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USGS2018

Interoperability in planetary research for geospatial data analysis

For more than a decade there has been a push in the planetary science community to support interoperable methods for accessing and working with geospatial data. Common geospatial data products for planetary research include image mosaics, digital elevation or terrain models, geologic maps, geographic location databases (e.g., craters, volcanoes) or any data that can be tied to the surface of a planetary body (including moons, comets or asteroids). Several U.S. and international cartographic research institutions have converged on mapping standards that embrace standardized geospatial image formats, geologic mapping conventions, U.S. Federal Geographic Data Committee (FGDC) cartographic and metadata standards, and notably on-line mapping services as defined by the Open Geospatial Consortium (OGC). The latter includes defined standards such as the OGC Web Mapping Services (simple image maps), Web Map Tile Services (cached image tiles), Web Feature Services (feature streaming), Web Coverage Services (rich scientific data streaming), and Catalog Services for the Web (data searching and discoverability). While these standards were developed for application to Earth-based data, they can be just as valuable for planetary domain. Another initiative, called VESPA (Virtual European Solar and Planetary Access), will marry several of the above geoscience standards and astronomy-based standards as defined by International Virtual Observatory Alliance (IVOA). This work outlines the current state of interoperability initiatives in use or in the process of being researched within the planetary geospatial community.

Planetary and Space Science↗

USGS2012

Selection of the Mars Science Laboratory landing site

The selection of Gale crater as the Mars Science Laboratory landing site took over five years, involved broad participation of the science community via five open workshops, and narrowed an initial >50 sites (25 by 20 km) to four finalists (Eberswalde, Gale, Holden and Mawrth) based on science and safety. Engineering constraints important to the selection included: (1) latitude (±30°) for thermal management of the rover and instruments, (2) elevation (<-1 km) for sufficient atmosphere to slow the spacecraft, (3) relief of <100-130 m at baselines of 1-1000 m for control authority and sufficient fuel during powered descent, (4) slopes of <30° at baselines of 2-5 m for rover stability at touchdown, (5) moderate rock abundance to avoid impacting the belly pan during touchdown, and (6) a radar-reflective, load-bearing, and trafficable surface that is safe for landing and roving and not dominated by fine-grained dust. Science criteria important for the selection include the ability to assess past habitable environments, which include diversity, context, and biosignature (including organics) preservation. Sites were evaluated in detail using targeted data from instruments on all active orbiters, and especially Mars Reconnaissance Orbiter. All of the final four sites have layered sedimentary rocks with spectral evidence for phyllosilicates that clearly address the science objectives of the mission. Sophisticated entry, descent and landing simulations that include detailed information on all of the engineering constraints indicate all of the final four sites are safe for landing. Evaluation of the traversabilty of the landing sites and target “go to” areas outside of the ellipse using slope and material properties information indicates that all are trafficable and “go to” sites can be accessed within the lifetime of the mission. In the final selection, Gale crater was favored over Eberswalde based on its greater diversity and potential habitability.

Space Science Reviews↗

USGS2023

Lessons learned from the 2022 CONVERSE Monogenetic Volcanism Response Scenario exercise

When volcanic unrest occurs, the scientific community can advance fundamental understanding of volcanic systems, but only with coordination before, during, and after the event across academic and governmental agencies. To develop a coordinated response plan, the Community Network for Volcanic Eruption Response (CONVERSE) orchestrated a scenario exercise centered around a hypothetical volcanic crisis in Arizona’s San Francisco Volcanic Field (SFVF). The exercise ran virtually from February 4 to March 4, 2022. Over 60 scientists from both academic and governmental spheres participated. The scenario exercise was assessed for its effectiveness in supporting collaborative production of knowledge, catalyzing transdisciplinary collaboration, supporting researcher confidence, and fostering a culture of inclusion within the volcanology community. This identified a need to support early career researchers through community and allyship. Overall, the 2022 CONVERSE exercise demonstrated how a fully remote, extended scenario can be authentically implemented and help broaden participation within the volcano science community.

