Drought is a complex hazard, and it has an impact on agricultural, ecological, and socio-economic systems. The vegetation condition index (VCI), which is derived from remote-sensing data, has been widely used for drought monitoring. However, VCI based on the normalized difference vegetation index (NDVI) does not perform well in certain circumstances. In this study, we examined the utility of the vegetation index based on the universal pattern decomposition method (VIUPD) based VCI for drought monitoring in various climate divisions across the continental United States (CONUS). We compared the VIUPD-derived VCI with the NDVI-derived VCI in various climate divisions and during different sub-periods of the growing season. It was also compared with other remote-sensing-based drought indices, such as the temperature condition index (TCI), precipitation condition index (PCI) and the soil moisture condition index (SMCI). The VIUPD-derived VCI had stronger correlations with long-term in situ drought indices, such as the Palmer Drought Severity Index (PDSI) and the standardized precipitation index (SPI-3, SPI-6, SPI-9, and SPI-12) than did the NDVI-derived VCI, and other indices, such as TCI, PCI and SMCI. The VIUPD has considerable potential for drought monitoring. As VIUPD can make use of the information from all the observation bands, the VIUPD-derived VCI can be regarded as an enhanced VCI.

Rising atmospheric dryness [vapor pressure deficit (VPD)] can limit photosynthesis and thus reduce vegetation productivity. Meanwhile, plants can benefit from global warming and the fertilization effect of carbon dioxide (CO₂). There are growing interests to study climate change impacts on terrestrial vegetation. However, global vegetation productivity responses to recent climate and CO₂ trends remain to be fully understood. Here, we provide a comprehensive evaluation of the relative impacts of VPD, temperature, and atmospheric CO₂ concentration on global vegetation productivity over the last two decades using a robust ensemble of solar‐induced chlorophyll fluorescence (SIF) and gross primary productivity (GPP) data. We document a significant increase in global vegetation productivity with rising VPD, temperature, and atmospheric CO₂ concentration over this period. For global SIF (or GPP), the decrease due to rising VPD was comparable to the increase due to warming but far less than the increase due to elevated CO₂ concentration. We found that rising VPD counteracted only a small proportion (approximately 8.1%–15.0%) of the warming and CO₂‐induced increase in global SIF (or GPP). Despite the sharp rise in atmospheric dryness imposing a negative impact on plants, the warming and CO₂ fertilization effects contributed to a persistent and widespread increase in vegetation productivity over the majority (approximately 66.5%–72.2%) of the globally vegetated areas. Overall, our findings provide a quantitative and comprehensive attribution of rising atmospheric dryness on global vegetation productivity under concurrent climate warming and CO₂ increasing.

Resilience is a fundamental concept for vegetation health. The increasing drought frequency and severity may pose severe threat to vegetation resilience. However, it is still not clear how vegetation resilience is evolving in response to climate change in pivotal biographical zones. Here, we examined the resilience changes in terms of leaf area index (LAI, an indicator of canopy structure) and gross primary productivity (GPP, an indicator of carbon uptake) in responding to the Standardized Precipitation‐Evapotranspiration Index (SPEI) and vapor pressure deficit (VPD) over China's Loess Plateau and Qinling Mountains. Linking remote sensing variables and tree ring width allows the upscaling of plot‐based vegetation growth information. We further explored potential explanatory factors associated with the heterogeneous spatial distributions of resilience changes. Results revealed that the resilience of GPP weakened more than LAI in response to drought, suggesting that compared to LAI, productivity requires more time to recover to the pre‐drought levels. Regionally, the change of vegetation resilience on the Loess Plateau and in high‐altitude areas was highly susceptible to SPEI and VPD, respectively. The observed spatial heterogeneity in resilience changes was mainly attributed by climate zone, water deficit, and their interactions. Our findings provide direct and empirical evidence that the vegetation in the Loess Plateau and Qinling Mountains is gradually losing resilience. The results indicate that sustained ecosystem water deficit and atmospheric dryness will continue to threaten vegetation survival and terrestrial ecosystem service.

Surface temperatures are mechanistically linked to vegetation biophysical and physiological processes. Although remote sensing in the thermal infrared (TIR) domain can offer novel insights into the impacts of changing surface temperatures on vegetation, the transformative potential of remote sensing for plant ecology has not yet been realized. Remotely sensed surface temperatures can be used to derive stomatal behaviour and identify stressful environmental conditions in near‐real time. Plant species, traits and structural characteristics can be evaluated with high spectral resolution TIR emissivity. Beyond canopy scales, thermal remote sensing can enhance the inferences obtained from manipulative experiments and empirical evidence, providing unique insight into shifts in species ranges and phenology with changing climate conditions. Scaling leaf traits, canopy structure and regional patterns require an integrated understanding of both process and technology. Theory linking surface temperatures to vegetation dynamics is summarized from an energy balance perspective. We outline scaling considerations including the impacts of morphology on leaf energy balance, canopy structure influences on convective heat exchange and potential confounding impacts of non‐vegetated surfaces. Synthesis. We introduce a unifying framework to link leaf to globe through thermal remote sensing. Recent and emerging advances in sensors, data availability and analytics, together with synergies between TIR remote sensing and other data sources, present a timely opportunity for ecologists to advance our understanding of plant physiology, ecology and biogeography with thermal remote sensing.