###### Abstract  
The terrestrial biosphere interacts with the free atmosphere through the exchange of momentum, energy and mass. This process is mediated by the atmospheric boundary layer, influencing both weather and climate across a range of scales. In recent decades, remote sensing observations from multiple platforms have emerged as potential tools to quantify the surface fluxes and biosphere characteristics. This will allow researchers to investigate the physical, chemical, and biological processes that drive biosphere-atmosphere interactions. Recent advancement in new platforms offers new insights into the quantitative remote sensing of the biosphere. Some examples include unmanned aerial vehicles (UAVs), remote sensing techniques, and sensors, including but not limited to thermal infrared, multispectral, hyperspectral, solar-induced chlorophyll fluorescence, and light detection and ranging (LiDAR) capable of unprecedented spectral and spatiotemporal resolutions. Despite the progress in remote sensing of the biosphere-atmosphere interface at various temporal and spatial scales, integrating the observations to understand the bidirectional feedback remains a challenge due to the complexity of interactions. The special issue was aimed at exploring the use of remote sensing data from passive or active sensors onboard any ground/airborne/spaceborne platforms or its combinations with modeling efforts or other datasets in understanding the interaction at the biosphere-atmosphere interface from local to global scales. A total of five manuscripts, four research articles and a review, were published from twelve submissions after the rigorous review process. The major topics covered in this Special Issue mostly utilized in situ measurements and remote sensing data, retrieved by ground/satellite-based sensors. The topics also included evaluations of uncertainties in remote sensing data products over different land cover types and climate regimes to understand the limitations of retrieval algorithms and improve confidence in remote sensing observations. Two papers [1, 2] in this Special Issue focus on improving the estimation of evapotranspiration (ET), using both direct and indirect methods. [PERSON] et al. [1] compared daily evapotranspiration (ET) estimations using direct calculation (DC) and temporal scaling by constant reference evaporative fraction methods, using long-term field and satellite data obtained from Moderate-resolution Imaging Spectroradiometer (MODIS) sensors. These data cover the period from late April 2009 to late October 2010 at the Yucheng site in China. They validated the estimated ET using eddy covariance (EC) ET from the Yucheng site, both with and without the correction of energy imbalance, and found that the DC method performed with higher accuracy when compared to uncorrected EC measurements. The study provides scientific guidance for developing an operational method for accurate daily ET estimates, with the potential to be applied across various climate types and geographic locations. [PERSON] et al. [2] evaluated the performance of multiple high spatial resolution evapotranspiration products over the Lancang-Mekong River Basin (LMRB), Southeast Asia. They compared the MODIS global terrestrial evapotranspiration product (MOD16), the ETproduct based on the Penman-Monteith-Leuning equation version 2 (PML-V2), the ET product based on the Breathing Earth System Simulator (BESS), and the ET product of the Global Land Surface Satellite (GLASS) with eddy covariance ET from 11 sites over different vegetation types in the LMRB region. Their results revealed that PML-V2 performs best in evergreen broadleaf forests, BESS performs best in deciduous broadleaf forests and croplands, and GLASS performs best in shrubs, grasslands, and mixed vegetation. Indeed, all of the above products performed well compared with MODIS ET. Their study reveals the inconsistent performance of the four ET products and discusses the possible ways to improve the accuracy of ET products over LMRB. [PERSON] et al.