Exploring the Applicability and Scaling Effects of Satellite-Observed Spring and Autumn Phenology in Complex Terrain Regions Using Four Different Spatial Resolution Products

Abstract

The information on land surface phenology (LSP) was extracted from remote sensing data in many studies. However, few studies have evaluated the impacts of satellite products with different spatial resolutions on LSP extraction over regions with a heterogeneous topography. To bridge this knowledge gap, this study took the Loess Plateau as an example region and employed four types of satellite data with different spatial resolutions (250, 500, and 1000 m MODIS NDVI during the period 2001–2020 and ~10 km GIMMS3g during the period 1982–2015) to investigate the LSP changes that took place. We used the correlation coefficient (r) and root mean square error (RMSE) to evaluate the performances of various satellite products and further analyzed the applicability of the four satellite products. Our results showed that the MODIS-based start of the growing season (SOS) and end of the growing season (EOS) were highly correlated with the ground-observed data with r values of 0.82 and 0.79, respectively (p < 0.01), while the GIMMS3g-based phenology signal performed badly (r < 0.50 and p > 0.05). Spatially, the LSP that was derived from the MODIS products produced more reasonable spatial distributions. The inter-annual averaged MODIS SOS and EOS presented overall advanced and delayed trends during the period 2001–2020, respectively. More than two-thirds of the SOS advances and EOS delays occurred in grasslands, which determined the overall phenological changes across the entire Loess Plateau. However, both inter-annual trends of SOS and EOS derived from the GIMMS3g data were opposite to those seen in the MODIS results. There were no significant differences among the three MODIS datasets (250, 500, and 1000 m) with regard to a bias lower than 2 days, RMSE lower than 1 day, and correlation coefficient greater than 0.95 (p < 0.01). Furthermore, it was found that the phenology that was derived from the data with a 1000 m spatial resolution in the heterogeneous topography regions was feasible. Yet, in forest ecosystems and areas with an accumulated temperature ≥10 °C, the differences in phenological phase between the MODIS products could be amplified.

Spatial difference on nitrogen removal in the water based on different resolutions for Sanhuanpao wetland, Northeast China

“…The upper limit of the reasonable observation scale was 70 m for the remote sensing interpretation of the alpine pine forests of the plot in Shangri La City, and the optimal spatial scale was 50 m for biomass estimation (Wang et al, 2020). It was found that the phenology that was derived from the data with a 1,000 m spatial resolution in the heterogeneous topography regions was feasible in Loess Plateau with its numerous gullies (Chen et al, 2021). The scale effect showed the most obvious difference between the element types and the index types, while it became smaller in the range of 21–90 km and disappeared beyond 90 km.…”

Probabilistic assessment of drought stress vulnerability in grasslands of Xinjiang, China

“…The only highly significant correlation (r = -0.52519) found in our study was between elevation and the probability of meadow decline to the 30th percentile of the land during severe drought, with a smaller effect of slope and slope orientation on meadow drought ( Figure 15 ). This is because the NDVI representing grasslands in our study used lower resolution (1/12°) GIMMS data that do not capture the effects of slope and slope orientation on grassland drought ( Chen et al., 2021 ).…”

Climatic Drivers of the Complex Phenology of the Mediterranean Semi-Deciduous Shrub Phlomis fruticosa Based on Satellite-Derived EVI

“…Spring events in Louros and the other phenophases of P. fruticosa showed weak or no trends for change. The advancement of spring phenology is one of the consistent observations across Northern Europe [ 18 ], North America [ 30 ], and China [ 5 ] during the two recent decades. In Mediterranean-type ecosystems, the spring phenology trends show scattered spatial pattern according to a comprehensive study of Ivits et al [ 4 ]; over the southern Mediterranean region, an earlier start-of-season was observed, whereas over parts of the northern Mediterranean basin a growing season shift towards later dates was evident.…”

“…Our understanding of vegetation function, its interactions with the climate, the key controlling mechanisms, and its vulnerability to climate change are far from complete. Evidently, understanding climatic influences on processes and interactions enables the prediction of changes under different climatic scenarios [ 4 , 5 ].…”