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The end of growing season (EOS) is an effective indicator of annual vegetation growth. Previous studies have revealed the dynamics of the EOS with climate change, while the influence of vegetation growth in preceding stage and peak of growing season (POS) on the EOS has not been thoroughly documented. In this study, we used four smoothing methods to obtain EOS dates from the Normalized Difference Vegetation Index (NDVI) in northeast Inner Mongolia (NIM) between 2001–2017, assessed the differences in the spatiotemporal variations of the EOS obtained by the four smoothing methods, and then investigated the impacts of climate factors, summer/ autumn vegetation growth and POS on the EOS. The results showed that the EOS dates obtained with different smoothing methods were broadly consistent in terms of their spatial patterns and temporal trends. In terms of climate factors, the EOS was driven mainly by preseason precipitation for the majority of vegetation types and advanced with increasing precipitation. For the steppe, both minimum temperature (Tmin) and relative humidity (RHU) played the most important roles in regulating the variation of EOS which was delayed with an increase in Tmin and reduction in RHU. Furthermore, our study found an earlier POS and vigorous vegetation growth in summer would jointly advance the steppe EOS, but these relationships were the opposite of each other in meadow and forest regions. Interestingly, the EOS of NIM was more related with vegetation growth in the most recent period before the EOS. This study highlights the importance of ecological processes in the preceding growth stage for understanding the dynamics of EOS.

The vegetation in desert/grassland biome transition zones is part of a fragile ecosystem that is sensitive to climate change. Thus, in recent decades, studying vegetation activity in desert/grassland biome transition zones has become important. Here, vegetation activity and the evolutionary tendencies of the temporal and spatial differentiation of the phenology of the desert/grassland biome transition zones were analyzed based on the Normalized Difference Vegetation Index (NDVI) of the third-generation Global Inventory Modeling and Mapping Studies (GIMMS3g) dataset. Additionally, the relationship between vegetation activity and climatic factors was analyzed based on NDVI and global meteorological reanalysis data. The results showed that the vegetation phenology of desert/grassland biome transition zones exhibits sharply contrasting characteristics between the Northern and Southern hemispheres, particularly when comparing differences before and after the breakpoint in global climate change (1998). The length of the growing season (LOS) of the Northern Hemisphere was shorter after 1998 than before it, and the integral of the growing season (IOS) of the NDVI decreased correspondingly. By contrast, the LOS in the Southern Hemisphere was longer, and after 1998, the IOS of the NDVI increased compared to its previous value. The vegetation activity trend and the fluctuation of the desert/grassland biome transition zones in the last 30 years can be divided into nine combined modes. However, these features also have an obvious turning point in 1998. The effects of evapotranspiration and precipitation on vegetation activity were most obvious, and these climatic factors drove the phenology changes in the different regions. Global warming limited the vegetation activity in low-latitude areas, but promoted it in middle-latitude areas.

Using the normalized difference vegetation index (NDVI) and climate data, we calculated the end of the growing season (EOS; unit: day-of-year (DOY)) on the Mongolian Plateau and explored the effects of the climate, the start of the growing season (SOS), and the annual peak growth (APG, unit: NDVI) of vegetation and its timing (peak growth time, PGT) on the EOS for the period of 1982-2013. The spatial distribution pattern of the EOS on the plateau presented a gradual delay from south to north in Mongolia and from southwest to northeast in Inner Mongolia, and spatially it was highly related to vegetation producty. During 1982-2013, the area-averaged EOS varied between 265.2 and 278.3, and showed a slight but non-significant advancing trend of 0.6 days decade–1, with a breaking point occurring in 1993. This insignificant advance resulted from substantial spatial heterogeneities of the trend in EOS, with advances in widespread grassland-dominated regions and delays in southwestern Inner Mongolia. Preseason air temperature (preseason means of the periods prior to the EOS date related to the EOS variation) exerted positive effects on the EOS in wet and cold areas in northern Mongolia, while preseason precipitation exerted positive effects in widespread arid and semiarid regions in central grassland regions, with different preseason lengths varying according to meteorological variables and locations. More importantly, we identified strong influences of the SOS (r=0.46, p=0.008), APG (r=0.35, p=0.05), and PGT (r=0.76, p

The Temperature Vegetation Dryness Index (TVDI), a drought monitoring index based on an empirical parameterization of the Land Surface Temperature (LST)–Normalized Difference Vegetation Index (NDVI) space, has been widely implemented in a variety of ecosystems worldwide because it does not depend on ancillary data. However, the simulation of dry/wet edges in the TVDI model can be problematic because remote sensing images do not have sufficient pixels to identify the wetness and dryness extremes of different vegetation coverages. In this study, an improvement in dry/wet edge simulation was proposed, and a comparison of the original TVDI and the modified Temperature Vegetation Dryness Index (TVDIm) was performed for drought monitoring in Ningxia Province, which is a typical semi-arid region in China. First, the difference between the land surface temperatures in day and night (∆LST) was used as an alternative to LST when building the TVDIm model. In addition, the wet edges were improved by removing outliers using a statistical method, and the dry edges were optimized by removing the “tail down” points in the NDVI range of 0.0–0.1. Here, the modeling process of TVDIm in 2005, one of recent extreme drought year is illustrated. The results show that both the TVDI and TVDIm can be used to monitor the temporal and spatial variations of drought, and the onset, duration, extent, and severity of drought can be reflected by TVDI and TVDIm maps. However, the magnitude of TVDI is higher than that of TVDIm, which could cause the TVDI-simulated drought condition to be elevated in normal years and underestimated in dry years. The TVDIm has higher coefficients of correlation with in situ meteorological drought index and agricultural drought statistical data than does the original TVDI, and it exhibits better performance in drought monitoring compared to that of the original TVDI in semi-arid regions of China.

Understanding of the pattern of agricultural drought and the way it responses to climate change in winter wheat growth season is critical for crop production in China. The remotely sensed MSAVI and NDWI time series and daily meteorological elements for the main growth season and four separate growth stages of winter wheat from 2000 to 2010 were used to analyze the temporal and spatial distribution and the trend of agricultural drought and climate change respectively in Huang-Huai-Hai region(HHH region), China. The results indicated that the total trend of agricultural drought in HHH region past decade was declining, but increasing in the north, which had significant correlation to the decreasing trend of temperature and increasing trend of precipitation. And the sensitivity of the indices response to temperature change is larger than precipitation. The study could provide a basis for agricultural drought research during winter wheat season in HHH region under the ground of climate change.