub-graphs to be detected in the base spatiotemporal graph; and fourth, the analysis of the spatiotemporal graph by detecting the sub-graphs and solving a constraint network to determine relevant sub-graphs. The final step is further broken down into two sub-steps: (i) the modeling of the constraint network with defined variables and constraints, and (ii) the solving of the constraint network to find relevant sub-graphs in the spatiotemporal graph. Experiments were conducted using real-world satellite images representing several cities in Saudi Arabia, and the results demonstrate the effectiveness of the proposed approach.

翻译：本文提出一种自动监测与分析复杂地理对象演化的方法。将对象建模为时空图，该图区分了派生关系、空间关系及时空关系，并通过使用约束满足问题（CSP）检测频繁子图进行分析。该方法分为四个步骤：首先，识别每幅卫星图像中的复杂对象；其次，构建时空图以建模复杂对象的时空变化；第三，创建待检测子图作为基础时空图的子集；第四，通过检测子图并求解约束网络来分析时空图，以确定相关子图。最后一步进一步分解为两个子步骤：（i）通过定义变量和约束对约束网络进行建模；（ii）求解约束网络以在时空图中寻找相关子图。实验采用代表沙特阿拉伯多个城市的真实卫星图像进行，结果验证了所提方法的有效性。