RT Journal Article
T1 Uncovering True Significant Trends in Global Greening.
A1 Gutiérrez-Hernández, Oliver
A1 García, Luís V.
K1 Biogeografía
K1 Sistemas de información geográfica
AB The global greening trend, marked by significant increases in vegetation cover across ecoregions, has attracted widespread attention. However, even robust traditional methods, like the non-parametric Mann-Kendall test, often overlook crucial factors such as serial correlation, spatial autocorrelation, and multiple testing, particularly in spatially gridded data. This oversight can lead to inflated significance of detected spatiotemporal trends. To address these limitations, this research introduces the True Significant Trends (TST) workflow, which enhances the conventional approach by incorporating pre-whitening to control for serial correlation, Theil-Sen (TS) slope for robust trend estimation, the Contextual Mann-Kendall (CMK) test to account for spatial and cross-correlation, and the adaptive False Discovery Rate (FDR) correction. Using AVHRR NDVI data over 42 years (1982–2023), we found that conventional workflow identified up to 50.96% of the Earth's terrestrial land surface as experiencing statistically significant vegetation trends. In contrast, the TST workflow reduced this to 38.16%, effectively filtering out spurious trends and providing a more accurate assessment. Among these significant trends identified using the TST workflow, 76.07% indicated greening, while 23.93% indicated browning. Notably, considering areas (pixels) with NDVI values above 0.15, greening accounted for 85.43% of the significant trends, with browning making up the remaining 14.57%. These findings strongly validate the ongoing global greening of vegetation. They also suggest that incorporating more robust analytical methods, such as the True Significant Trends (TST) approach, could significantly improve the accuracy and reliability of spatiotemporal trend analyses
PB Elsevier
YR 2024
FD 2024
LK https://hdl.handle.net/10630/35257
UL https://hdl.handle.net/10630/35257
LA eng
NO Gutiérrez-Hernández, O., García, L. v. (2024). Uncovering True Significant Trends in Global Greening. Remote Sensing Applications: Society and Environment, 37-101377. DOI: https://doi.org/10.1016/j.rsase.2024.101377
NO This publication has been funded by the Universidad de Málaga and the Consorcio de Bibliotecas Universitarias de Andalucía (CBUA) to support its open-access publication.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026