Arizona↗

USGS2024

Best practices for incorporating climate change science into Department of the Interior analyses, consultations, and decision making

The purpose of this document is to provide technical guidance, practical application examples, and resource lists for those who conduct, manage, and/or interpret technical workflows within the Department of the Interior. This document is intended to support implementation of Department of the Interior policy 526 DM 1 and establish best practices for using climate change science to inform analysis, consultation, and decision making. The Earth’s climate is an interconnected system that distributes energy, heat, and water around the planet. Due to human-driven increases in long-lived greenhouse gases, the Earth’s climate is now changing. For Departmental decision-making purposes, assuming a static, unchanging baseline climate is no longer consistent with current knowledge about the climate system. There are uncertainties about future climate and how resources or assets (RoAs) will respond to new conditions. To depict the possibilities, the global climate science community develops scenarios and models to explore how future climate may respond to socioeconomic and technological development in the world. Principles for informing policy development, planning and decisions, and regulatory processes using climate change science must: 1) consider the effects of future climate change, 2) characterize the risks, and 3) characterize the uncertainties. Best practices include: Use multiple scenarios to assess risks from a range of plausible societal pathways. When constraints prevent the use of multiple scenarios or if decision makers are risk averse, ensure that the chosen scenario considers higher risk outcomes. This is particularly important for large investments or irreversible decisions and reduces the chances of overconfident decision making. Use multiple climate models within each scenario to account for the range of outcomes due to model uncertainty. Do not rely solely on a single model or an ensemble average. Use relevant climate data . Use a time-period for model projections of the future climate change consistent with the relevant timeframe of the policy, action, or decision being considered. Historical observations are useful for understanding past conditions and climate trends for the next several years, but not beyond the next decade. Consult with climate data and modeling experts to assess which data and model resources are most appropriate for any given application. Clearly describe key analysis uncertainties (including with any climate observations, models, and scenarios used), and how they were addressed in the analysis and/or decision process. This ensures transparency and learning among analysts and decision makers.

Report↗

USGS2026

Advancing monitoring approaches to enhance tidal Chesapeake Bay habitat assessment for submerged aquatic vegetation, water clarity, chlorophyll a and dissolved oxygen

Water quality monitoring capacity has been declining for the Chesapeake Bay Program (CBP) at a time when information needs are growing, and data gaps exist to address critical decision-support for managers. The CBP Scientific Technical Assessment and Reporting Team is leading a Principal’s Staff Committee requested gap analyses toward understanding support needed to improve water quality monitoring and analysis programming. Advanced technologies and alternative monitoring approaches in the form of satellite-based measurements, Artificial Intelligence/Machine Learning (AI/ML) algorithms for data interpretation, continuous water quality in-situ sensor arrays, and community science efforts offer a growing portfolio of valuable opportunities for expanding data collections and analysis program capacities. However, since 1985, each of these options are examples of growing opportunities to enhance water quality assessments yet has seen limited adoption into elements of Chesapeake Bay water quality monitoring programs. Where new technologies have been adopted (e.g., shallow water continuous water quality monitoring), such temporally rich data streams have supported Bay health insights yet had limited use in regulatory water quality criteria assessment. This Scientific Technical Advisory Committee (STAC) supported workshop provided the ideal forum for engaging our CBP partnership regarding the maturity of new and evolving monitoring and analysis capacities to address program information needs while appreciating limitations with adopting new tools and approaches. Improving natural resources monitoring efficiency and effectiveness will expand the scientific and technical foundations for making robust, strategic choices on decisions for CBP Partnership community-based priorities, policies, and management actions. Workshop findings and recommendations reflect progress in science, technology, and analyses addressing long-standing programmatic limitations in data collection and analysis capacities. State-of-the-science updates highlighted in the workshop span the spectrum of efforts representing improvements, successes, remaining challenges toward operationalizing protocols, and guidance toward research, or adoption and implementation by monitoring programs.

Maryland, Pennsylvania, Virginia↗

USGS2020

Changes to Monitoring Trends in Burn Severity Program’s production procedures and data products

The Monitoring Trends in Burn Severity (MTBS) program has been providing the fire science community with large fire perimeter and burn severity data for the past 14 years. As of October 2019, 22 969 fires have been mapped by the MTBS program and are available on the MTBS website ( https://www.mtbs.gov ). These data have been widely used by researchers to examine a variety of fire and climate science topics. However, MTBS has undergone significant changes to its fire mapping methodology, the remotely sensed imagery used to map fires, and the subsequent fire occurrence, burned boundary, and severity databases. To gather a better understanding of these changes and the potential impacts that they may have on the user community, we examined the changes to the MTBS burn mapping protocols and whether remapped burned area boundary and severity products differ significantly from the original MTBS products.

