Response of Ecological Quality to Land Use/Cover Change During Rapid Urbanization of Xiong’an New Area DOI Creative Commons
Qi Sun,

Ruitong Qiao,

Quanjun Jiao

et al.

Land, Journal Year: 2024, Volume and Issue: 13(12), P. 2167 - 2167

Published: Dec. 13, 2024

Rapid urbanization facilitates socioeconomic development but also exacerbates land use/cover change (LUCC), significantly impacting ecological environments. Timely, objective, and quantitative assessments of quality changes resulting from LUCC are essential for safeguarding the natural environment managing resources. However, limited research has explored potential interrelationships between spatio-temporal heterogeneity during urbanization. This study focuses on Xiong’an New Area, a region experiencing rapid urbanization, utilizing remote sensing-based index (RSEI) to monitor dynamics 2017 2023. To address computational challenges associated with large-scale regions, streamlined RSEI construction method was developed using Landsat imagery implemented via Google Earth Engine (GEE). A geographically weighted regression (GWR) analysis, integrated Sentinel-2 use data, employed examine influence quality. The findings reveal following: (1) Ecological in Area exhibited an overall positive trajectory, improvements elevating status above moderate levels. (2) Urban expansion resulted 17% reduction farmland, primarily converted into land, which expanded by approximately 12%. (3) protection policies have facilitated conversion farmland wetlands urban green areas, emerged as principal contributors enhancement. (4) correlation observed quality, while negative identified shifts provides valuable scientific insights conservation management, thereby establishing foundation rational resource planning sustainable strategies Area.

Language: Английский

Scale dependency of trade-offs/synergies analysis of ecosystem services based on Bayesian Belief Networks: A case of the Yellow River Basin DOI

Lại Hải Đăng,

Fen Zhao, Yanmin Teng

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 375, P. 124410 - 124410

Published: Feb. 1, 2025

Language: Английский

Citations

3
Constructing cropland ecological stability assessment method based on disturbance-resistance-response processes and classifying cropland ecological types DOI
Haoran Gao, Jian Gong,

Teng Ye

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 930, P. 172673 - 172673

Published: April 25, 2024

Language: Английский

Citations

10
Monitoring and evaluation of ecological restoration in open-pit coal mine using remote sensing data based on a OM-RSEI model DOI
S. Wang, Chao Ma, Yingying Ma

et al.

International Journal of Mining Reclamation and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 23

Published: Jan. 29, 2025

Language: Английский

Citations

1
Dynamic evaluation of the ecological evolution and quality of arid and semi-arid deserts in the Aibugai River Basin based on an improved remote sensing ecological index DOI Creative Commons

Haobin Zhang,

Chao Ma, Pei Liu

et al.

Ecological Informatics, Journal Year: 2024, Volume and Issue: 82, P. 102727 - 102727

Published: July 15, 2024

The ecological quality of arid and semi-arid regions (ASRs) is fragile, the evaluation dynamic changes in multi-factor, long-time-series these can provide a scientific basis for sustainable regional development. Based on remote sensing index (RSEI) its derivative indices dedicated to monitoring ASRs, this study proposes new modified RSEI (nmRSEI) suitable ASRs. We used nmRSEI evaluate analyse factors driving Aibugai River Basin middle Inner Mongolian Plateau core Asia from 1986 2022. results led following conclusions: (1) use helps solve problems related original greenness index, i.e. normalised difference vegetation which was readily affected by soil background areas with low coverage; (2) dryness meet requirements surface degree >98.65% area; (3) introduced salinity showed significant negative correlation nmRSEI; (4) exhibits gradual downward trend (Slope = −0.00326/10a); (5) temperature main factor controlling during research period. provides fast effective method regularly In addition, analysis theoretical support protection ASRs realisation United Nations 2030 Sustainable Development Goals.

Language: Английский

Citations

8
Spatiotemporal Variation and Driving Factors of Ecological Environment Quality on the Loess Plateau in China from 2000 to 2020 DOI Creative Commons

Shuaizhi Kang,

Xia Jia,

Yonghua Zhao

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(24), P. 4778 - 4778

Published: Dec. 21, 2024

The Loess Plateau (LP) in China is an ecologically fragile region that has long faced challenges such as soil erosion, water shortages, and land degradation. spatial temporal variations ecological environment quality on the LP from 2000 to 2020 were analyzed using Remote Sensing Ecological Index (RSEI) Google Earth Engine (GEE) platform. Sen, Mann–Kendall, Hurst exponent analyses used examine variation trends over past 20 years, while Geodetector identified key factors influencing RSEI changes their interactions. results indicate (1) effectively represents environmental of LP, with 47% study area’s annual mean values 20-year period classified moderate, ranging 0.017 0.815. (2) showed improvement 72% area, a 90% overall increase, but 84% these are not likely continue. (3) Key during abrupt change years included precipitation, use/land cover, sediment content, precipitation topography emerging primary influences quality. Although natural largely drive changes, human activities also exert both positive negative effects. This underscores importance sustainable management provides policy insights for advancing civilization contributing achievement Sustainable Development Goals (SDGs).

