Uncovering the impact of multiple determinants on vegetation NPP in Inner Mongolia DOI Creative Commons
Zhiwei Yu, Lijuan Miao, Qiang Liu

et al.

Global Ecology and Conservation, Journal Year: 2024, Volume and Issue: 56, P. e03341 - e03341

Published: Dec. 1, 2024

Language: Английский

Spatiotemporal changes of vegetation in the northern foothills of Qinling Mountains based on kNDVI considering climate time-lag effects and human activities DOI
Lili Chen,

Zhenhong Li,

Chenglong Zhang

et al.

Environmental Research, Journal Year: 2025, Volume and Issue: unknown, P. 120959 - 120959

Published: Jan. 1, 2025

Language: Английский

Citations

2

Identifying priority conservation areas based on systematic conservation planning analysis in the Loess Plateau, China DOI Creative Commons
Le Hui, Hao Wang, Jiamin Liu

et al.

Global Ecology and Conservation, Journal Year: 2025, Volume and Issue: unknown, P. e03495 - e03495

Published: Feb. 1, 2025

Language: Английский

Citations

0

Spatiotemporal Heterogeneity of Vegetation Cover Dynamics and Its Drivers in Coastal Regions: Evidence from a Typical Coastal Province in China DOI Creative Commons
Yiping Yu, Dong Liu, Shiyu Hu

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(5), P. 921 - 921

Published: March 5, 2025

Studying the spatiotemporal trends and influencing factors of vegetation coverage is essential for assessing ecological quality monitoring regional ecosystem dynamics. The existing research on variations their driving predominantly focused inland ecologically vulnerable regions, while coastal areas received relatively little attention. However, with unique geographical, ecological, anthropogenic activity characteristics, may exhibit distinct distribution patterns mechanisms. To address this gap, we selected Shandong Province (SDP), a representative province in China significant natural socioeconomic heterogeneity, as our study area. investigate coastal–inland differentiation dynamics its underlying mechanisms, SDP was stratified into four geographic sub-regions: coastal, eastern, central, western. Fractional cover (FVC) derived from MOD13A3 v061 NDVI data served key indicator, integrated multi-source datasets (2000–2023) encompassing climatic, topographic, variables. We analyzed characteristics dominant across these sub-regions. results indicated that (1) FVC displayed complex notable gradient where decreased towards coast. (2) influence various significantly varied sub-regions, dominating an east–west polarity, i.e., explanatory power intensified westward resurging zones. (3) intricate interaction multiple influenced spatial FVC, particularly dual-factor synergies interactions between other were crucial determining coverage. Notably, zone exhibited high sensitivity to drivers, highlighting exceptional ecosystems human activities. This provides insights different geographical zones well factors. These findings can help understand challenges faced protecting vegetation, facilitating deeper insight responses enabling formulation effective tailored strategies promote sustainable development areas.

Language: Английский

Citations

0

Regional Responses of Ecosystem Service Security to Land Use Changes and Driving Mechanisms: Insights from Nearly 40 Years of Observations in Shaanxi, China DOI
Shan Qu, Ling Han,

Liangzhi Li

et al.

Journal of environmental chemical engineering, Journal Year: 2025, Volume and Issue: unknown, P. 116224 - 116224

Published: March 1, 2025

Language: Английский

Citations

0

Integration of ecosystem service composite index and driving thresholds for ecological zoning management: A case study of Qinling-Daba Mountain, China DOI
Juan Bai, Xiaofeng Wang,

You Tu

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 384, P. 125309 - 125309

Published: April 29, 2025

Language: Английский

Citations

0

Spatio-Temporal Variations of Soil Conservation Service Supply–Demand Balance in the Qinling Mountains, China DOI Creative Commons
Pengtao Wang, Guan Huang, Le Chen

et al.

Land, Journal Year: 2024, Volume and Issue: 13(10), P. 1667 - 1667

Published: Oct. 13, 2024

The ecological conservation of nature reserves has garnered considerable attention and is subject to stringent management in China. However, the majority these areas have a history underdeveloped economies require urgent improvements well-being local communities. Effectively coupling harmonizing dynamic relationship between ecosystem services socio-economic development emerged as crucial concern for reserves. Therefore, further exploration needed achieve spatio-temporal balance alignment supply demand ESs Utilizing multiple datasets, RULSE, bivariate autocorrelation methods, this study investigated evolution supply–demand ratio (ESDR) spatial matches soil (SCSs) Qinling Mountains (QMs) from 2000 2020. results indicated following: (1) Over years, SCSs exhibited consistently high level, with an upward trend observed 63.10% QMs, while generally low, decreasing 82.68% QMs. (2) remained favorable, positive ESDR reaching 82.19% From 2010, there was significant decline ESDR; however, substantial rebound across region 2010 (3) counties districts values ESDR. When examining cities, Weinan, Xi’an, Ankang demonstrated relatively consistent patterns higher over time. In 2000, on northern slope lower than that southern slope; situation subsequently underwent reversal. (4) distribution SCS predominantly characterized by matching regions exhibiting either High Supply–High Demand or Low Supply–Low years. This suggests dynamics been favorable recent matches. These findings can provide valuable insights similar aiming implement environmental protection sustainable development. future research endeavors, should strive expand upon exploring associated other diverse reserves, considering their unique geographical characteristics, order promote more rational strategies.

