As cities expand, many old towns face the threat of being renovated or demolished. In recent years, the drawbacks of extensive urban renewal have become increasingly apparent, and the focus of urban development is gradually shifting from efficiency to quality. This study aims to combine urban renewal with emerging technologies to address the dilemma between efficiency and quality in urban renewal. The study found that algorithm models based on graph theory, topology, and shortest path principles neglect the influence of internal states and visual features on pedestrian activity, resulting in lower simulation accuracy. Although incorporating internal states and visual features into the core of the algorithm further improved the simulation accuracy, the model operates in a 3D environment with lower efficiency. To address the problems of insufficient simulation accuracy and low efficiency, this study proposes a dynamic pedestrian activity model based on a multi-agent system and incorporating visual features. The model simulates pedestrian daily activity paths using pheromones and virtual sensors as the core, and it was found that using Visibility Graph Analysis could accurately divide pheromones in the environment, thus obtaining more accurate simulation results. Subsequently, based on the optimized pedestrian model’s agent activity rules and dynamic pheromone theory, a model for automatically generating road paving in urban renewal projects was developed, and the generated results were verified for their rationality through design practice. This technology can effectively promote urban renewal and the preservation of historic neighborhoods, providing technical support for achieving sustainable urban development.

Based on the theory of space syntax, this study quantitatively analyzes the landscape space of Baosteel Zhanjiang Steel Co. Ltd., which is constrained by epidemic preventive measures and steel plant safety production requirements in the post-epidemic age. Space syntax has the benefits of decreasing research expenses, boosting analytical efficiency, assessing space use efficiency, minimizing environmental interference, and addressing epidemic prevention demands.

Based on the theory of space syntax, this research conducts a quantitative study on the four stages of Zhanjiang urban spatial organization system, and draws the urban evolution process. This study found that the development strategy of different periods has a huge impact on the urban development. It determines the structural basis of the original urban space and creates strong development inertia. According to these research results, it can provide an effective theoretical reference for the future spatial expansion of the city.

Mangroves, as one of the most efficient carbon—sequestering ecosystems globally, provide critical ecological services including coastal protection, water purification, and biodiversity conservation. This study integrates remote sensing and ecological modeling to assess the spatial–temporal dynamics and restoration potential of mangroves in coastal Guangdong, China, under alternative socioeconomic pathways. Using Sentinel‐2 imagery and hybrid classification, we mapped the 2020 mangrove distribution with high accuracy, estimating a total area of 110.28 km ² . The MaxEnt model, driven by 37 climatic, hydrological, topographic, soil, and land use/land cover (LUCC) variables, identified a maximum potential habitat area of 1908 km ² . However, when LULC constraints were introduced, the suitable area decreased to 1221 km ² , highlighting LULC as a major limiting factor. Variable importance analysis revealed that LULC (38.2%), annual temperature range (20.8%), and distance to coastline (11.7%) jointly explained over 70% of the variation in habitat suitability, underscoring the interplay of anthropogenic and natural drivers. By coupling MaxEnt with LULC projections from the Patch‐generating Land Use Simulation (PLUS) model under three SSP scenarios for 2040, we further identified dominant land‐use constraints and generated multi‐scenario distribution predictions. Results suggest that the SSP126 (low‐emission) pathway provides the greatest restoration opportunities, whereas SSP585 (high‐emission) favors limited climatic suitability gains but widespread habitat loss due to urban expansion. Our findings emphasize that integrating ecological niche modeling with advanced LULC simulation provides a novel decision‐support framework that links potential habitat prediction with realistic land‐use governance. The study not only identifies high‐priority restoration and conservation zones but also offers actionable strategies—such as pond‐to‐forest conversion, hydrological connectivity restoration, and zoning‐based adaptive management—to reconcile coastal development with long‐term ecosystem resilience.

Not-yet-known not-yet-known not-yet-known unknown Mangrove ecosystems are among the most effective natural environments for carbon fixation and sequestration, playing a critical role in coastal protection, water quality maintenance, and providing habitats for marine life, which are essential for environmental conservation and climate regulation. This study utilized Sentinel-2 satellite imagery to map the distribution of mangroves along the coast of Guangdong Province, China, where the existing area was found to be 110.28 km². Subsequently, the Maximum Entropy (MaxEnt) model was employed to predict potential mangrove distribution areas, estimated at 1756 km². By analyzing both current and potential distribution maps, the carbon sequestration of the coastal mangroves in Guangdong were estimated at 131.65 ± 62.63 Mg C yr⁻¹ and 1958.41 ± 921.61 Mg C yr⁻¹, respectively. Environmental variables, soil physical properties, topographical data, marine variables, and land type data were used in the MaxEnt model to identify the key factors limiting mangrove distribution. The study found that the primary constraints on the potential distribution of mangroves along the Guangdong coast were the precipitation of the driest month (bio14) and the annual temperature range (bio7). Although the carbon sequestration capacity of Guangdong’s coastal mangroves is below the global average, the extensive potential distribution area suggests that strategic ecological restoration could significantly enhance regional carbon sequestration capacity while providing a wealth of ecosystem services and mutual benefits for the coastal area.