Asymmetric responses of EVI and tree ring growth to extreme climate on the northeastern margin of the Tibetan Plateau

International Journal of Biometeorology, Год журнала: 2024, Номер unknown

Опубликована: Окт. 2, 2024

Язык: Английский

Effects of climate variability and urbanization on spatiotemporal patterns of vegetation in the middle and lower Yangtze River Basin, China

Frontiers in Plant Science, Год журнала: 2024, Номер 15

Опубликована: Ноя. 4, 2024

Vegetation serves as a crucial indicator of ecological environment and plays vital role in preserving ecosystem stability. However, urbanization escalates rapidly, natural vegetation landscapes are undergoing continuous transformation. Paradoxically, is pivotal mitigating the environmental challenges posed by urban sprawl. The middle lower Yangtze River Basin (MLYRB) China, particularly its economically thriving reaches, has witnessed surge urbanization. Consequently, this study explored spatiotemporal variations normalized difference index (NDVI) MLYRB, with an emphasis on elucidating impact climate change dynamics. results indicate that significant increasing trend NDVI across MLYRB from 2000 to 2020, pattern expected persist. An improvement was observed 94.12% prefecture-level cities area, predominantly western southern regions. Temperature wind speed stand out dominant contributors improvement. Nevertheless, degradation detected some highly urbanized central eastern parts mainly attributed negative effects escalating Interestingly, positive correlation between rate observed, which may be largely related proactive preservation policies. Additionally, global climatic oscillations were identified key force driving periodic variations. These findings hold importance promoting harmonious preservation, thereby providing invaluable insights for future planning efforts.

Язык: Английский

Methods for Extracting Fractional Vegetation Cover from Differentiated Scenarios Based on Unmanned Aerial Vehicle Imagery

Land, Год журнала: 2024, Номер 13(11), С. 1840 - 1840

Опубликована: Ноя. 5, 2024

Fractional vegetation cover (FVC) plays a key role in ecological and environmental status assessment because it directly reflects the extent of its status, yet is an important component ecosystems. FVC estimation methods have evolved from traditional manual interpretation to advanced remote sensing technologies, such as satellite data analysis unmanned aerial vehicle (UAV) image processing. Extraction based on high-resolution UAV are being increasingly studied fields ecology sensing. However, research UAV-based extraction against backdrop high soil reflectance arid regions remains scarce. In this paper, 12 visible light images differentiated scenarios Ebinur Lake basin, Xinjiang, China, various used for high-precision estimation: Otsu’s thresholding method combined with Visible Vegetation Indices (abbreviated Otsu-VVIs) (excess green index, excess red minus normalized green–red difference green–blue red–green ratio color index extraction, visible-band-modified soil-adjusted modified red–green–blue visible-band index), space (red, green, blue, hue, saturation, value, lightness, ‘a’ (Green–Red component), ‘b’ (Blue–Yellow component)), linear mixing model (LMM), two machine learning algorithms (a support vector neural network). The results show that following exhibit accuracy across scenarios: Otsu–CIVE, (‘a’: Green–Red LMM, SVM (Accuracy > 0.75, Precision 0.8, kappa coefficient 0.6). Nonetheless, higher scene complexity entropy reduce applicability precise methods. This study facilitates accurate, efficient information within semiarid regions, providing technical references similar areas.

Язык: Английский