Language: Английский

Citations

7
IRSEI-based monitoring of ecological quality and analysis of drivers in the Daling River Basin DOI Creative Commons

Jintao Ge,

Cheng Qian, Chao Zhang

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: June 24, 2024

Abstract The Daling River Basin is an important ecological functional area in the western region of Liaoning with outstanding environmental problems. monitoring and quality basin analysis driving factors are great importance for protection environment improvement economic quality. In this paper, three periods Landsat remote sensing images 1995, 2010 2020 used as basic data, platforms technical means such RS GIS to decipher extract land use information, construct type transfer matrix. index (RSEI) was improved, principal component method applied improved (IRSEI) model based on greenness (NDVI), moisture (WET), heat (LST) new dryness (N-NDBSI), so realize dynamic study area. Based change, combined trend Basin, thus achieving purpose rapid efficient from 1995 2020. A geoprobe then systematically assess drivers catchment. results show that can efficiently accurately obtain spatial distribution pattern temporal variation IRSEI area, which more line characteristics indicators showed increasing 2020, 0.4794 0.5615, proportion benign classes increased year by during period. Among evaluation indicators, NDVI N-NDBSI main affecting increase vegetation cover, climate regulation human activities have obvious promoting effects Basin. This provides a scientific theoretical basis implementation further measures.

Language: Английский

Citations

4
Assessment of ecological asset quality and its drivers in Agro-pastoral Ecotone of China DOI Creative Commons

Wenmin Liu,

Zhiyuan Cheng,

Jie Li

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 170, P. 113072 - 113072

Published: Jan. 1, 2025

Language: Английский

Citations

0
Analysis of the spatial pattern and causes of ecological environmental quality in Myanmar based on the RSEI model and the Geodetector-GCCM method DOI Creative Commons

Shuangfu Shi,

Shuangyun Peng,

Zhiqiang Lin

et al.

Frontiers in Environmental Science, Journal Year: 2025, Volume and Issue: 13

Published: Feb. 11, 2025

Facing the challenges brought about by global climate change and biodiversity loss, accurately assessing ecological environmental quality (EEQ), its driving factors are crucial for formulating effective strategies protection restoration. However, there remains limited understanding of interactions causal relationships between multiple factors, with existing studies mainly focusing on impact individual EEQ their correlations. This study took Myanmar as research area, employing a Remote Sensing Ecological Index (RSEI) model spatial autocorrelation analysis to quantitatively evaluate distribution characteristics Myanmar’s in 2020 reveal dependence. Furthermore, innovatively integrating Geodetector Geographical Convergent Cross Mapping (GCCM) methods, this systematically analyzed impacts various spatiotemporal differentiation EEQ. The results indicate that: (1) overall was relatively good, but is significant heterogeneity; (2) Local revealed clear clustering pattern Myanmar; (3) identified DEM, slope, Net Primary Productivity (NPP), land use, human footprint dominant influencing EEQ, among these factors; (4) GCCM further verified effects NPP, while temperature, precipitation, use weaker. established technical framework analyzing causes unveiling mechanisms evolution driven natural factors. It enriched human-environment within coupled systems delved into complex system. These insights enhanced our intricate providing valuable references sustainable development Myanmar.

Language: Английский

Citations

0
NCSBFF-Net: Nested Cross-Scale and Bidirectional Feature Fusion Network for Lightweight and Accurate Remote-Sensing Image Semantic Segmentation DOI Open Access

Shihao Zhu,

Binqiang Zhang,

Dawei Wen

et al.

Electronics, Journal Year: 2025, Volume and Issue: 14(7), P. 1335 - 1335

Published: March 27, 2025

Semantic segmentation has emerged as a critical research area in Earth observation. This paper proposes novel end-to-end semantic network, the Nested Cross-Scale and Bidirectional Feature Fusion Network (NCSBFF-Net), to address issues such intra-class heterogeneity, inter-class homogeneity, scale variability, classification of tiny objects. Specifically, CNN-based lightweight feature pyramid module is employed extract contextual information across multiple scales, thereby addressing heterogeneity. The NCSBFF leverages features from both shallow deep layers designed fuse multi-scale features, enhancing differences. Additionally, shallowest passed Shuffle Attention block module, which adaptively filters out weak details highlights for Extensive experiments were conducted on Potsdam Vaihingen benchmarks. Experiment results demonstrate that NCSBFF-Net outperforms state-of-the-art methods, achieving better trade-off between accuracy efficiency, with 5% improvement mIoU significantly recognition capability small complex objects, vehicles irregular land parcels, challenging scenes, 1.73% increase demonstrating balance computational efficiency accuracy, providing an optimized solution deployment edge devices.

Language: Английский

Citations

0
Multitemporal Analysis Using Remote Sensing and GIS to Monitor Wetlands Changes and Degradation in the Central Andes of Ecuador (Period 1986–2022) DOI Creative Commons
Juan Carlos Carrasco, Daisy Carolina Carrasco López,

Jorge Daniel Córdova Lliquín

et al.

Resources, Journal Year: 2025, Volume and Issue: 14(4), P. 61 - 61

Published: April 4, 2025

Wetlands are transitional lands between terrestrial and aquatic systems that provide various ecosystem services. The objective of this study was to evaluate the change in wetlands Chimborazo Wildlife Reserve (CR) period 1986–2022 using geographic information (GISs), multitemporal satellite data, field data from 16 reserve. Images Landsat collections (five Thematic Mapper, seven Enhanced eight Operational Land Imager Thermal Infrared Sensor) were used. Image analysis processing performed, resulting maps evaluated a GIS environment determine land cover growth rate hydrophilic opportunistic vegetation (HOV) according hillside orientation. results show there negative annual anomalies water-covered areas, which coincide with increase HOV. This shows constancy or HOV, varies 0.0018 0.0028, causes disappearance these ecosystems. importance lies its potential contribution decision-making process management CR.

Language: Английский

Citations

0