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Ocean warming is increasing the incidence, scale, and severity of global-scale coral bleaching and mortality, culminating in the third global coral bleaching event that occurred during record marine heatwaves of 2014-2017. While local effects of these events have been widely reported, the global implications remain unknown. Analysis of 15,066 reef surveys during 2014-2017 revealed that 80% of surveyed reefs experienced significant coral bleaching and 35% experienced significant coral mortality. The global extent of significant coral bleaching and mortality was assessed by extrapolating results from reef surveys using comprehensive remote-sensing data of regional heat stress. This model predicted that 51% of the world’s coral reefs suffered significant bleaching and 15% significant mortality, surpassing damage from any prior global bleaching event. These observations demonstrate that global warming’s widespread damage to coral reefs is accelerating and underscores the threat anthropogenic climate change poses for the irreversible transformation of these essential ecosystems.

Hydrographic sounding selection is the process of generalizing high-resolution bathymetry data to a more manageable subset capable of supporting nautical chart compilation or bathymetric modeling, and thus, is a fundamental task in nautical cartography. As technology improves and bathymetric data are collected at higher resolutions, the need for automated generalization algorithms that respect nautical cartographic constraints increases, since errors in this phase are carried over to the final product. Currently, automated algorithms for hydrographic sounding selection rely on radius- and grid-based approaches; however, their outputs contain a dense set of soundings with a significant number of cartographic constraint violations, thus increasing the burden and cost of the subsequent, mostly manual, cartographic sounding selection. This work presents a novel label-based generalization algorithm that utilizes the physical dimensions of the symbolized depth values on charts to avoid the over-plot of depth labels at scale. Additionally, validation tests based on cartographic constraints for nautical charting are implemented to compare the results of the proposed algorithm to radius and grid-based approaches. It is shown that the label-based generalization approach best adheres to the constraints of functionality (safety) and legibility.

In the 1990’s, the International Maritime Organization (IMO) adopted the International Hydrographic Office’s (IHO) S-57 performance standards for Electronic Navigation Charts (ENC), which enforce standardized content, structure, and format. The IMO also revised its Safety of Life at Sea (SOLAS) chapter V regulations to require Electronic Chart Display and Information Systems (ECDIS) onboard certain SOLAS class vessels, starting from 2018. These systems allow for navigating with ENC data, which has several advantages over paper charts; however, many mariners still prefer traditional paper or raster charts. Through the feedback of key stakeholders such as local pilot associations, it has become apparent that the preference for raster or paper charts is due to the inclusion of non-critical S-57 land features. These S-57 land features, which are typically not added to ENC products, such as roads and elevation contours, can supplement navigational positioning systems by providing visual references, particularly when other landmarks (e.g., spot elevations on major topographic features) are not present on the ENC. Moreover, charting roads on ENC products can be useful for locating water access points. This paper discusses the addition of roads and land elevation contours to NOAA’s re-schemed ENC suite in an effort to supplement currently charted marine features and land features crossing over water. General cartographic guidelines have also been developed for the representation of these features through ENC scales (i.e., usage bands 3 to 5). Additionally, this paper includes a discussion on the benefits and challenges of incorporating publicly available land transportation data versus traditional sources on ENC products.