Spatio-Temporal Evolution and Multi-Scenario Prediction of Ecosystem Carbon Storage in Chang-Zhu-Tan Urban Agglomeration Based on the FLUS-InVEST Model DOI Open Access

Weiyi Sun,

Xianzhao Liu

Sustainability, Год журнала: 2024, Номер 16(16), С. 7025 - 7025

Опубликована: Авг. 16, 2024

Land use/land cover change has a significant indicative effect on the carbon storage of terrestrial ecosystems. We selected Chang-Zhu-Tan urban agglomeration as research object, coupled FLUS and InVEST models to explore changes in land use region from 2010 2020, predicted their spatiotemporal evolution characteristics under three scenarios 2035: natural development (S1), ecological priority (S2) (S3). Spatial autocorrelation was used analyze spatial distribution storage. The results revealed rapid expansion encroaching cultivated forest resulting total area 1957.50 km2 by 2020. Carbon experienced loss 6.86 × 106 t, primarily between 2015. model indicated pattern “low middle high around”, with areas low showing large-scale faceted aggregate 2035. Under different regional scenarios, S3 exhibited highest loss, reaching 150.93 t. S1 decline 136.30 while S2 only reduction 24.26 primary driving factor is conversion into areas. It recommended that implementation protection policies optimization structures effectively minimize

Язык: Английский

Developing Strategies for Carbon Neutrality Through Restoration of Ecological Spatial Networks in the Thal Desert, Punjab DOI Creative Commons

Tauqeer Nawaz,

Muhammad Gohar Ismail Ansari, Qiang Yu

и другие.

Remote Sensing, Год журнала: 2025, Номер 17(3), С. 431 - 431

Опубликована: Янв. 27, 2025

Carbon neutrality is an important goal for addressing global warming. It can be achieved by increasing carbon storage and reducing emissions. Vegetation plays a key role in storing carbon, but it often lost or damaged, especially areas affected desertification. Therefore, restoring vegetation these crucial. Using advanced techniques to improve ecosystem structure support ecological processes, enhance soil environmental conditions, encourage growth, boost effectively. This study focuses on optimizing Ecological Spatial Networks (ESNs) revitalization regional development, employing such as the MCR model corridor construction, spatial analysis, Gephi mapping topological attributes. Various metrics were used evaluate network performance, while EFCT was applied optimize ESN maximize sinks. In Thal Desert, source patches (ESPs) divided into four modularity levels (15.6% 49.54%) five communities. The northeastern southwestern regions showed higher functionality lower connectivity, central region exhibited reverse. To structure, 27 51 corridors added 76 existing patches, including 56 forest 20 water/wetland using model. optimized resulted 14.97% improvement sink capacity compared unoptimized primarily due better functioning of wetland areas. Enhanced connectivity between components contributed more resilient stable ESN, supporting both sustainability sequestration.

Язык: Английский

Процитировано

0

Urban Expansion-Induced Land Use Land Cover Changes and the Subsequent Changes in Ecosystem Service and Land Surface Temperature in the Central Highland of Ethiopia DOI Creative Commons
Belew Bekele, Wei Wu,

Lemma Tsegaye

и другие.

Environmental and Sustainability Indicators, Год журнала: 2025, Номер unknown, С. 100626 - 100626

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

From Green to Grey: Assessing the Impact of Urbanization on Land Surface Temperature and Thermal Comfort in Multan City DOI
Zainab Tahir, Syed Amer Mahmood, Syed Amer Mahmood

и другие.

Earth Systems and Environment, Год журнала: 2025, Номер unknown

Опубликована: Фев. 14, 2025

Язык: Английский

Процитировано

0

Dynamicity of carbon emission and its relationship with heat extreme and green spaces in a global south tropical mega city region DOI
Manob Das, Arijit Das

Atmospheric Pollution Research, Год журнала: 2025, Номер unknown, С. 102484 - 102484

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Carbon neutral spatial zoning and optimization based on land use carbon emission in the qinba mountain region, China DOI Creative Commons
Jingeng Huo,

Zhenqin Shi,

Wenbo Zhu

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Март 25, 2025

Amid global climate change, the pursuit of low-carbon development has become a unified international goal. The Qinba Mountain region plays an important role in maintaining China's ecological security, making spatial zoning tailored for carbon neutrality vital local sustainable development. Using land use and socioeconomic data from 2000 to 2020 81 county-level units, neutral framework was developed, considering natural, economic, resource factors. This study further integrated spatiotemporal dynamics index multi-scenario predictions future emission (CE) zoning. results revealed that had overall positive net-carbon trend without significant deficits, central faced increased CE northern weak carrying capacity. predicted continued decrease under scenario reached 30.55 million t by 2060, with only nine units failing reach their peaking 2030. Five different zones were identified: sink functional zone, stabilization high-carbon control zone source optimization zone. Tailored strategies each proposed enhance regional environment contribute green These findings offer insights into achieving regions or cities.

Язык: Английский

Процитировано

0

High-Resolution Flood Susceptibility Mapping and Exposure Assessment in Pakistan: An Integrated Artificial Intelligence, Machine Learning and Geospatial Framework DOI Creative Commons
Mirza Waleed, Muhammad Sajjad

International Journal of Disaster Risk Reduction, Год журнала: 2025, Номер unknown, С. 105442 - 105442

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

Leveraging Google Earth Engine for improved groundwater management and sustainability DOI
Muhammad Shareef Shazil

Elsevier eBooks, Год журнала: 2025, Номер unknown, С. 213 - 229

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Evaluation of Land Use and Land Cover Change on Ecosystem Carbon Storage Using Mlpnn-Markov and Invest Model Using Field Data in Kedarnath Wildlife Sanctuary, Temperate Forests, India from 2010 to 2035 DOI

pawan negi,

Rajiv Pandey

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Machine Learning-based Spatio-Temporal Assessment of Land Use/Land Cover Change in Barishal District of Bangladesh between 1988 and 2024 DOI Creative Commons

Walida Zaman,

H Rainak Khan Real

Environmental Challenges, Год журнала: 2025, Номер unknown, С. 101168 - 101168

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

Integrating Remote Sensing and Machine Learning to Analyze Urban Growth and Its Environmental Effects: A 30-Year Assessment in Başakşehir, Turkey DOI Creative Commons
Muhammed Ernur Akıner, Mehdi Ghasri

Pure and Applied Geophysics, Год журнала: 2025, Номер unknown

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0