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USGS2003

The challenge of archiving and preserving remotely sensed data

Few would question the need to archive the scientific and technical (S&T) data generated by researchers. At a minimum, the data are needed for change analysis. Likewise, most people would value efforts to ensure the preservation of the archived S&T data. Future generations will use analysis techniques not even considered today. Until recently, archiving and preserving these data were usually accomplished within existing infrastructures and budgets. As the volume of archived data increases, however, organizations charged with archiving S&T data will be increasingly challenged (U.S. General Accounting Office, 2002). The U.S. Geological Survey has had experience in this area and has developed strategies to deal with the mountain of land remote sensing data currently being managed and the tidal wave of expected new data. The Agency has dealt with archiving issues, such as selection criteria, purging, advisory panels, and data access, and has met with preservation challenges involving photographic and digital media. That experience has allowed the USGS to develop management approaches, which this paper outlines.

Data Science Journal↗

USGS2011

Globally Gridded Satellite observations for climate studies

Geostationary satellites have provided routine, high temporal resolution Earth observations since the 1970s. Despite the long period of record, use of these data in climate studies has been limited for numerous reasons, among them that no central archive of geostationary data for all international satellites exists, full temporal and spatial resolution data are voluminous, and diverse calibration and navigation formats encumber the uniform processing needed for multisatellite climate studies. The International Satellite Cloud Climatology Project (ISCCP) set the stage for overcoming these issues by archiving a subset of the full-resolution geostationary data at ~10-km resolution at 3-hourly intervals since 1983. Recent efforts at NOAA's National Climatic Data Center to provide convenient access to these data include remapping the data to a standard map projection, recalibrating the data to optimize temporal homogeneity, extending the record of observations back to 1980, and reformatting the data for broad public distribution. The Gridded Satellite (GridSat) dataset includes observations from the visible, infrared window, and infrared water vapor channels. Data are stored in Network Common Data Format (netCDF) using standards that permit a wide variety of tools and libraries to process the data quickly and easily. A novel data layering approach, together with appropriate satellite and file metadata, allows users to access GridSat data at varying levels of complexity based on their needs. The result is a climate data record already in use by the meteorological community. Examples include reanalysis of tropical cyclones, studies of global precipitation, and detection and tracking of the intertropical convergence zone.

Bulletin of the American Meteorological Society↗

USGS2010

Appraising U.S. Geological Survey science records

The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center has legislative charters to preserve and make accessible land remote sensing records important to the United States. This essay explains the appraisal process developed by EROS to ensure the science records it holds and those offered to it align with those charters. The justifications behind the questions employed to weed and to complement the EROS archive are explained along with the literature reviewed supporting their inclusion. Appraisal results are listed by individual collection and include the recommendations accepted by EROS management.

Archival Issues↗

USGS2016

Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US

Using the NASA Earth Exchange platform, the North American Forest Dynamics (NAFD) project mapped forest history wall-to-wall, annually for the contiguous US (1986–2010) using the Vegetation Change Tracker algorithm. As with any effort to identify real changes in remotely sensed time-series, data gaps, shifts in seasonality, misregistration, inconsistent radiometry and cloud contamination can be sources of error. We discuss the NAFD image selection and processing stream (NISPS) that was designed to minimize these sources of error. The NISPS image quality assessments highlighted issues with the Landsat archive and metadata including inadequate georegistration, unreliability of the pre-2009 L5 cloud cover assessments algorithm, missing growing-season imagery and paucity of clear views. Assessment maps of Landsat 5–7 image quantities and qualities are presented that offer novel perspectives on the growing-season archive considered for this study. Over 150,000+ Landsat images were considered for the NAFD project. Optimally, one high quality cloud-free image in each year or a total of 12,152 images would be used. However, to accommodate data gaps and cloud/shadow contamination 23,338 images were needed. In 220 specific path-row image years no acceptable images were found resulting in data gaps in the annual national map products.

