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Rapid urbanization has seriously interfered with the carbon sink function of forests, and has even led to an increased risk of forest carbon imbalance. It is important to explore the regional carbon compensation mechanism and zoning optimization path based on forest carbon accounting to achieve the “dual carbon” goal and sustainable forest management in Fujian Province. Based on remote sensing and GIS technologies, this study measured forest carbon emissions and carbon sequestration of each county in Fujian Province, revealed spatial and temporal evolution of forest carbon budget during the period from 2000 to 2020, and calculated carbon compensation value of each county, so as to realize scientific accounting of forest carbon compensation, and then explored zoning optimization pathways of forest carbon compensation in Fujian Province. The results show the following: (1) From 2000 to 2020, the forest carbon budget in Fujian Province as a whole showed a spatial pattern of “coastal deficit, northwest surplus”, with obvious spatial imbalance characteristics, and showed a high growth trend of net carbon sequestration. (2) From 2000 to 2020, the average carbon compensation rate in Fujian Province was 7.92, and compensation zones were mainly concentrated in the economically developed southeast coastal regins such as Fuzhou, Quanzhou, Xiamen, Zhangzhou, and Putian, while compensation-receiving zones were mainly concentrated in northwestern mountainous areas such as Nanping, Ningde, and Longyan, which had a high forest coverage rate. (3) From 2000 to 2020, there was a significant difference in growth rates of compensation amounts and compensation-receiving amounts in Fujian Province. The cumulative increase in compensation amounts was 322.82%, while the cumulative increase in compensation-receiving amounts was only 17.5%. (4) Based on priority levels, the counties in Fujian Province are classified into six types of forest carbon compensation zones—potential compensation zones, secondary compensation zones, priority compensation zones, potential compensation-receiving zones, secondary compensation-receiving zones and priority compensation-receiving zones—and optimization paths of differentiated zones are explored. Full article

Traditional emergency reconnaissance UAV nest deployment methods face limitations such as blind coverage, delayed response, single coverage targets, and undifferentiated regional priorities. This paper proposes an optimized deployment approach that maximizes response satisfaction and regional coverage, achieving comprehensive coverage while avoiding resource waste and blind zones. UAV nest location needs to consider several factors, including UAV nest coverage, distribution of mandatory coverage areas, scope of critical areas, and various constraints. Mandatory coverage areas are disaster-prone zones identified from historical data, requiring focused reconnaissance. Critical areas are regions with high population density and critical infrastructure concentration. Constraints contain the nest coverage radius constraints, surplus coverage constraints, economic cost constraints, nest distance constraints, nest synergy constraints, and regional boundary constraints. We developed an improved multi-dimensional ant colony optimization algorithm tailored to the problem characteristics, which incorporates multi-dimensional pheromones representing coverage potential, cost efficiency, and spatial constraints, along with adaptive updating and dynamic selection mechanisms for effective problem-solving. This paper takes Nanjing, Jiangsu Province as an analysis case. And the solution achieved 100% regional coverage, redundant coverage of critical zones, and seamless inter-nest collaboration. Sensitivity analysis confirmed the model’s robustness and effectiveness under varying coverage radius and budget conditions. Full article