Evolution and Predictive Analysis of Spatiotemporal Patterns of Habitat Quality in the Turpan–Hami Basin DOI Creative Commons
Yaqian Li, Yongqiang Liu, Yan Qin

et al.

Land, Journal Year: 2024, Volume and Issue: 13(12), P. 2186 - 2186

Published: Dec. 14, 2024

The expansion of urban areas and unsustainable land use associated with human activities have brought about a decline in habitat quality (HQ), especially arid regions fragile ecosystems. A precise prediction changes across different scenarios is crucial for the sustainable maintenance ecological diversity. In this article, InVEST model was employed to assess both degradation levels habitats Turpan–Hami Basin (THB) spanning 1990~2020. Additionally, InVEST-PLUS coupling forecast conditions under three 2050. Specifically, it involved comparison spatial distribution HQ natural development (ND) scenarios, town (UD) protection (EP) along analysis hot spots 1990~2050. outcomes revealed following: (1) primary THB categorized as unused land, alongside notable expansions cultivated grassland, built-up land. Conversely, there considerable observed forests, water bodies, (2) within exhibited evident clustering characteristics. Between 1990 2020, low accounted over 85%, unchanged constituted 88.19%, experiencing deteriorated comprised approximately 5.02%, displaying improved encompassed around 6.79%. (3) Through ND, UD, EP 2050, that average scenario ranked highest, exhibiting lowest degree on average. This indicates most advantageous preserving HQ. Conclusively, research provides valuable viewpoints making decisions aimed at enhancing ecologically regions.

Language: Английский

Understanding spatiotemporal changes and influencing factors in the habitat quality of coastal waters: A case study of Jiangsu Province, China (2006–2020) DOI Creative Commons
Zhou Chen, Yan Jing Chen, Haifeng Zhang

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 170, P. 113125 - 113125

Published: Jan. 1, 2025

Language: Английский

Citations

1
Artificial Intelligence for Computational Remote Sensing: Quantifying Patterns of Land Cover Types around Cheetham Wetlands, Port Phillip Bay, Australia DOI Creative Commons
Polina Lemenkova

Journal of Marine Science and Engineering, Journal Year: 2024, Volume and Issue: 12(8), P. 1279 - 1279

Published: July 29, 2024

This paper evaluates the potential of using artificial intelligence (AI) and machine learning (ML) approaches for classification Landsat satellite imagery environmental coastal mapping. The aim is to identify changes in patterns land cover types a area around Cheetham Wetlands, Port Phillip Bay, Australia. scripting approach Geographic Resources Analysis Support System (GRASS) geographic information system (GIS) uses AI-based methods image analysis accurately discriminate types. Four ML algorithms are applied, tested compared supervised classification. Technical based on ‘r.learn.train’ module, which employs scikit-learn library Python. methodology includes following algorithms: (1) random forest (RF), (2) support vector (SVM), (3) an ANN-based multi-layer perceptron (MLP) classifier, (4) decision tree classifier (DTC). AI demonstrated robust results classification, with highest overall accuracy exceeding 98% reached by SVM RF models. presented GRASS GIS detected southern Victoria over period 2013–2024. From our findings, use offers effective solutions monitoring change detection multi-temporal RS data. have applications wetland monitoring, urban planning Earth observation

Language: Английский

Citations

4
Tourism impacts on marine and coastal ecosystem services: A systematic review DOI Creative Commons
Eglė Baltranaitė, Miguel Inácio, Luís Valença Pinto

et al.

Geography and sustainability, Journal Year: 2025, Volume and Issue: unknown, P. 100277 - 100277

Published: Feb. 1, 2025

Language: Английский

Citations

0
Assessing and predicting habitat quality under urbanization and climate pressures DOI
Zahra Parvar, Abdolrassoul Salmanmahiny

Journal for Nature Conservation, Journal Year: 2025, Volume and Issue: unknown, P. 126903 - 126903

Published: March 1, 2025

Language: Английский

Citations

0
Digital twin comprehensive models: a study of ancient tree ecological environment quality assessment based on a cyber-physical system DOI
Yansheng Chen, Huagang Huang, Jie Li

et al.

Environmental Monitoring and Assessment, Journal Year: 2025, Volume and Issue: 197(4)

Published: April 1, 2025

Language: Английский

Citations

0
Spatio‐Temporal Variations of Habitat Quality Under 8 SSP‐RCP Scenarios in China DOI

Yuke Feng,

Shiyan Zhai, Genxin Song

et al.

