Impact of multi-scenario land-use changes on habitat quality evolution in the Yangtze River economic belt

Frontiers in Environmental Science, Journal Year: 2025, Volume and Issue: 12

Published: Jan. 9, 2025

Ecosystems worldwide are facing significant challenges resulting from the dual pressures of global climate change and human activities, particularly in terms biodiversity loss associated with land-use change. Focusing on Yangtze River Economic Belt (YREB), this study uses System Dynamics (SD) - Patch-generating Land Use Simulation (PLUS) model to simulate development under different scenarios shared socio-economic pathways (SSPs) representative concentration (RCPs) 2030 2050. Furthermore, InVEST is applied evaluate changes habitat quality (HQ) over period 2000 A hotspot analysis further highlights spatial heterogeneity HQ within YREB. The showed that pattern YREB 2020 2050 will be dominated by cropland eastern region, grassland north-west, forest land central southern regions, a steady increase built-up east. index exhibits gradual east west, ultimately declining 0.726 SSP585 scenario for This trend reflects moderate degradation (HD), degree shifting towards lower higher proportions HQ. Spatial reveals region identified as cold spot, categorized non-significant, while western emerges hot where exceeds 40%. These findings offer scientific foundation promoting high-quality enhancing conservation

Language: Английский

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The Role of Smart Grid Technologies in Urban and Sustainable Energy Planning

Energies, Journal Year: 2025, Volume and Issue: 18(7), P. 1618 - 1618

Published: March 24, 2025

Traditional centralized energy grids struggle to meet urban areas’ increasingly complex demands, necessitating the development of more sustainable and resilient solutions. Smart microgrids offer a decentralized approach that enhances efficiency, facilitates integration renewable sources, improves resilience. This study follows systematic review approach, analyzing literature published in peer-reviewed journals, conference proceedings, industry reports between 2011 2025. The research draws from academic publications institutions alongside regulatory reports, examining actual smart microgrid deployments San Diego, Barcelona, Seoul. Additionally, this article provides real-world case studies New York London, showcasing successful unsuccessful deployments. Brooklyn Microgrid demonstrates peer-to-peer trading, while London faces regulations funding challenges its systems. paper also explores economic policy frameworks such as public–private partnerships (PPPs), localized markets, standardized models enable adoption at scale. While PPPs provide financial infrastructural support for deployment, they introduce stakeholder alignment compliance complexities. Countries like Germany India have successfully used development, leveraging low-interest loans, government incentives, mechanisms encourage innovation technologies. In addition, examines new trends utilization AI quantum computing optimize energy, climate design before outlining future agenda focused on cybersecurity, decarbonization, inclusion technology. Contributions include modular scalable framework, innovative hybrid storage systems, performance-based model suited environment. These contributions help fill gap what is possible today needed systems create foundation cities next century.

Language: Английский

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Impact of Habitat Quality Changes on Regional Thermal Environment: A Case Study in Anhui Province, China

Sustainability, Journal Year: 2024, Volume and Issue: 16(19), P. 8560 - 8560

Published: Oct. 2, 2024

Biodiversity degradation and loss represent critical global challenges, primarily driven by the urban heat island effect, which results from elevated surface temperatures. As urbanization climate change continue to progress, these phenomena have a profound impact on both habitats human residential environments. This study focuses Anhui Province as case systematically investigate effects of changes in habitat quality (HQ) evolution regional thermal environment. The objective is provide scientific basis for addressing environment issues promoting biodiversity conservation. paper employs InVEST-HQ model analyze HQ 2000 2020 integrates temperature data assess response variations show that: (1) From 2020, index exhibited general decline, characterized pronounced spatial heterogeneity, with lower values observed northern regions higher southwestern southern areas. (2) Concurrently, relative continued rise, particularly central areas such Hefei, where increase impermeable surfaces has facilitated expansion high-temperature zones. (3) Different types had distinctly varying environments: classified poor or worse were associated noticeable warming effects, while those categorized good excellent significant cooling effects. (4) contribution ranged −0.2 0.3, indicating that positively contributed environments, whereas exerted negative contribution. City-level analyses revealed cities Suzhou, Chizhou, Wuhu, Anqing, Xuancheng, Lu’an positive contributions temperature, including Bengbu, Fuyang, Chuzhou, Huaibei, Tongling, Ma’anshan, Hefei demonstrated contributions. provides valuable insights optimizing distribution cold islands ecological sustainable development.

Language: Английский

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Advancing Urban Resilience Amid Rapid Urbanization: An Integrated Interdisciplinary Approach for Tomorrow’s Climate-Adaptive Smart Cities—A Case Study of Wuhan, China

