Vegetation is a key element in the energy, water and carbon balances over the land surfaces and is strongly impacted by climate change and anthropogenic effects. Remotely sensed observations are commonly used for the monitoring of vegetation dynamics and its temporal changes from regional to global scales. Among the different indices derived from Earth observation satellites to study the vegetation, the vegetation optical depth (VOD), which is related to the intensity of extinction effects within the vegetation canopy layer in the microwave domain and which can be derived from both passive and active microwave observations, is increasingly used for monitoring a wide range of ecological vegetation variables. Based on different frequency bands used to derive VOD, from L- to Ka-bands, these variables include, among others, the vegetation water content/status and the above ground biomass. In this review, the theoretical bases of VOD estimates for both the passive and active microwave domains are presented and the global long-term VOD products computed from various groups in the world are described. Then, major findings obtained using VOD are reviewed and the perspectives offered by methodological improvements and by new sensors onboard satellite missions recently launched or to be launched in a close future are presented.

Terrestrial sequestration of carbon has mitigated ≈30% of anthropogenic carbon emissions. However, its distribution across different pools, live or dead biomass and soil and sedimentary organic carbon, remains uncertain. Analyzing global observational datasets of changes in terrestrial carbon pools, we found that ≈35 ± 14 gigatons of carbon (GtC) have been sequestered on land between 1992 and 2019, whereas live biomass changed by ≈1 ± 7 GtC. Global vegetation models instead imply that sequestration has been mostly in live biomass. We identify key processes not included in most models that can explain this discrepancy. Most terrestrial carbon gains are sequestered as nonliving matter and thus are more persistent than previously appreciated, with a substantial fraction linked to human activities such as river damming, wood harvest, and garbage disposal in landfills.

In the Amazon, deforestation and climate change lead to increased vulnerability to forest degradation, threatening its existing carbon stocks and its capacity as a carbon sink. We use satellite L‐Band Vegetation Optical Depth (L‐VOD) data that provide an integrated (top‐down) estimate of biomass carbon to track changes over 2011–2019. Because the spatial resolution of L‐VOD is coarse (0.25°), it allows limited attribution of the observed changes. We therefore combined high‐resolution annual maps of forest cover and disturbances with biomass maps to model carbon losses (bottom‐up) from deforestation and degradation, and gains from regrowing secondary forests. We show an increase of deforestation and associated degradation losses since 2012 which greatly outweigh secondary forest gains. Degradation accounted for 40% of gross losses. After an increase in 2011, old‐growth forests show a net loss of above‐ground carbon between 2012 and 2019. The sum of component carbon fluxes in our model is consistent with the total biomass change from L‐VOD of 1.3 Pg C over 2012‐2019. Across nine Amazon countries, we found that while Brazil contains the majority of biomass stocks (64%), its losses from disturbances were disproportionately high (79% of gross losses). Our multi‐source analysis provides a pessimistic assessment of the Amazon carbon balance and highlights the urgent need to stop the recent rise of deforestation and degradation, particularly in the Brazilian Amazon.

Long-term surface soil moisture (SM) data are increasingly needed in water budget and energy balance analysis of watersheds. The performance of nine remotely sensed SM products from Advanced Microwave Scanning Radiometer 2 (AMSR2), Soil Moisture and Ocean Salinity (SMOS), and Soil Moisture Active Passive (SMAP) missions are evaluated based on observations collected from distributed observation networks in the Heihe River Basin (HRB) of China during 2013 to 2017. Results show that the SMAP Level 3 dual channel algorithm SM retrievals reflect the seasonal SM variations well with high temporal correlations of ∼0.7 and high accuracy within 0.04 m ³ /m ³ in terms of unbiased root mean squared error (ubRMSE) over the grassland in the HRB. The SMOS level 3 SM retrievals present increased underestimation and ubRMSE of ∼0.10 m ³ /m ³ as the vegetation increases. The newly published SMOS Institut National de la Recherche Agronomique–Centre d'Etudes Spatiales de la BIOsphère product in version 2 outperforms the SMOS level 3 product with improved temporal correlation coefficient above 0.4 and lower ubRMSE of ∼0.05 m ³ /m ³ . AMSR2 Land Parameter Retrieval Algorithm SM products show extremely large overestimation over the vegetated regions in HRB, especially the C-band products. Drastically high underestimation biases are observed in the Japan Aerospace Exploration Agency AMSR2 SM product. Parameter uncertainty analyses indicate that the different parameterization schemes of vegetation optical depth inputs could be one of the main reasons resulting in the systematic overestimation/underestimation biases in the AMSR2/SMOS/SMAP SM retrievals. The findings aim to provide insights into studies on algorithms refinements and data fusions of SM products in HRB.

Semi-transparent polymer solar cells (ST-PSCs) have attracted great attention recently because of their potential for application in smart windows, etc. Here, we fabricated ST-PSCs based on a low band-gap conjugated polymer, PTB7-Th, as the donor and a narrow band-gap n-type organic semiconductor (n-OS), ITVfIC, as the acceptor. The active layer (with a thickness of 100 nm) of the ST-PSC exhibits a high average transmittance (AT) of 73.46% in the wavelength range of 400–600 nm. The as-cast ST-PSC with 15 nm Ag as the cathode without any additive or thermal-annealing treatment shows a higher power conversion efficiency (PCE) of 8.21% with an AT of 33.7%, which is one of the highest values for ST-PSCs without extra treatment. In addition, the ST-PSCs show good thermal stability with 91% of their original PCE value retained after high temperature treatment at 200 °C for 2 hours. The higher PCE and good stability indicate that the ST-PSC has potential for practical application and the narrow bandgap ITVfIC could be a promising n-OS acceptor for the fabrication of ST-PSCs.