Fire Ecology↗

USGS2021

Science storms the cloud

The core tools of science (data, software, and computers) are undergoing a rapid and historic evolution, changing what questions scientists ask and how they find answers. Earth science data are being transformed into new formats optimized for cloud storage that enable rapid analysis of multi-petabyte data sets. Data sets are moving from archive centers to vast cloud data storage, adjacent to massive server farms. Open source cloud-based data science platforms, accessed through a web-browser window, are enabling advanced, collaborative, interdisciplinary science to be performed wherever scientists can connect to the internet. Specialized software and hardware for machine learning and artificial intelligence are being integrated into data science platforms, making them more accessible to average scientists. Increasing amounts of data and computational power in the cloud are unlocking new approaches for data-driven discovery. For the first time, it is truly feasible for scientists to bring their analysis to data in the cloud without specialized cloud computing knowledge. This shift in paradigm has the potential to lower the threshold for entry, expand the science community, and increase opportunities for collaboration while promoting scientific innovation, transparency, and reproducibility. Yet, we have all witnessed promising new tools which seem harmless and beneficial at the outset become damaging or limiting. What do we need to consider as this new way of doing science is evolving?

AGU Advances↗

USGS2022

Community established best practice recommendations for tephra studies— From collection through analysis

Tephra is a unique volcanic product with an unparalleled role in understanding past eruptions, long-term behavior of volcanoes, and the effects of volcanism on climate and the environment. Tephra deposits also provide spatially widespread, high-resolution time-stratigraphic markers across a range of sedimentary settings and thus are used in numerous disciplines (e.g., volcanology, climate science, archaeology). Nonetheless, the study of tephra deposits is challenged by a lack of standardization that inhibits data integration across geographic regions and disciplines. We present comprehensive recommendations for tephra data gathering and reporting that were developed by the tephra science community to guide future investigators and to ensure that sufficient data are gathered for interoperability. Recommendations include standardized field and laboratory data collection, reporting and correlation guidance. These are organized as tabulated lists of key metadata with their definition and purpose. They are system independent and usable for template, tool, and database development. This standardized framework promotes consistent documentation and archiving, fosters interdisciplinary communication, and improves effectiveness of data sharing among diverse communities of researchers.

Scientific Data↗

USGS2015

The U.S. Geological Survey Geologic Collections Management System (GCMS)—A master catalog and collections management plan for U.S. Geological Survey geologic samples and sample collections

**Updated guidance is available in USGS Instructional Memorandum CSS 2019-01 .** Abstract The U.S. Geological Survey (USGS) is widely recognized in the earth science community as possessing extensive collections of earth materials collected by research personnel over the course of its history. In 2006, a Geologic Collections Inventory was conducted within the USGS Geology Discipline to determine the extent and nature of its sample collections, and in 2008, a working group was convened by the USGS National Geologic and Geophysical Data Preservation Program to examine ways in which these collections could be coordinated, cataloged, and made available to researchers both inside and outside the USGS. The charge to this working group was to evaluate the proposition of creating a Geologic Collections Management System (GCMS), a centralized database that would (1) identify all existing USGS geologic collections, regardless of size, (2) create a virtual link among the collections, and (3) provide a way for scientists and other researchers to obtain access to the samples and data in which they are interested. Additionally, the group was instructed to develop criteria for evaluating current collections and to establish an operating plan and set of standard practices for handling, identifying, and managing future sample collections. Policies and procedures promoted by the GCMS would be based on extant best practices established by the National Science Foundation and the Smithsonian Institution. The resulting report—USGS Circular 1410, “The U.S. Geological Survey Geologic Collections Management System (GCMS): A Master Catalog and Collections Management Plan for U.S. Geological Survey Geologic Samples and Sample Collections”—has been developed for sample repositories to be a guide to establishing common practices in the collection, retention, and disposal of geologic research materials throughout the USGS. While constructing this report, the GCMS’s potential customers and their needs were considered. Two critical definitions have been clarified: a repository is a facility for the long-term management of geologic collections, and a collection is a set of specimens that have been brought together on the basis of some common characteristic. Required sample metadata for newly collected samples, as well as for older collections, were also stipulated and are listed and explained in this report. Several basic policies are also recommended by the GCMS in order to standardize operations among the physical repositories where collections are currently housed. The GCMS Collection Management Plan provides a set of protocols and templates for the management of scientific collections, including access, storage, transfer, and disposal of physical geologic samples and data. This plan is flexible to allow each repository to adapt the practices best suited to its collections. The general consideration for implementation of the GCMS is that all active USGS geologic sample repositories will form the core of GCMS and that participating science centers will develop procedures based on proposed GCMS methodologies. The GCMS is a collective resource for the entire USGS community and the users who discover the geologic materials kept in these repositories and seek to access them.