Smart Cities, Journal Year: 2024, Volume and Issue: 7(4), P. 2110 - 2130

Published: Aug. 1, 2024

This research addresses the urgent challenges posed by rapid urbanization and climate change through an integrated interdisciplinary approach combining advanced technologies with rigorous scientific exploration. The comprehensive analysis focused on Wuhan, China, spanning decades of meteorological land-use data to trace extreme trajectories reveal intricate temporal spatial patterns. Employing innovative 360° radial Fibonacci geometric growth framework, study facilitated a meticulous dissection urban morphology at granular scales, establishing model that combined fixed mobile observational techniques uncover climatic shifts transformations. Geographic information systems computational fluid dynamics were pivotal tools used explore interplay between structures their environments. These analyses elucidated nuanced impact diverse morphosectors local conditions. Furthermore, genetic algorithms harnessed distill meaningful relationships from extensive collected, optimizing arrangements enhance resilience sustainability. pioneering not only illuminates complex ecosystems but also offers transformative insights for designing smarter, more adaptable cities. findings underscore critical role green spaces in mitigating heat island effects. highlights imperative sustainable planning address multifaceted 21st century, promoting long-term environmental sustainability health, particularly context tomorrow’s climate-adaptive smart

Language: Английский

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Advanced Digital Technologies in the Post-Disaster Reconstruction Process—A Review Leveraging Small Language Models

Buildings, Journal Year: 2024, Volume and Issue: 14(11), P. 3367 - 3367

Published: Oct. 24, 2024

Post-disaster reconstruction of the built environment represents a key global challenge that looks set to remain for foreseeable future, but it also offers significant implications future sustainability and resilience environment. The purpose this research is explore current applications advanced digital/Industry 4.0 technologies in post-disaster (PDR) process with view improving its effectiveness efficiency extant literature from Scopus database on identified described. In novel review approach, small language models are used classification filtering technology-related articles. A qualitative content analysis then carried out understand extent which Industry applied practice, mapping their specific phases PDR identifying dominant trends technology deployment. study reveals rapidly evolving landscape technological innovation transformative potential enhancing efficiency, effectiveness, rebuilding efforts, including GIS, remote sensing, AI, BIM. Key include increasing automation data-driven decision-making, integration multiple 4.0/digital technologies, growing emphasis incorporating community needs local knowledge into plans. highlights need address challenges, such as developing interoperable platforms, addressing ethical using AI big data, exploring contribution sustainable practices.

Language: Английский

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Disaster Management Based on Biodiversity Conservation Using Remote Sensing Data Analysis Using Machine Learning Model

Remote Sensing in Earth Systems Sciences, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 8, 2025

Language: Английский

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Disaster Risk Reduction and Management With Emerging Technologies

IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 71 - 110

Published: April 17, 2025

This chapter explores the role of emerging technologies in disaster risk reduction and management (DRRM), focusing on integration Internet Things (IoT), Artificial Intelligence (AI), Data Analytics to enhance urban resilience. IoT-enabled sensors smart infrastructure provide real-time data for early warning systems, monitoring, emergency response. AI-driven predictive analytics enhances assessment, resource allocation, post-disaster recovery, while enables integration, visualization, scenario planning. Despite their potential, challenges like quality, scalability, cybersecurity, ethical concerns must be addressed. The future Disaster Risk Reduction Management (DRRM) will depend incorporation modern technology, increased public involvement, global cooperation, allowing cities develop more intelligent, secure, sustainable settings.

Language: Английский

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A systematic review of factors, data sources, and prediction techniques for earlier prediction of traffic collision using AI and machine Learning

Multimedia Tools and Applications, Journal Year: 2024, Volume and Issue: unknown

Published: July 13, 2024

Abstract The prevalence of road traffic collisions is a pressing issue both worldwide and within the United States. consequences these incidents are severe, resulting in loss life, reduced productivity, other socio-economic implications that demand immediate attention. To effectively address this problem, conducting an extensive literature review crucial to identify various causes complex interdependencies between them. Addressing challenge necessitates targeted exploration its multifaceted their interrelations through review, incorporating latest advancements machine learning deep techniques. However, lack consensus on datasets prediction techniques hinders development accurate, location-specific collision predictions. By meticulously analyzing factors data sources leveraging state-of-the-art ML DL approaches, paper endeavors forge pathway toward developing precise, location-adapted predictions for collisions, thereby contributing significantly discourse long-term preventative strategies.

Language: Английский

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Determining geo-disaster chains probabilities and disaster mitigation mode: A meta-analytical perspective

Ecological Indicators, Journal Year: 2024, Volume and Issue: 163, P. 112074 - 112074

Published: May 2, 2024

In a harsh geological environment, different geo-disasters might co-occur or be in chain sequence. Currently, existing research related fields documents numerous instances of disaster chains and responses, which provided this study with important materials for determining probability summarized the prevention mitigation (DPM) mode. study, through depth geo-disaster cases DPM cases, enabled mode analysis summary. We take case as an example represent 20 typical by data fusion structuring 139 cases.The assessment is crucial risk management regional resilience. introduced Bayesian network (BN) model to describe process formation map structure assess joint chains. The BN results showed that longer length, smaller occurring. Among these, "Collapses-landslides-debris flows–barrier lakes–flash floods" lowest (0.069). Through sensitivity analysis, it found precipitation most sensitive factor development geo-disaster. Interpretive structural modeling (ISM) employed examine index system across three key aspects: emergency preparation, response, recovery, conceptualized interaction among these components. ISM government policy intervention scientific measures can effectively reduce losses caused This combined occurrence response process, determined entire characterization from understanding helped vulnerabilities disasters.

Language: Английский

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Enhancing Disaster Management by leveraging Smart Cities Technologies

Published: May 2, 2024

Language: Английский

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