Research on the Coordination Relationship and Zoning Optimization of Territorial Spatial Functions in Southern Karst Regions Based on a Multi-Scale Fusion Model

Land, Journal Year: 2025, Volume and Issue: 14(2), P. 430 - 430

Published: Feb. 19, 2025

Territorial Space (TS) is characterized by its multifunctionality. The identification and management of Spatial Functions (TSFs) across multi-scale crucial for achieving the SDGs. However, previous studies have primarily concentrated on variations in TSFs within administrative or grid units at a single scale, with investigations remaining challenge. This study focuses typical karst region Guangxi province China develops Multi-Scale Fusion model (MSF) assessing employs coupling coordination degree (CCD) to examine relationships. Furthermore, principal component analysis (PCA) used classify various types influencing factors, Revealed Comparative Advantage (RCA) index employed identify primary factors county level. integrates advantage into zoning process. results demonstrate: (1) Ecological function dominant function. At unit production living functions exhibit spatial pattern “high southeast low northwest”, while ecological shows opposite pattern. Under scale fusion, high texture characteristics are more pronounced. (2) slight moderate disorder. Slight disorder widely distributed, predominantly found northwest mountainous regions. In contrast, coordinated relationships frequently observed urban areas. (3) driver can be categorized four categories: Terrain-Population, Agriculture Development, Location-Economy, Non-Agriculture Development. By integrating relationships, six zones delineated. Based this, precise differentiated optimization suggestions proposed promote orderly utilization sustainable development TS.

Language: Английский

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Research on Water Resource Carrying Capacity Assessment and Water Quality Forecasting Based on Feature Selection with CNN-BiLSTM-Attention Model of the Min River Basin

Water, Journal Year: 2025, Volume and Issue: 17(6), P. 824 - 824

Published: March 13, 2025

To achieve a more accurate assessment of water resource carrying capacity (WRCC), the indicators resources, social and ecological environment were selected to construct WRCC system on basis combinatorial assignment method with advantages. Moreover, incorporation key quality influences into predictions facilitated performance predictive models. Adaptive Lasso Regression was used select factors affecting quality, whereas CatBoost algorithm ranked importance by in prediction model. The Convolutional Neural Network-Bidirectional Long Short-Term Memory-Attention (CNN-BiLSTM-Attention) model forecast WQI. research results propose new evaluation method. show that average barrier levels for socio-economic development, 34.97%, 34.93%, 30.10%, respectively. Compared other layers WRCC, obstacle degree layer has always been lower. total sewage treatment, greening coverage built-up areas, per capita green space parks main within Min River Basin. Based factor screening, it can be seen dissolved oxygen is positively correlated watershed, while influencing are negatively Total nitrogen had greatest impact conditions regression coefficient −1.7532. From comparison results, known hybrid make MAE value 45% monitoring points reach minimum, RMSE 35% minimum. percentages remaining models reached lowest values 15% 20% 30%, models, MSE relatively small, which conducive predicting

Language: Английский

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Evaluation and Influencing Factors of Coupling Coordination of “Production–Living–Ecological” Functions Based on Grid Scale: Empirical Experience of Karst Beibu Gulf in Southwest Guangxi, China

Land, Journal Year: 2025, Volume and Issue: 14(3), P. 614 - 614

Published: March 14, 2025

Territorial space (TS) is multifunctional, and exploring the relationships between functions their influencing factors key to achieving sustainable development of territorial space. However, existing research mostly focuses on exploration administrative units, while grid units needs be improved. This paper takes Beibu Gulf Economic Zone (BGEZ) in Guangxi as object, evaluates “Production–Living–Ecological” Functions (PLEFs) using land category scoring method summarizes evolution characteristics its spatial pattern. It analyzes dominant combined revealed comparative advantage index, explores various by introducing a coupling coordination degree model, comprehensively uses Geodetector Geographically Temporally Weighted Regression (GTWR) models analyze spatiotemporal heterogeneity functions. The results indicate that at scale (1) regional dominated ecological space, followed production with living accounting for smallest proportion. Production has decreased, increased, spaces flowing into (2) distribution relatively homogeneous, differentiation most significant. can divided three function-dominant types six function-combination types. (3) Living function primarily disordered functions, production–ecological mainly coordinated. (4) Policy regulation factor affecting functional coordination, scope influence each show significant heterogeneity. study reveals mechanisms temporal TS scale, providing scientific basis efficient use TS.

Language: Английский

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Spatiotemporal Variation and Driving Mechanisms of the Global Production-Living-Ecological Space Coupling Coordination Degree

Land, Journal Year: 2024, Volume and Issue: 13(12), P. 2136 - 2136

Published: Dec. 9, 2024

The coupling coordination degree (CCD) of the production-living-ecological space (PLES) functional index is an indicator regional sustainable development potential. However, previous studies have failed to reveal driving mechanisms CCD PLES on a global scale. Therefore, this study employed model evaluate and spatial regression models measure heterogeneous drivers using multi-source data in 2000, 2010, 2020. results demonstrated that ecological spaces dominated (85%) globally, while living comprised smallest share (3%). was higher than production indices. Further analyses revealed topographic factors were main restricting for PLES; proportion decreased with increasing altitude slope, whereas showed opposite trend. values 2020 0.186, 0.189, 0.198, respectively, showing High generally observed areas dense population industry where human activity systems interact natural ecosystems. formation pattern from joint action socioeconomic factors, pronounced heterogeneity. Our findings can help optimize territorial utilization, improve utilization efficiency, realize goals.

Language: Английский

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