Language: Английский

Citations

3

Research on Evaluating the Characteristics of the Rural Landscape of Zhanqi Village, Chengdu, China, Based on Oblique Aerial Photography by Unmanned Aerial Vehicles DOI Open Access
Chunyan Zhu, Rong Li,

Jinming Luo

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(12), P. 5151 - 5151

Published: June 17, 2024

To achieve the transition of rural areas from traditional to modern, visualization landscape data and feature evaluations are essential. Landscape character assessment (LCA) is a well-established tool that was developed assess understand features. In recent years, drones have become increasingly attractive for various applications services due their low costs relative ease operation. Unlike most previous studies relied solely on drone-based remote sensing or visual esthetic evaluations, this study proposes an innovative method based characteristic oblique drone photography technology, supported by specific survey results. These include metrics, such as Shannon diversity index (SHDI), evenness (SHEI), vegetation coverage, zoning, delineations ecologically sensitive areas. This applied Zhanqi Village in Chengdu, Sichuan Province, China revealed some unique characteristics village. By categorizing describing features, makes judgments decisions about them. beneficial attempt apply scientific methods assessments production management aerial surveys. provides comprehensive framework evaluating features demonstrates combination LCA technology feasible research. Additionally, emphasizes need further research explore potential application continuously evolving urban environments future.

Language: Английский

Citations

1

Spatio-Temporal Evolution of Vegetation Coverage and Eco-Environmental Quality and Their Coupling Relationship: A Case Study of Southwestern Shandong Province, China DOI Open Access
Dongling Ma, Qian Wang,

Qingji Huang

et al.

Forests, Journal Year: 2024, Volume and Issue: 15(7), P. 1200 - 1200

Published: July 11, 2024

Propelled by rapid economic growth, the southwestern Shandong urban agglomeration (SSUA) in China has become a crucial industrial hub, but this process somewhat hindered vegetation growth and environmental quality. Leveraging functionalities of Google Earth Engine (GEE) platform, we derived fractional coverage (FVC) through Normalized Difference Vegetation Index (NDVI) assessed eco-environmental quality using Remote Sensing Ecological (RSEI). To examine patterns shifts SSUA, employed Theil–Sen median slope estimation, which provided robust estimates linear trends, Mann–Kendall trend test to determine statistical significance these Hurst exponent analysis evaluate long-term persistence predict future changes Furthermore, explore interdependencies between (VC) quality, applied an improved coupling coordination degree model (ICCDM). This allowed us assess co-evolution synergy two factors over study period, providing comprehensive insights for sustainable ecological planning region. The VC consistently across most SSUA from 2000 2020. dominance had transitioned being predominantly characterized relatively high mainly VC. A substantial portion is predicted experience improvements its moving forward. relationship conditions southwest Province generally exhibited state orderly coordinated development. With passage time, there was clear tendency toward expansion coupled uncoordinated areas distributed network within each regional center. Our research unveils dynamics spatial-temporal elucidates mechanism aspects, provides theoretical support understanding healthy development ecology agglomerations context.

Language: Английский

Citations

1

Spatial Scale Effect on Fractional Vegetation Coverage Changes and Driving Factors in the Henan Section of the Yellow River Basin DOI Creative Commons

Rongxi Wang,

Hongtao Wang, Cheng Wang

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(14), P. 2575 - 2575

Published: July 13, 2024

Vegetation plays a crucial role in terrestrial ecosystems, and the FVC (Fractional Coverage) is key indicator reflecting growth status of vegetation. The accurate quantification dynamics underlying driving factors has become hot topic. However, scale effect on changes received less attention previous studies. In this study, at multiple scales were analyzed to reveal spatial temporal change vegetation Henan section Yellow River basin. Firstly, based pixel dichotomy model, different times was calculated using Landsat-8 data. Then, characteristics simple linear regression CV (Coefficient Variation). Finally, GD (Geographic Detector) used quantitatively analyze scales. results study revealed that (1) showed an upward trend all scales, increasing by average 0.55% yr−1 from 2014 2022. areas with 10.83% more than those decreasing trend. (2) As decreased, explanatory power topography (aspect, elevation, slope) for gradually strengthened, while climate (evapotranspiration, temperature, rainfall) anthropogenic activities (night light) decreased. (3) q value evapotranspiration always highest across peaking notably 1000 m (q = 0.48).

Language: Английский

Citations

1

Impacts of Climate and Land-Use Change on Fraction Vegetation Coverage Based on PLUS-Dimidiate Pixel Model DOI Open Access
Hong Shi, Ji Yang,

Q. Liu

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(23), P. 10430 - 10430

Published: Nov. 28, 2024

Climate and land-use change are key factors of vegetation dynamics, impacts arising from both them need to be further studied. This study simulated the fraction coverage in 2050 through coupling Patch-Generating Land Use Simulation (PLUS) model Dimidiate Pixel explored effects climate on Chengdu-Chongqing Economic Circle region. The findings indicated that: (1) was mainly restored over 2000–2020 period, accounting for 59.38% investigation area. Under SSP245 SSP585 scenarios, increased by 40.57% 46.38%, respectively. (2) under superposition effect land use significantly outweighed compensation effect. Specifically, cover accounted 90.69% 90.57% total area, Conversely, constituted a relatively minor proportion, representing 9.31% 9.43% (3) positive changes 35.47% 40.90%, respectively, while negative 55.22% 49.67%, These aimed offer guidance execution restoration initiatives upstream

Language: Английский

Citations

0