###### Abstract
[3] explored the use of long-term MODIS normalized difference vegetation index (NDVI) and climate data (precipitation and temperature), derived from the meteorological stations, to evaluate the effects of climate change on vegetation growth in the Yellow River Basin (YRB) from 2000 to 2019. The results indicate that the spatial variations of precipitation, temperature, and NDVI were heterogeneous, and the correlations between NDVI and climate variables varied with seasons in the YRB from 2000-2019. Both NDVI and climatic variables exhibited overall increasing trends during this period. Exceptions to this were a number of locations in the northern, southern, and southwestern regions of the YRB. This study contributes to improving the current understanding of the spatiotemporal relationships between precipitation, temperature and vegetation dynamics in the YRB region and provides guidance on the restoration efforts of the functional ecosystem in this area. [PERSON] et al. [4] presented a method for predicting soil respiration using plant productivity in a subarctic tundra site in northern Sweden. They used NDVI from a handheld spectrometer and chamber-based soil CO2 efflux measurements to establish the relationship between aboveground plant productivity and belowground soil respiration. Their results indicate that a combination of ground-based remote sensing products (NDVI) and in situ sampling of soil temperature adequately predicted soil respiration and highlighted the more complicated relationship between vegetation productivity and soil organic carbon in a highly heterogeneous ecosystem. This study highlights the potential to estimate and map soil respiration at a landscape scale using high-resolution UAV and multi-spectral satellite imagery, especially important for understanding soil carbon dynamics in a warming Arctic. [PERSON] et al. [5] reviewed the current progress in direct and indirect estimation methods of ecosystem water use efficiency (WUE), a key variable for understanding the ecosystem of carbon-water coupling, by remote sensing. They examined various methods for estimating WUE by utilizing ecosystem level gross primary production (GPP)/evaptranspiration (ET) from ground-based eddy covariance observations, processed-based models and remote sensing. This review also assessed the challenges in WUE remote sensing, uncertainties and limitations of the above-mentioned methods for WUE estimation, and possible ways of improving WUE remote sensing by data fusion, analytical models, intelligent algorithms and big data platforms. This review gives insight into multiple approaches, new mechanistic models for our understanding of ecosystem carbon-water cycle coupling across different scales. Utilizing remote sensing technology to elucidate biosphere-atmosphere interactions is a challenging and emerging research topic that has the potential to remain an area of great interest to the scientific community in the coming decades. The five manuscripts published here reveal meaningful progress on different aspects of this research by providing new methods and techniques and demonstrating the use of conventional in situ measurements in improving and validating remote sensing data products. The Special Issue highlights the potential of using remote sensing to study biosphere-atmosphere interactions across various spatial and temporal scales and serves as a steppingstone for further efforts to integrate multisource remote sensing observations using advanced methods for a better understanding of bi-directional feedbacks at the biosphere-atmosphere interface. **Author Contributions:** Conceptualization, P.K. and S.W. ; writing--original draft preparation, P.K. ; review and editing; P.K. and S.W. All authors have read and agreed to the published version of the manuscript. **Acknowledgments:** The guest editors would like to thank all authors who have contributed their research work to this Special Issue and the reviewers for their valuable time and insightful comments on the papers.