The Decisive Influence of the Improved Remote Sensing Ecological Index on the Terrestrial Ecosystem in Typical Arid Areas of China DOI Creative Commons

Guo Long,

Chao Xu, Hongqi Wu

et al.

Land, Journal Year: 2024, Volume and Issue: 13(12), P. 2162 - 2162

Published: Dec. 12, 2024

This study aims to assess the spatiotemporal changes in ecological environment quality (EEQ) arid regions, using Xinjiang as a case study, from 2000 2023, with an improved remote sensing index (IRSEI). Due complex ecology of traditional (RSEI) has limitations capturing dynamics. To address this, we propose enhanced IRSEI model that replaces normalization standardization, improving robustness against outliers. Additionally, kernel normalized difference vegetation (kNDVI) and salinity (NDSI) are integrated saline areas more effectively. The methodology includes time series analysis, spatial distribution statistical evaluations method, coefficient variation, Hurst index. Results show accurately reflects dynamics than RSEI. Temporal analysis reveals stable overall EEQ, some improving. Spatially, is generally better north mountainous regions south plains. Statistical suggest positive trend changes, surpassing degraded ones. contributes monitoring, protection, management region ecosystems, emphasizing need for high-resolution data further analysis.

Language: Английский

Study on the driving mechanism of spatio-temporal non-stationarity of vegetation dynamics in the Taihangshan-Yanshan Region DOI Creative Commons

Jiao Pang,

Meiqing Wang, Huicong Zhang

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 170, P. 113084 - 113084

Published: Jan. 1, 2025

Language: Английский

Citations

1
Impacts of Climate Change and Anthropogenic Activities on Vegetation Dynamics Considering Time Lag and Accumulation Effects: A Case Study in the Three Rivers Source Region, China DOI Open Access
Yunfei Ma, Xiaobo He, Donghui Shangguan

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(6), P. 2348 - 2348

Published: March 7, 2025

Examining the effects of climate change (CC) and anthropogenic activities (AAs) on vegetation dynamics is essential for ecosystem management. However, time lag accumulation plant growth are often overlooked, resulting in an underestimation CC impacts. Combined with kernel normalized difference index (kNDVI), data during growing season from 2000 to 2023 Three Rivers Source Region (TRSR) trend correlation analyses were employed assess kNDVI dynamics. Furthermore, effect upgraded residual analysis applied explore how climatic human drivers jointly influence vegetation. The results show following: (1) showed a fluctuating but overall increasing trend, indicating improvement growth. Although future likely continue improving, certain areas—such as east western Yangtze River basin, south Yellow parts Lancang basin—will remain at risk deterioration. (2) Overall, both precipitation temperature positively correlated kNDVI, acting dominant factor affecting predominant temporal 0-month 1-month accumulation, while primarily 2–3-month 0–1-month accumulation. main category (PA_TL), which accounted 70.93% TRSR. (3) Together, AA drove dynamics, contributions 35.73% 64.27%, respectively, that played role. incorporating combined enhanced explanatory ability factors

Language: Английский

Citations

1
Research Trends in Vegetation Spatiotemporal Dynamics and Driving Forces: A Bibliometric Analysis (1987–2024) DOI Open Access

Dejin Dong,

Jianbo Shen, Daohong Gong

et al.

Forests, Journal Year: 2025, Volume and Issue: 16(4), P. 588 - 588

Published: March 28, 2025

Under the dual pressures of climate change and rapid urbanization, a comprehensive analysis vegetation’s spatiotemporal patterns their driving forces plays pivotal role for addressing global ecological challenges. However, systematic bibliometric analyses in this field remain limited. This study involved 18,270 related publications from 1989 to 2024 retrieved Web Science SCI-Expanded database, elucidating research trends, methodologies, key thematic areas. Utilizing bibliometrix biblioshiny tools, results reveal an annual average growth rate 17.62% number published articles, indicating expansion. Climate emerged as core force, with high-frequency keywords such “vegetation”, “dynamics”, “variability”. China (18,687 papers), United States (14,502 Germany (3394 papers) are leading contributors domain, showing fastest output, albeit relatively lower citation rates. Core journals, including Remote Sensing Environment Global Change Biology, have played roles advancing vegetation dynamics research, remote sensing techniques dominating field. The highlights shift single-variable (e.g., temperature, precipitation) multi-scale multidimensional approaches around 2010. Regional studies, those focusing on Loess Plateau, gaining importance, while advancements machine learning technologies enhanced precision scalability research. provides summary current state development trends forces, offering valuable insights future

