Spatiotemporal Changes of Vegetation Growth and Its Influencing Factors in the Huojitu Mining Area from 1999 to 2023 Based on kNDVI

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(3), P. 536 - 536

Published: Feb. 5, 2025

Vegetation indices are important representatives of plant growth. Climate change and human activities seriously affect vegetation. This study focuses on the Huojitu mining area in Shendong region, utilizing kNDVI index calculated via Google Earth Engine (GEE) cloud platform. The Mann–Kendall mutation test linear regression analysis were employed to examine spatiotemporal changes vegetation growth over a 25-year period from 1999 2023. Through correlation analysis, geographic detector models, land use map fusion, combined with climate, topography, soil, mining, data, this investigates influencing factors evolution. key findings as follows: (1) is more suitable for analyzing compared NDVI. (2) Over past 25 years, has exhibited an overall fluctuating upward trend, annual rate 0.0041/a. average value 0.121. Specifically, initially increased gradually, then rapidly increased, subsequently declined rapidly. (3) significantly improved, areas improved accounting 89.08% total area, while degraded account 11.02%. (4) Precipitation air temperature primary natural fluctuations precipitation being dominant factor (r = 0.81, p < 0.01). spatial heterogeneity influenced by use, soil nutrients, activities, having greatest impact (q 0.43). Major contribute 46.45% improvement 13.43% degradation. provide scientific basis ecological planning development area.

Language: Английский

The Spatiotemporal Evolution of Vegetation in the Henan Section of the Yellow River Basin and Mining Areas Based on the Normalized Difference Vegetation Index

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

Analysis of Spatiotemporal Evolution and Driving Forces of Vegetation from 2001 to 2020: A Case Study of Shandong Province, China

Forests, Journal Year: 2024, Volume and Issue: 15(7), P. 1245 - 1245

Published: July 17, 2024

As global climate change intensifies and human activities escalate, changes in vegetation cover, an important ecological indicator, hold significant implications for ecosystem protection management. Shandong Province, a critical agricultural economic zone China, experiences that crucially affect regional regulation biodiversity conservation. This study employed normalized difference index (NDVI) data, combined with climatic, topographic, anthropogenic activity utilizing trend analysis methods, partial correlation analysis, Geodetector to comprehensively analyze the spatiotemporal variations primary driving factors of cover Province from 2001 2020. The findings indicate overall upward particularly areas concentrated activities. Climatic factors, such as precipitation temperature, exhibit positive growth, while land use emerge one key drivers influencing dynamics. Additionally, topography also impacts spatial distribution certain extent. research provides scientific basis management similar regions, supporting formulation effective restoration conservation strategies.

Language: Английский