International Journal of Digital Earth↗

USGS2010

Real-time seismic monitoring of structures: Data handling and case studies

Within the last decade, advances in the acquisition, processing and transmission of data from real-time seismic monitoring systems has contributed to the growth in the number structures instrumented with such systems. An equally important factor for such growth can be attributed to the demands by stakeholders to find rapid answers to important questions related to the functionality (or “state of health”) of structures during and immediately following a seismic event. Hence, rapid and accurate assessment of the damage condition or performance of a building or a lifeline structure is of paramount importance to stakeholders, including owners, leasers, permanent and/or temporary occupants, users of infrastructures, city officials and rescue teams that are concerned with safety of those in the building, and those that may be affected in nearby buildings and infrastructures. In earlier papers, we described how observed data from sensors deployed in structures can be configured to establish seismic health monitoring of structures. In these configurations, drift ratios are the main parametric indicator of damage condition of a building. The process described for buildings can be applied directly for bridges as well. For bridges, the term, “drift ratio” is not generally used; however, relative displacements of critical elements of a bridge can be construed as such. While real-time data from structural arrays indicate that these methods are reliable and provide requisite information for owners and other parties to make informed decisions and to choose among pre-defined actions following significant events, there are several issues related to data ownership, transmission and archiving. This paper examines the real-time seismic monitoring systems deployed mainly in the United States, with particular attention to data issues – handling, dissemination, storage, and archiving. In most cases, due to the numerous channels involved, the deployments in each one of the real-time structures can be considered to be an individual array. Two detailed cases are described that demonstrate the variability in data ownership and dissemination.

Book chapter↗

USGS2007

Workshop: Western hemisphere network of bird banding programs

Purpose: To promote collaboration among banding programs in the Americas. Introduction: Bird banding and marking provide indispensable tools for ornithological research, management, and conservation of migratory birds on migratory routes, breeding and non-breeding grounds. Many countries and organizations in Latin America and the Caribbean are in the process of developing or have expressed interest in developing national banding schemes and databases to support their research and management programs. Coordination of developing and existing banding programs is essential for effective data management, reporting, archiving and security, and most importantly, for gaining a fuller understanding of migratory bird conservation issues and how the banding data can help. Currently, there is a well established bird-banding program in the U.S.A. and Canada, and programs in other countries are being developed as well. Ornithologists in many Latin American countries and the Caribbean are interested in using banding and marking in their research programs. Many in the ornithological community are interested in establishing banding schemes and some countries have recently initiated independent banding programs. With the number of long term collaborative and international initiatives increasing, the time is ripe to discuss and explore opportunities for international collaboration, coordination, and administration of bird banding programs in the Western Hemisphere. We propose the second ?Western Hemisphere Network of Bird Banding Programs? workshop, in association with the SCSCB, to be an essential step in the progress to strengthen international partnerships and support migratory bird conservation in the Americas and beyond. This will be the second multi-national meeting to promote collaboration among banding programs in the Americas (the first meeting was held in October 8-9, 2006 in La Mancha, Veracruz, Mexico). The Second ?Western Hemisphere Network of Bird Banding Programs? workshop will continue addressing issues surrounding the coordination of an Americas? approach to bird banding and will review in detail the advances made on the first workshop such as, coordination of bands and markers, coordination in recovery reporting, permit issues, data management and data sharing and archiving, data security, training, etc. Workshop Goals: Build on accomplishments of the network?s first workshop (Oct 8-9, 2006). Identify and explore new opportunities for data sharing, data archiving, data access, training, etc. Initiate strategies to support international collaboration and coordination amongst bird banding programs in the Western Hemisphere. Workshop structure: One day workshop of guided discussions. Participants: Representatives of government agencies, program managers and NGOs.

Book chapter↗

USGS2024

Best practices for genetic and genomic data archiving

Genetic and genomic data are collected for a vast array of scientific and applied purposes. Despite mandates for public archiving, data are typically used only by the generating authors. The reuse of genetic and genomic datasets remains uncommon because it is difficult, if not impossible, due to non-standard archiving practices and lack of contextual metadata. But as the new field of macrogenetics is demonstrating, if genetic data and their metadata were more accessible and FAIR (findable, accessible, interoperable and reusable) compliant, they could be reused for many additional purposes. We discuss the main challenges with existing genetic and genomic data archives, and suggest best practices for archiving genetic and genomic data. Recognizing that this is a longstanding issue due to little formal data management training within the fields of ecology and evolution, we highlight steps that research institutions and publishers could take to improve data archiving.