Circular↗

USGS2024

Increasing the usability and accessibility of Voyager 2 images of Triton

Much of what we know about Neptune’s moon Triton was inferred from the analysis of images returned by the Voyager 2 mission, the only spacecraft to have visited that putative ocean world. Unfortunately, the highest-resolution images (scales < 2 km pixel −1 ) are difficult to use because they are only available in nonstandard formats, and the locations of the images on Triton’s surface are incorrect by up to 200 km. Although image mosaics of Triton are publicly available, these do not include the highest-resolution data. Here we describe our effort to improve the usability and accessibility of Voyager 2 images of Triton. We used the USGS’s ISIS software to process 41 Triton images, including geometric calibration, radiometric calibration, and reseau removal. We improved the image locations using a photogrammetric control network with 958 points and 3910 image measurements. Least-squares bundle adjustment of the network yielded rms uncertainty of 0.50, 0.52, and 0.51 pixels in latitude, longitude, and radius, respectively, and maximum residuals of −4.21 and +3.20 pixels, respectively. Image-to-image alignment is therefore vastly improved. We have released these processed images as cloud-optimized GeoTIFFs in orthographic projection at the original pixel scale of each image. Associated mosaics have also been created and released to provide geologic context for the individual images. These products provide the science community with analysis-ready data that enable new investigations of Triton, increase accessibility to this unique data set, and continue to enhance the scientific return from the Voyager 2 mission.

Planetary Science Journal↗

USGS2014

Engineering uses of physics-based ground motion simulations

This paper summarizes validation methodologies focused on enabling ground motion simulations to be used with confidence in engineering applications such as seismic hazard analysis and dynmaic analysis of structural and geotechnical systems. Numberical simullation of ground motion from large erthquakes, utilizing physics-based models of earthquake rupture and wave propagation, is an area of active research in the earth science community. Refinement and validatoin of these models require collaboration between earthquake scientists and engineering users, and testing/rating methodolgies for simulated ground motions to be used with confidence in engineering applications. This paper provides an introduction to this field and an overview of current research activities being coordinated by the Souther California Earthquake Center (SCEC). These activities are related both to advancing the science and computational infrastructure needed to produce ground motion simulations, as well as to engineering validation procedures. Current research areas and anticipated future achievements are also discussed.

Conference Paper↗

USGS2011

A working environment for digital planetary data processing and mapping using ISIS and GRASS GIS

Since the beginning of planetary exploration, mapping has been fundamental to summarize observations returned by scientific missions. Sensor-based mapping has been used to highlight specific features from the planetary surfaces by means of processing. Interpretative mapping makes use of instrumental observations to produce thematic maps that summarize observations of actual data into a specific theme. Geologic maps, for example, are thematic interpretative maps that focus on the representation of materials and processes and their relative timing. The advancements in technology of the last 30 years have allowed us to develop specialized systems where the mapping process can be made entirely in the digital domain. The spread of networked computers on a global scale allowed the rapid propagation of software and digital data such that every researcher can now access digital mapping facilities on his desktop. The efforts to maintain planetary missions data accessible to the scientific community have led to the creation of standardized digital archives that facilitate the access to different datasets by software capable of processing these data from the raw level to the map projected one. Geographic Information Systems (GIS) have been developed to optimize the storage, the analysis, and the retrieval of spatially referenced Earth based environmental geodata; since the last decade these computer programs have become popular among the planetary science community, and recent mission data start to be distributed in formats compatible with these systems. Among all the systems developed for the analysis of planetary and spatially referenced data, we have created a working environment combining two software suites that have similar characteristics in their modular design, their development history, their policy of distribution and their support system. The first, the Integrated Software for Imagers and Spectrometers (ISIS) developed by the United States Geological Survey, represents the state of the art for processing planetary remote sensing data, from the raw unprocessed state to the map projected product. The second, the Geographic Resources Analysis Support System (GRASS) is a Geographic Information System developed by an international team of developers, and one of the core projects promoted by the Open Source Geospatial Foundation (OSGeo). We have worked on enabling the combined use of these software systems throughout the set-up of a common user interface, the unification of the cartographic reference system nomenclature and the minimization of data conversion. Both software packages are distributed with free open source licenses, as well as the source code, scripts and configuration files hereafter presented. In this paper we describe our work done to merge these working environments into a common one, where the user benefits from functionalities of both systems without the need to switch or transfer data from one software suite to the other one. Thereafter we provide an example of its usage in the handling of planetary data and the crafting of a digital geologic map. ?? 2010 Elsevier Ltd. All rights reserved.