Journal of Geophysical Research Biogeosciences, Journal Year: 2024, Volume and Issue: 129(7)

Published: June 29, 2024

Abstract Habitat quality is a key expression of ecosystem ability and the basis for effective species conservation regional ecological environment improvement. However, most studies have focused on assessing habitat over historical periods, ignoring influence coupled future development paths climate change. The present study addresses this issue by developing spatial‐temporal variation analysis framework in China, which integrates Integrated Valuation Ecosystem Services Trade‐offs (InVEST) model with eight Earth system scenarios (SSP‐RCP). results showed that from 2020 to 2100, under five (SSP2‐4.5, SSP3‐7.0, SSP4‐6.0, SSP5‐3.4, SSP5‐8.5), was generally stable high, while three (SSP1‐1.9, SSP1‐2.6, SSP4‐3.4), it decreased. SSP2‐4.5 scenario significantly better than SSP4‐3.4 scenario. In all scenarios, influences different patterns China's ecologically fragile areas were obvious serious. 2030 2060, spatial distribution degradation had similar characteristics. High values mostly distributed east Heihe‐Tengchong Line, low mainly arid zone. mean ranged between 0.0226 0.0302, degree relatively light. index 0.5120–0.5376, indicating overall at medium level. This provides potential protection baseline China based an important reference sustainable development.

Language: Английский

Citations

1
Simulation and Forecast of Coastal Ecosystem Services in Jiaodong Peninsula Based on SSP-RCP Scenarios DOI Creative Commons

Wenhui Guo,

Ranghui Wang,

Fanhui Meng

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(19), P. 3614 - 3614

Published: Sept. 27, 2024

This study simulated the spatiotemporal changes in coastal ecosystem services (ESs) Jiaodong Peninsula from 2000 to 2050 and analyzed driving mechanisms of climate change human activities with respect ESs, aiming provide policy recommendations that promote regional sustainable development. Future land use were forecast based on scenarios Coupled Model Intercomparison Project Phase 6 (CMIP6). The Integrated Valuation Ecosystem Services Tradeoffs (InVEST) model was used assess ESs such as water yield (WY), carbon storage (CS), soil retention (SR), habitat quality (HQ). Key drivers identified using Structural Equation Modeling (SEM). Results demonstrate following: (1) High WY are concentrated built-up areas, while high CS, HQ, SR mainly found mountainous hilly regions extensive forests grasslands. (2) By 2050, CS HQ will show a gradual degradation trend, annual variations closely related precipitation. Among different scenarios, most severe ES occurs under SSP5-8.5 scenario, SSP1-2.6 scenario shows relatively less degradation. (3) SEM analysis indicates urbanization leads continuous declines topographic factors controlling spatial distribution four ESs. Climate can directly influence SR, their impact is stronger higher activity intensity than those lower intensity. (4) Considering combined effects we recommend future development decisions be made rationally control give greater consideration context change.

Language: Английский

Citations

1
The “Blue” Habitat of Urban & Suburban Areas and approaches for its biodiversity research: A scoping review DOI Creative Commons

Pingyao Sun,

Mingze Chen, Jing-Yi Chen

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 373, P. 123567 - 123567

Published: Dec. 14, 2024

This article explores recent research initially driven by interest in studying the "Blue" Habitat of Urban and Suburban Areas (BHUS), focusing on water-related ecosystems. BHUS, encompassing a wide range aquatic habitats, is crucial to ecosystem health but increasingly threatened biodiversity loss resulting from climate change, land-use expansion, unsustainable practices. Through scoping review 93 peer-reviewed studies, this establishes framework classify BHUS types, identify target species, analyze diverse latest techniques water system research. The main themes for environmental aspects these blue habitats are highlighted, along with urgent need address urban conservation. Findings reveal that systems biologically rich present unique challenges due their variability dynamic, interconnected nature. While there growing recognition consider human influence, many studies overlook complex, adaptive nature as an integrated system. gives insight into establishing comprehensive integrating methodologies technologies specialized biodiversity, emphasizing role advancing interdisciplinary collaboration between urbanism ecology. These approaches essential support sustainable development addresses conservation needs mitigates urbanization's impacts BHUS. Further should explore how spatial planning strategies can more effectively integrate strengthen within global urbanization context.

Language: Английский

Citations

1
Offshore habitats of endangered large mobile species in the western Yellow Sea: Quality status under shipping pressure DOI
Xuezhong Fan, Qinglong Zhang,

Qian Wu

et al.

Marine Pollution Bulletin, Journal Year: 2024, Volume and Issue: 204, P. 116565 - 116565

Published: June 5, 2024

Language: Английский

Citations

0
Adaptive Integrated Coastal Zone Planning: History, Challenges, Advances, and Perspectives DOI

Xinyi Wang,

Fenzhen Su,

Xuege Wang

et al.

Chinese Geographical Science, Journal Year: 2024, Volume and Issue: 34(4), P. 599 - 617

Published: July 17, 2024

Language: Английский

Citations

0