Language: Английский

Citations

0
Revealing the spectral bands that make generic remote estimates of leaf area index in wheat crop over various interference factors and planting conditions DOI
Heli Li,

Pingheng Li,

Xingang Xu

et al.

Computers and Electronics in Agriculture, Journal Year: 2025, Volume and Issue: 235, P. 110381 - 110381

Published: April 14, 2025

Language: Английский

Citations

0
Quantifying the impacts of climate change and human activities on vegetation in ecologically fragile regions: a case study of Northern China DOI

Xiangzhou Dou,

Xiumei Li,

Guoqing Sang

et al.

Theoretical and Applied Climatology, Journal Year: 2025, Volume and Issue: 156(5)

Published: April 25, 2025

Language: Английский

Citations

0
Characteristics of Spatial and Temporal Vegetation Succession in the Yellow River Basin and Its Impact on Runoff DOI
Wenxian Guo,

Shi Hai,

Xuyang Jiao

et al.

Ecohydrology, Journal Year: 2025, Volume and Issue: 18(3)

Published: May 1, 2025

ABSTRACT Vegetation is an important part of the ecosystem and all play role in hydrological cycle. This study uses MODIS NDVI data from Yellow River Basin (YRB) for last two decades, together with corresponding meteorological same period. Spatial temporal trends vegetation succession within YRB were analysed using a variety methods including Theil‐Sen median trend analysis, Mann‐Kendall test, partial correlation, geographic detector Hurst index. Furthermore, attribution analyses performed, along quantitative assessment influence on runoff through application Budyko–Fu equation. The results indicate that: (1) cover exhibited significant overall increasing 2001 to 2021, characterized by multi‐year average value 0.574 growth rate 0.0047/a. (2) Precipitation strong positive whereas air temperature evapotranspiration factor demonstrated negative correlation. contributions human activities climate change changes quantified at 57.8% 42.2%, respectively. (3) Future projections declining YRB. (4) Runoff basin increased 2012, then decreased 2013 2017, subsequently again after 2018, revealing upward trend. (5) impact variations ranged 7.6% 18.1%. offers valuable reference protection sustainable development

Language: Английский

Citations

0
The Spatiotemporal Evolution of Vegetation in the Henan Section of the Yellow River Basin and Mining Areas Based on the Normalized Difference Vegetation Index DOI Creative Commons
Zhichao Chen, Xueqing Liu,

Honghao Feng

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(23), P. 4419 - 4419

Published: Nov. 26, 2024

The Yellow River Basin is rich in coal resources, but the ecological environment fragile, and degradation of vegetation exacerbated by disruption caused high-intensity mining activities. Analyzing dynamic evolution Henan section its areas over long term run reveals regional offers a scientific foundation for region’s sustainable development. In this study, we obtained time series Landsat imageries from 1987 to 2023 on Google Earth Engine (GEE) platform utilized geographically weighted regression models, Sen (Theil–Sen median) trend analysis, M-K (Mann–Kendall) test, coefficient variation (CV), Hurst index investigate cover based kNDVI (the normalized difference index). This used explore spatial temporal characteristics future development trend. Our results showed that (1) value exhibited fluctuating upward at rate 0.0509/10a 2023. region aligned closely with overall section; however, annual each area consistently remained lower than displayed degree fluctuation, predominantly characterized medium–high variability, moderate high fluctuations accounting 73.5% total. (2) study significant improvement trends. We detected area; yet, might cause 87% area, which may be related multiple factors such as intensity mine site, anthropogenic disturbances, climate change. (3) status shows positive correlation distance areas, 90.9% total, indicating has strong impact cover. provides basis restoration, green mineral Basin.