Conference Paper↗

USGS2021

A socio-ecological imperative for broadening participation in coastal and estuarine research and management

For most of the scientific disciplines associated with coastal and estuarine research, workforce representation does not match the demographics of communities we serve, especially for Black, Hispanic or Latino, and Indigenous peoples. This essay provides an overview of this inequity and identifies how a scientific society can catalyze representational, structural, and interactional diversity to achieve greater inclusion. Needed changes go beyond representational diversity and require an intentional commitment to build capacity through inclusivity and community engagement by supporting anti-racist policies and actions. We want to realize a sense of belonging on the part of scientists in society at large and enable research pursuits through a lens of social justice in service of coastal communities. Minimally, this framework offers an avenue for increased recruitment of individuals from more diverse racial and ethnic identities. More broadly, the mechanisms described here aim to create a culture in scientific societies in which social justice, driven by anti-racist actions, produces systemic change in how members of scientific societies approach, discuss, and address issues of inequity. We have written this essay for members of the coastal and marine science community who are interested in change. We aim to call in new voices, allies, and champions to this work.

Estuaries and Coasts↗

USGS2002

Operating the EOSDIS at the land processes DAAC managing expectations, requirements, and performance across agencies, missions, instruments, systems, and user communities

NASA developed the Earth Observing System (EOS) during the 1990'S. At the Land Processes Distributed Active Archive Center (LP DAAC), located at the USGS EROS Data Center, the EOS Data and Information System (EOSDIS) is required to support heritage missions as well as Landsat 7, Terra, and Aqua. The original system concept of the early 1990'S changed as each community had its say - first the managers, then engineers, scientists, developers, operators, and then finally the general public. The systems at the LP DAAC - particularly the largest single system, the EOSDIS Core System (ECS) - are changing as experience accumulates, technology changes, and each user group gains influence. The LP DAAC has adapted as contingencies were planned for, requirements and therefore plans were modified, and expectations changed faster than requirements could hope to be satisfied. Although not responsible for Quality Assurance of the science data, the LP DAAC works to ensure the data are accessible and useable by influencing systems, capabilities, and data formats where possible, and providing tools and user support as necessary. While supporting multiple missions and instruments, the LP DAAC also works with and learns from multiple management and oversight groups as they review mission requirements, system capabilities, and the overall operation of the LP DAAC. Stakeholders, including the Land Science community, are consulted regularly to ensure that the LP DAAC remains cognizant and responsive to the evolving needs of the user community. Today, the systems do not look or function as originally planned, but they do work, and they allow customers to search and order of an impressive amount of diverse data.

Conference Paper↗

USGS2021

Toward an integrative geological and geophysical view of Cascadia subduction zone earthquakes

The Cascadia subduction zone (CSZ) is an exceptional geologic environment for recording evidence of land level changes, tsunamis, and ground motion that reveals at least 19 great megathrust earthquakes over the past 10 kyr. Such earthquakes are among the most impactful natural hazards on Earth, transcend national boundaries, and can have global impact. Reducing the societal impacts of future events in the U.S. Pacific Northwest and coastal British Columbia, Canada requires improved scientific understanding of megathrust earthquake rupture, recurrence, and corresponding hazards. Despite substantial knowledge gained from decades of research, large uncertainties remain about the characteristics and frequencies of past CSZ earthquakes. In this review, we summarize geological, geophysical, and instrumental evidence relevant to understanding megathrust earthquakes along the CSZ and associated uncertainties. We discuss how the evidence constrains various models of great megathrust earthquake recurrence in Cascadia and identify potential paths forward for the earthquake science community.

