DETERMINATION OF POTENTIAL LOCATIONS FOR SETTLEMENT DEVELOPMENT BASED ON LAND CARRYING CAPACITY USING CELLULAR AUTOMATA (Case Study: Karangnunggal Subdistrict)

Engineering notes

Key topics: autonomous driving, planning, control. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

<ns5:p>Abstract Background Karangnunggal has been designated as the prospective capital of the Proposed New Autonomous Region of South Tasikmalaya Regency, a status expected to accelerate population growth and settlement land demand in an area that remains prone to landslides and earthquakes. Determining suitable settlement development locations is therefore critical to keeping this growth within the limits of land carrying capacity. Methods This study determined potential locations for settlement development in Karangnunggal Subdistrict by integrating land carrying capacity analysis with Cellular Automata (CA) modeling through the MOLUSCE plugin in QGIS. The stages included land capability analysis based on nine Land Capability Units (LCU), land carrying capacity analysis following a spatial planning approach (a 60:40 ratio between built-up and open space), and an Artificial Neural Network (ANN)-based CA simulation using driving and constraint variables to project land cover up to 2045. Results Land capability in Karangnunggal Subdistrict is dominated by the fairly high and high classes, with a potential land carrying capacity zone covering 9,154.36 Ha, or 60% of the total subdistrict area. The CA model demonstrated high reliability, indicated by a % of Correctness of 97.17529% and an overall Kappa of 0.96743. The projection shows settlement area increasing from 1,248.39 Ha (2015) to 1,770.39 Ha (2020) and reaching 2,617.95 Ha by 2045, with Karangnunggal Village as the center of highest growth, consistent with its function as the Proposed New Autonomous Region government center. Conclusions This study provides a more adaptive and controlled direction for settlement development in a disaster-prone area and offers input for regional spatial policy that balances development with environmental preservation.</ns5:p>

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