Nature, Ecology and Evolution↗

USGS2018

Spatial sampling bias in the Neotoma paleoecological archives affects species paleo-distribution models

The ability to infer paleo-distributions with limited knowledge of absence makes species distribution modeling (SDM) a useful tool for exploring paleobiogeographic questions. Spatial sampling bias is a known issue when modeling extant species. Here we quantify the spatial sampling bias in a North American packrat midden archive and explore its impact on estimating paleo-distributions. We test whether (1) spatial sampling bias inherent in this macrofossil record can influence estimates of paleo-distributions, (2) this bias can alter the ability to measure shifts in distributions and climatic niche breadth from the Northgrippian subdivision of the Holocene (8.3 ka – 4.2 ka) to present day (1950–2000 yr), and (3) bias correction methods can improve estimates of paleo-distributions and analyses of range shifts and niche breadth. We estimate spatial sampling bias for the mid-Holocene period with a three-stage statistical model, each representing a hypothesized source of bias: fossil site availability, preservation and accessibility. This approach enables the use of SDM to evaluate three separate paleo-distributions calibrated on the packrat midden archive: those without bias correction (σ-naïve), those created with a standard method (σ-standard), and those created with a novel alternative (σ-modeled) incorporating the three-stage model of bias. We find that paleo-distributions modeled for the mid-Holocene without bias correction (σ-naïve) provided poor estimates of hindcast paleo-distributions, and that the σ-modeled correction method improved paleo-distributions for our six species with, on average, 50% higher overlap to hindcast distributions than σ-naïve paleo-distributions (σ-standard results fell between σ-naïve and σ-modeled).

Journal of Quaternary Science Reviews↗

USGS2020

Final Alabama Barrier Island restoration assessment report, appendix A: Data management plan

The Alabama Barrier Island Restoration Assessment project focused exclusively on Dauphin Island, a significant barrier island along the northern Gulf of Mexico. This restoration feasibility study effort required data collection and analysis of many data types (e.g., hydro, sediment, currents, etc.) through the project’s life cycle to assess restoration measures and their effects on the sustainability of Dauphin Island. As such, the project requires a data management plan (DMP) to address issues such as data delivery format, organizational strategies, internal data sharing, archival processes, and product dissemination.

Alabama↗

USGS2015

Landsat Science Team meeting: Winter 2015

The summer meeting of the joint U.S. Geological Survey (USGS)–NASA Landsat Science Team (LST) was held at the USGS’s Earth Resources Observation and Science (EROS) Center July 7-9, 2015, in Sioux Falls, SD. The LST co-chairs, Tom Loveland [EROS—Senior Scientist] and Jim Irons [NASA’s Goddard Space Flight Center (GSFC)—Landsat 8 Project Scientist], opened the three-day meeting on an upbeat note following the recent successful launch of the European Space Agency’s Sentinel-2 mission on June 23, 2015 (see image on page 14), and the news that work on Landsat 9 has begun, with a projected launch date of 2023. With over 60 participants in attendance, this was the largest LST meeting ever held. Meeting topics on the first day included Sustainable Land Imaging and Landsat 9 development, Landsat 7 and 8 operations and data archiving, the Landsat 8 Thermal Infrared Sensor (TIRS) stray-light issue, and the successful Sentinel-2 launch. In addition, on days two and three the LST members presented updates on their Landsat science and applications research. All presentations are available at landsat.usgs.gov/science_LST_Team_ Meetings.php.

The Earth Observer↗

USGS2008

Borehole Geophysical Logging Program: Incorporating New and Existing Techniques in Hydrologic Studies

The borehole geophysical logging program at the U.S. Geological Survey (USGS)-Florida Integrated Science Center (FISC) provides subsurface information needed to resolve geologic, hydrologic, and environmental issues in Florida. The program includes the acquisition, processing, display, interpretation, and archiving of borehole geophysical logs. The borehole geophysical logging program is a critical component of many FISC investigations, including hydrogeologic framework studies, aquifer flow-zone characterization, and freshwater-saltwater interface delineation.

Fact Sheet↗

USGS1991

Integration of remote sensing and GIS: Data and data access

CT: Theintegration of remote sensing tools and technology with the spatial analysis orientation of geographic information systems is a complex task. In this paper, we focus on the issues of making data available and useful to the user. In part, this involves a set of problems which reflect on the physical and logical structures used to encode the data. At the same time, however, the mechanisms and protocols which provide information about the data, and which maintain the data through time, have become increasingly important. We discuss these latter issues from the viewpoint of the functions which must be provided by archives of spatial data.

