Popularity influence mechanism of coastal spaces in urban areas: Insights from multi-modal large language models

Cities, Год журнала: 2025, Номер 161, С. 105909 - 105909

Опубликована: Апрель 2, 2025

Язык: Английский

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The Protected Areas System Policy Enhances Habitat Quality Conservation Effectiveness in Dongting Lake Eco-Economic Zone

Journal of Cleaner Production, Год журнала: 2025, Номер unknown, С. 145425 - 145425

Опубликована: Апрель 1, 2025

Язык: Английский

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Characteristics of Ecosystem Services in Megacities Within the Yellow River Basin, Analyzed Through a Resilience Perspective: A Case Study of Xi’an and Jinan

Sustainability, Год журнала: 2025, Номер 17(8), С. 3371 - 3371

Опубликована: Апрель 10, 2025

Megacities in developing countries are still undergoing rapid urbanization, with different cities exhibiting ecosystem services (ESs) heterogeneity. Evaluating ESs among various and analyzing the influencing factors from a resilience perspective can effectively enhance ability of to deal react quickly risks uncertainty. This approach is also crucial for optimizing ecological security patterns. study focuses on Xi’an Jinan, two important megacities along Yellow River China. First, we quantified four both cities: carbon storage (CS), habitat quality (HQ), food production (FP), soil conservation (SC). Second, analyzed synergies trade-offs between these using bivariate local spatial autocorrelation Spearman’s rank correlation coefficient. Finally, conducted driver analysis Geographic Detector. Results: (1) The temporal distribution Jinan quite different, but show lower ES levels urban core area. (2) showed strong synergistic effect. Among them, CS-HQ had strongest synergy 0.93. In terms space, north dominated by low–low clustering, while south high–high clustering. FP-SC trade-off effect −0.35 2000, which gradually weakened over time was mainly distributed northern area city where cropland construction were concentrated. (3) Edge density, patch NDVI have greatest influence CS Jinan. DEM, slope, density HQ. Temperature, edge impact temperature FP cities. SC. Landscape fragmentation has great CS, HQ, SC Due insufficient research data, this focused only middle reaches River. However, results provide new solving problem regional sustainable development directions ideas follow-up field.

Язык: Английский

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Evaluation of Ecosystem Service Capacity Using the Integrated Ecosystem Services Index at Optimal Scale in Central Yunnan, China

Ecology and Evolution, Год журнала: 2025, Номер 15(4)

Опубликована: Апрель 1, 2025

Understanding and quantifying the dynamic features of local ecosystem services (ESs) integrating diverse assessment results form crucial foundations for regional ES management. However, existing methods objectively evaluating multiple ESs remain limited. Consequently, this research evaluates four key based on InVEST RUSLE models in Central Yunnan Province (CYP)-from 2000 to 2020: water yield (WY), carbon storage (CS), habitat quality (HQ), soil conservation (SC). It then constructs an Integrated Ecosystem Service Index (IESI) using principal component analysis (PCA). Additionally, study explores factors driving spatial divergence by employing optimal parameter-based geographical detector model (OPGD) at scale. The indicated that (1) IESI was effectively applied CYP could quantitatively comprehensively integrate ESs. (2) During period, showed increasing trends WY, HQ, SC, while CS a decreasing trend. (3) during period exhibited trend initially increasing. average values were 0.7338 2000, 0.6981 2005, 0.6947 2010, 0.6650 2015, 0.6992 2020. (4) A 4500 m × grid identified as scale detecting comprehensive service (CES) CYP, relief degree land surface (RDLS), slope, NDVI top three drivers q-values. This offers more scientific effective method CES. also provides analytical tool balancing use competition assessing effectiveness policy implementation.

Язык: Английский

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Assessment of coupling coordination and spatial distribution characteristics between urbanization and ecosystem health in the Yellow River Basin

Land Use Policy, Год журнала: 2025, Номер 154, С. 107572 - 107572

Опубликована: Апрель 21, 2025

Язык: Английский

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Utilizing Deep Learning and Spatial Analysis for Accurate Forest Fire Occurrence Forecasting in the Central Region of China

Forests, Год журнала: 2024, Номер 15(8), С. 1380 - 1380

Опубликована: Авг. 7, 2024

Forest fires in central China pose significant threats to ecosystem health, public safety, and economic stability. This study employs advanced Geographic Information System (GIS) technology Convolutional Neural Network (CNN) models comprehensively analyze the factors driving occurrence of these fire events. A predictive model for forest occurrences has been developed, complemented by targeted zoning management strategies. The key findings are as follows: (i) Spatial analysis reveals substantial clustering spatial autocorrelation points, indicating high-density areas occurrence, primarily Hunan Jiangxi provinces, well northeastern region. underscores need tailored prevention approaches. (ii) prediction region demonstrates exceptional accuracy, reliability, power. It achieves outstanding performance metrics both training validation sets, with an accuracy 86.00%, precision 88.00%, recall 87.00%, F1 score 87.50%, AUC value 90.50%. (iii) Throughout year, varies location season. Low-occurrence periods observed summer winter, particularly Hubei due moderate weather conditions, agricultural practices, reduced outdoor activities. However, spring autumn also present localized risks uneven rainfall dry climates. provides valuable insights into dynamics China, offering a solid framework proactive policy formulation effectively mitigate impacts

Язык: Английский

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Assessment of ecological resilience and its response mechanism to land spatial structure conflicts in China’s Southeast Coastal Areas

Ecological Indicators, Год журнала: 2024, Номер 170, С. 112980 - 112980

Опубликована: Дек. 16, 2024

Язык: Английский

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