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

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

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A study of spatial distribution and dynamic change in monthly FVC of urban parks

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(8), P. e0308805 - e0308805

Published: Aug. 23, 2024

The study on the spatial distribution and dynamic change in monthly Fractional Vegetation Cover (FVC) of parks provides a scientific basis for vegetation management optimization urban parks. This research focuses two comprehensive located Xinxiang, China—People’s Park Harmony Park, using multi-spectral Unmanned Aerial Vehicle (UAV) images as data source considering periods. Monthly FVC was obtained method Dimidiate Pixel Model based Normalized Difference Index (NDVI). changes at regional scale were described through mean areas various scales, analyzed coefficient variation curve trends. Furthermore, scales standard deviation Subsequently, differential used to analyze pixel scale. results indicate: (1) In terms characteristics parks, both exhibit highest ratio bare area January February. proportions People’s are 59.17% 64.46%, while they 69.10% 51.92%, showing most distinct characteristics. high very coverage each month mainly distributed outskirts park, medium, medium-low, low central middle parts park. overall park shows trend periphery center. (2) spatial-temporal scale, average an “∩” -shaped pattern. peak minimum values different occur times. appears August, it June, with corresponding 0.46 0.50, respectively. occurs February, January, 0.17 0.15, Among highest-coverage greatest fluctuations, ascending descending rates generally opposite (3) overall, moderate improvement from February-August, degradation January-February August-December. primarily slight. significant March-April, predominant type changes. show during September-October October-November, respectively, During periods FVC, decreases February August December, increases relatively good conditions June August. should consider: balancing recreational ecological functions controlling proportion land, enhancing canopy structure or hard surfaces; locally increasing evergreen plants moderately planting density. addition, strengthen reduce impact flooding maintain health vegetation.

Language: Английский

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Spatial–Temporal Differentiation and Driving Factors of Vegetation Landscape Pattern in Beijing–Tianjin–Hebei Region Based on the ESTARFM Model

Sustainability, Journal Year: 2024, Volume and Issue: 16(23), P. 10498 - 10498

Published: Nov. 29, 2024

Urbanization and industrialization have led to obvious changes in the ecological environment landscape pattern Beijing–Tianjin–Hebei region. Therefore, it is crucial clarify spatial–temporal vegetation cover its conduct analysis with driving factors for preservation This study combined AVHRR GIMMS NDVI MODIS data based on ESTARFM model obtain a high resolution cover; then analyzed at type scales using index explored of through principal component analysis. The results show that (1) mainly medium higher coverage distributed northeast, western part Taihang Mountains central plains area. From 1985 2022, there was no statistically significant difference overall change coverage. (2) level, exhibited following characteristics: increased fragmentation, an increase complexity shape, decrease connectivity, discrete species diversity. At demonstrated most degree fragmentation. high-vegetation-cover areas more concentrated distribution. Additionally, low, lower types displayed complexity, discreteness heterogeneity within landscape. (3) Meanwhile, showed were result effects climatic anthropogenic human factor played dominant role; this followed by larger contributions from factors. In addition offering pertinent scientific insights maximization fostering regional sustainable development region, aforementioned research could serve as foundation management planning cover.

Language: Английский

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