Language: Английский

Citations

3
Response of Vegetation Coverage to Climate Drivers in the Min-Jiang River Basin along the Eastern Margin of the Tibetan Plat-Eau, 2000–2022 DOI Open Access
Shuyuan Liu,

Yicheng Gu,

Huan Wang

et al.

Forests, Journal Year: 2024, Volume and Issue: 15(7), P. 1093 - 1093

Published: June 24, 2024

Ecological zonation research is typically conducted in the eastern margin of Tibetan Plateau. In order to enhance structure and function regional ecosystems monitor their quality, it crucial investigate shifts coverage vegetation factors that contribute these shifts. The goal this study assess spatial temporal variations covering partitioning its drivers Minjiang River Basin on edge Plateau between 2000 2022. Mann-Kendall test, Hurst index, Theil-Sen median trend analysis, other techniques were used look at features geographical changes as well potential development trends. climatic influences leading differentiation NDVI (Normalized Difference Vegetation Index) quantified through partial complex correlation analyses with temperature precipitation. results showed (1) watershed performed a stable upward trend, indicating growth was generally good; (2) analysis coefficient variation reached 0.092, which highlighted stability change region; (3) future low, there certain degree ecological risk; (4) main driver non-climate factor, distributed most parts watershed; (5) climate shows localized influence, especially concentrated southwest, downstream part upstream areas watershed.

Language: Английский

Citations

2
Vegetation Dynamics and Driving Mechanisms Considering Time-Lag and Accumulation Effects: A Case Study of Hubao–Egyu Urban Agglomeration DOI Creative Commons
Xi Liu, Guoming Du,

Xiaodie Zhang

et al.

Land, Journal Year: 2024, Volume and Issue: 13(9), P. 1337 - 1337

Published: Aug. 23, 2024

The Hubao–Egyu Urban Agglomeration (HBEY) was a crucial ecological barrier in northern China. To accurately assess the impact of climate change on vegetation growth, it is essential to consider effects time lag and accumulation. In this study, we used newly proposed kernel Normalized Difference Vegetation Index (kNDVI) as metric for condition, employed partial correlation analysis ascertain accumulation period response by considering different scenarios (No/Lag/Acc/LagAcc) various combinations. Moreover, further modified traditional residual model. results are follows: (1) From 2000 2022, HBEY experienced extensive persistent greening, with kNDVI slope 0.0163/decade. Precipitation identified dominant climatic factor influencing dynamics. (2) HBEY, effect temperature most distinct, particularly affecting cropland grassland. precipitation pronounced (3) Incorporating into models increases explanatory power impacts dynamics 6.95% compared models. Our findings hold implications regional regulation research.

Language: Английский

Citations

1
Vegetation Greenness Changes and Land Surface Temperatures Monitoring in the Bandung City, West Java DOI Creative Commons
Shafira Himayah, Dede Sugandi

E3S Web of Conferences, Journal Year: 2024, Volume and Issue: 600, P. 03005 - 03005

Published: Jan. 1, 2024

Remote sensing can be used to examine the city of Bandung with variations in its topographical appearance. Apart from that, urban areas such as generally experience land cover transformation (vegetation and non-vegetation) well changes surface temperature. This research aims to: 1) Analyse vegetation greenness City, 2) temperature 3) correlation between dynamics City. The method is information extraction through remote imagery obtain temperature, field measurements. use Landsat 5 8 get a value built-up index greenness. results this are identification spectral character greenness, their influence on temperatures Basin. Types vegetated use, including rice fields, parks plantations, have lower than settlements, roads, empty cemeteries. Positive values regression indicate NDVI LST variables.

Language: Английский

Citations

0