British Columbia, Oregon, Washington↗

USGS2016

Optimizing available network resources to address questions in environmental biogeochemistry

An increasing number of network observatories have been established globally to collect long-term biogeochemical data at multiple spatial and temporal scales. Although many outstanding questions in biogeochemistry would benefit from network science, the ability of the earth- and environmental-sciences community to conduct synthesis studies within and across networks is limited and seldom done satisfactorily. We identify the ideal characteristics of networks, common problems with using data, and key improvements to strengthen intra- and internetwork compatibility. We suggest that targeted improvements to existing networks should include promoting standardization in data collection, developing incentives to promote rapid data release to the public, and increasing the ability of investigators to conduct their own studies across sites. Internetwork efforts should include identifying a standard measurement suite—we propose profiles of plant canopy and soil properties—and an online, searchable data portal that connects network, investigator-led, and citizen-science projects.

BioScience↗

USGS2022

GSPy: A new toolbox and data standard for Geophysical Datasets

The diversity of geophysical methods and datatypes, as well as the isolated nature of various specialties (e.g., electromagnetic, seismic, potential fields) leads to a profusion of separate data file formats and documentation conventions. This can hinder cooperation and reduce the impact of datasets researchers have invested in heavily to collect and prepare. An open, portable, and well-supported community data standard could greatly improve the interoperability, transferability, and long-term archival of geophysical data. Airborne geophysical methods particularly need an open and accessible data standard, and they exemplify the complexity that is common in geophysical datasets where critical auxiliary information on the survey and system parameters are required to fully utilize and understand the data. Here, we propose a new Geophysical Standard, termed the GS convention, that leverages the well-established and widely used NetCDF file format and builds on the Climate and Forecasts (CF) metadata convention. We also present an accompanying open-source Python package, GSPy, to provide methods and workflows for building the GS-standardized NetCDF files, importing and exporting between common data formats, preparing input files for geophysical inversion software, and visualizing data and inverted models. By using the NetCDF format, handled through the Xarray Python package, and following the CF conventions, we standardize how metadata is recorded and directly stored with the data, from general survey and system information down to specific variable attributes. Utilizing the hierarchical nature of NetCDF, GS-formatted files are organized with a root Survey group that contains global metadata about the geophysical survey. Data are then organized into subgroups beneath Survey and are categorized as Tabular or Raster depending on the geometry and point of origin for the data. Lastly, the standard ensures consistency in constructing and tracking coordinate reference systems, which is vital for accurate portability and analysis. Development and adoption of a NetCDF-based data standard for geophysical surveys can greatly improve how these complex datasets are shared and utilized, making the data more accessible to a broader science community. The architecture of GSPy can be easily transferred to additional geophysical datatypes and methods in future releases.

Frontiers in Earth Science - Environmental Informa↗

USGS2023

Ten best practices for effective phenological research

The number and diversity of phenological studies has increased rapidly in recent years. Innovative experiments, field studies, citizen science projects, and analyses of newly available historical data are contributing insights that advance our understanding of ecological and evolutionary responses to the environment, particularly climate change. However, many phenological data sets have peculiarities that are not immediately obvious and can lead to mistakes in analyses and interpretation of results. This paper aims to help researchers, especially those new to the field of phenology, understand challenges and practices that are crucial for effective studies. For example, researchers may fail to account for sampling biases in phenological data, struggle to choose or design a volunteer data collection strategy that adequately fits their project’s needs, or combine data sets in inappropriate ways. We describe ten best practices for designing studies of plant and animal phenology, evaluating data quality, and analyzing data. Practices include accounting for common biases in data, using effective citizen or community science methods, and employing appropriate data when investigating phenological mismatches. We present these best practices to help researchers entering the field take full advantage of the wealth of available data and approaches to advance our understanding of phenology and its implications for ecology.

International Journal of Biometeorology↗