Boundary delineation of the Qi Great Wall National Cultural Park: a data-driven approach combining Geographical Detectors and Explainable AI (SHAP)
Year: 2026
Type: article
Abstract: Scientific boundary delineation is fundamental to the spatial governance of the Qi Great Wall National Cultural Park. However, existing methods often rely on empirical buffering, failing to reveal nonlinear human-land relationships or identify quantitative management thresholds. Taking the Changqing section as a case study, this research establishes a framework integrating the Geographical Detector and Explainable AI (SHAP). First, Kernel Density Estimation (KDE) identified heritage agglomeration to determine the core protection range. Second, the Geographical Detector and SHAP analyzed driving mechanisms, revealing that heritage distribution is highly correlated with “natural adaptation” (elevation) and “human avoidance” (distance to roads). … Consequently, a “rigid core protection zone” (58.7 km2) and a “flexible comprehensive control zone” (181.2 km2) were established. This study achieves a transition from purely “empirical circle drawing” to a hybrid decision-support framework, offering a scientific paradigm for the refined management of linear cultural heritage.
Language: English
Subfield: Archeology
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,165
OpenAlex ID: W7204112189