Visible satellite imagery (VIS) is essential for monitoring weather patterns and tracking ground surface changes associated with climate change. However, its availability is limited during nighttime. To address this limitation, we present a discrete variational autoencoder (VQVAE) method for translating infrared satellite imagery to VIS. This method departs from previous efforts that utilize a U-Net architecture. By removing the connections between corresponding layers of the encoder and decoder, the model learns a discrete and rich codebook of latent priors for the translation task. We train and test our model on mesoscale data from the Geostationary Operational Environmental Satellite (GOES) West Advanced Baseline Imager (ABI) sensor, spanning 4 years (2019 to 2022) using the Conditional Generative Adversarial Nets (CGAN) framework. This work demonstrates the practical use of a VQVAE for meteorological satellite image translation. Our approach provides a modular framework for data compression and reconstruction, with a latent representation space specifically designed for handling meteorological satellite imagery.

Since the 1990s, Pine Island Glacier (PIG) has been a focal point of research due to its vulnerability within the West Antarctic Ice Sheet. Decades of research have interrogated this dynamic glacier system with a focus on its main trunk and the ice shelf section bordering and stabilizing PIG to the south (the ‘south shelf’), receiving comparatively less attention. Using satellite-derived observations from 2017 to 2023, we document marked dynamic changes on the south shelf, particularly following PIG’s 2018 calving event, which removed >60 km2 of ice from this section. Measurements of surface deformation, ice velocity and strain rates from synthetic aperture radar and optical imagery show localized acceleration and structural weakening of the south shelf near-coincident with this loss. Our findings, highlighting the role of peripheral ice shelves in glacier-system stability, suggest that PIG’s new configuration—characterized by weakening margins and a compromised south shelf—may result in a geometry that grows progressively unstable.

Satellite remote sensing is vital for monitoring anthropogenic changes and for alerting us to escalating environmental threats. With recent technological advances, a variety of satellite-based monitoring systems are available to aid conservation practitioners. Yet, documented knowledge of who uses near-real-time satellite-based monitoring and how these technologies are applied to inform conservation decisions is sparse. Through an online survey and semi-structured interviews, we explored how developers and users leverage conservation early-warning and alert systems (CEASs) for enhanced conservation decisions. Some 167 developers and users of near-real-time fire and forest monitoring systems from 40 countries participated in this study. Globally, respondents used 66 unique CEASs. The most common applications were for education and awareness, fire/disaster management and law enforcement. Respondents primarily used CEASs to enforce land-use policies and deter illegal activities, and they perceived these tools as underutilized for incentivizing policy compliance or conservation. Respondents experienced inequities regarding system access, exposure and ability to act upon alert information. More investments in capacity-building, resources and action plans are needed to better link information to action. Implementing recommendations from this research can help us to increase the accessibility and inclusivity of CEAS applications to unlock their powerful capabilities for achieving conservation goals.

Remote sensing is a powerful method to reconstruct annual mass-balance series over past decades by exploiting archives of available images, as well as to study glaciers in inaccessible regions. We present the application of a methodological framework based only on optical satellite images to retrieve glacier-wide annual mass balances for 30 glaciers in the French Alps. The glacier-wide annual mass balance for the period 1983–2014 was reconstructed by combining changes in glacier volumes computed from remote-sensing derived DEMs with annual measurements of the snow line altitude on satellite images. Data from direct observations on two of the glaciers confirmed the accuracy of the annual mass balances quantified by remote sensing with an average difference of ~0.3 m w.e., within the uncertainty range of the methods. Our results confirm the significant increase in mass loss since the early 2000s, with a difference >1 m w.e. a−1 between the periods 1983–2002 and 2003–14. The region-wide mass balance for the French Alps over the period 1979–2011 was −0.66 ± 0.27 m w.e. a−1, close to that of the European Alps. We also show that changes in glacier surface area or length are not representative of changes in mass balance at the scale of a few decades.