Photogrammetric Engineering and Remote Sensing↗

USGS2004

Cyanide hazards to plants and animals from gold mining and related water issues

Highly toxic sodium cyanide (NaCN) is used by the international mining community to extract gold and other precious metals through milling of high-grade ores and heap leaching of low-grade ores (Korte et al. 2000). The process to concentrate gold using cyanide was developed in Scotland in 1887 and was used almost immediately in the Witwatersrand gold fields of the Republic of South Africa. Heap leaching with cyanide was proposed by the U.S. Bureau of Mines in 1969 as a means of extracting gold from low-grade ores. The gold industry adopted the technique in the 1970s, soon making heap leaching the dominant technology in gold extraction (Da Rosa and Lyon 1997). The heap leach and milling processes, which involve dewatering of gold-bearing ores, spraying of dilute cyanide solutions on extremely large heaps of ores containing low concentrations of gold, or the milling of ores with the use of cyanide and subsequent recovery of the gold-cyanide complex, have created a number of serious environmental problems affecting wildlife and water management. In this account, we review the history of cyanide use in gold mining with emphasis on heap leach gold mining, cyanide hazards to plants and animals, water management issues associated with gold mining, and proposed mitigation and research needs.

Archives of Environmental Contamination and Toxico↗

USGS2026

Creating 3D point clouds, digital elevation models, and orthomosaics from historical aerial imagery through structure from motion aided photogrammetry

Detailed and accurate historical data are crucial to characterizing landscape change, whether it is caused by natural phenomena or of anthropogenic origin. Aerial imagery has been periodically collected by government and nongovernment agencies, for a broad range of purposes, since the early 20th century. The acquisition of aerial images involves using standardized equipment with large-format, carefully calibrated cameras and lens assemblies. Historical archives of aerial images preserve a record of the landscape and are invaluable sources of information that predate satellite and lidar. Structure from motion (SfM) aided photogrammetry provides an efficient means for creating digital three-dimensional data from the vast archives of historical aerial imagery. This report presents techniques, methods, best practices, and a standard workflow for creating point clouds, digital elevation models, and orthomosaic digital scans of overlapping (stereographic) vertical aerial photographs using photogrammetry software. A list of critical issues relevant to SfM-aided photogrammetry of historical aerial imagery is provided, along with potential contingencies and solutions. The workflow was tested in many geographic study areas and with historical imagery datasets of different scales and sources. Three case studies are included. By integrating known SfM methods, these procedures enable the consistent and optimal extraction of historical quantitative data from archives like the U.S. Geological Survey (USGS) Aerial Photo Single Frame archive in the USGS EarthExplorer data portal.

Techniques and Methods↗

USGS2016

Water isotope systematics: Improving our palaeoclimate interpretations

The stable isotopes of oxygen and hydrogen, measured in a variety of archives, are widely used proxies in Quaternary Science. Understanding the processes that control δ18O change have long been a focus of research (e.g. Shackleton and Opdyke, 1973; Talbot, 1990 ; Leng, 2006). Both the dynamics of water isotope cycling and the appropriate interpretation of geological water-isotope proxy time series remain subjects of active research and debate. It is clear that achieving a complete understanding of the isotope systematics for any given archive type, and ideally each individual archive, is vital if these palaeo-data are to be used to their full potential, including comparison with climate model experiments of the past. Combining information from modern monitoring and process studies, climate models, and proxy data is crucial for improving our statistical constraints on reconstructions of past climate variability. As climate models increasingly incorporate stable water isotope physics, this common language should aid quantitative comparisons between proxy data and climate model output. Water-isotope palaeoclimate data provide crucial metrics for validating GCMs, whereas GCMs provide a tool for exploring the climate variability dominating signals in the proxy data. Several of the studies in this set of papers highlight how collaborations between palaeoclimate experimentalists and modelers may serve to expand the usefulness of palaeoclimate data for climate prediction in future work. This collection of papers follows the session on Water Isotope Systematics held at the 2013 AGU Fall Meeting in San Francisco. Papers in that session, the breadth of which are represented here, discussed such issues as; understanding sub-GNIP scale (Global Network for Isotopes in Precipitation, (IAEA/WMO, 2006)) variability in isotopes in precipitation from different regions, detailed examination of the transfer of isotope signals from precipitation to geological archives, and the implications of advances in understanding in these areas for the interpretation of palaeo records and proxy data – climate model comparison. Here, we briefly review these areas of research, and discuss challenges for the water isotope community in improving our ability to partition climate vs. auxiliary signals in palaeoclimate data.

Quaternary Science Reviews↗

USGS2012

Reducing Vulnerability of Ports and Harbors to Earthquake and Tsunami Hazards

Recent scientific research suggests the Pacific Northwest could experience catastrophic earthquakes in the near future, both from distant and local sources, posing a significant threat to coastal communities. Damage could result from numerous earthquake-related hazards, such as severe ground shaking, soil liquefaction, landslides, land subsidence/uplift, and tsunami inundation. Because of their geographic location, ports and harbors are especially vulnerable to these hazards. Ports and harbors, however, are important components of many coastal communities, supporting numerous activities critical to the local and regional economy and possibly serving as vital post-event, response-recovery transportation links. A collaborative, multi-year initiative is underway to increase the resiliency of Pacific Northwest ports and harbors to earthquake and tsunami hazards, involving Oregon Sea Grant (OSG), Washington Sea Grant (WSG), the National Oceanic and Atmospheric Administration Coastal Services Center (CSC), and the U.S. Geological Survey Center for Science Policy (CSP). Specific products of this research, planning, and outreach initiative include a regional stakeholder issues and needs assessment, a community-based mitigation planning process, a Geographic Information System (GIS) — based vulnerability assessment methodology, an educational web-site and a regional data archive. This paper summarizes these efforts, including results of two pilot port-harbor community projects, one in Yaquina Bay, Oregon and the other in Sinclair Inlet, Washington. Finally, plans are outlined for outreach to other port and harbor communities in the Pacific Northwest and beyond, using "getting started" workshops and a web-based tutorial.

Oregon, Washington↗

USGS1994

Topographic data requirements for EOS global change research

This document is a result of Earth Observing System Data and Information System (EOSDIS) Version 0 activities of the Land Processes Distributed Active Archive Center at the U.S. Geological Survey's EROS Data Center. A relatively small part of the Version 0 funding provided by NASA is used to address topographic data issues related to EOS. These issues include identifying and improving access to existing sources of topographic data, data generation, facilitating the use of topographic data in global change research by demonstrating derivative products, and inventorying the specific topographic data requirements of EOS investigators. There is a clear need for global topographic data in EOSDIS. Only 10 percent of the global land surface is covered by high-resolution data that are available to the global change science community. Alternative sources for new data exist or have been proposed; however, none of them alone can fulfill the data requirements by the launch of the first EOS platform in 4 years. There is no operational provider of all the source data that are required. Even if appropriate global source data existed, a concerted production effort would be necessary to ensure the existence of the requisite topographic data before EOS launch. Additionally, no funding from NASA or any other agency has been appropriated for a new mapping mission or for other means of data acquisition. This effort to document requirements is an initial step toward understanding the severity of the data shortage. It is well beyond the scope of Version 0 funding and capabilities to provide the required data in the proper timeframe. The shortage of data and the lack of a plan for providing the necessary topographic data through EOSDIS in time for launch are issues that must be addressed by the EOS program.

Open-File Report↗

USGS2021

Classifying crop types using two generations of hyperspectral sensors (Hyperion and DESIS) with machine learning on the cloud

Advances in spaceborne hyperspectral (HS) remote sensing, cloud-computing, and machine learning can help measure, model, map and monitor agricultural crops to address global food and water security issues, such as by providing accurate estimates of crop area and yield to model agricultural productivity. Leveraging these advances, we used the Earth Observing-1 (EO-1) Hyperion historical archive and the new generation DLR Earth Sensing Imaging Spectrometer (DESIS) data to evaluate the performance of hyperspectral narrowbands in classifying major agricultural crops of the U.S. with machine learning (ML) on Google Earth Engine (GEE). EO-1 Hyperion images from the 2010–2013 growing seasons and DESIS images from the 2019 growing season were used to classify three world crops (corn, soybean, and winter wheat) along with other crops and non-crops near Ponca City, Oklahoma, USA. The supervised classification algorithms: Random Forest (RF), Support Vector Machine (SVM), and Naive Bayes (NB), and the unsupervised clustering algorithm WekaXMeans (WXM) were run using selected optimal Hyperion and DESIS HS narrowbands (HNBs). RF and SVM returned the highest overall producer’s, and user’s accuracies, with the performances of NB and WXM being substantially lower. The best accuracies were achieved with two or three images throughout the growing season, especially a combination of an earlier month (June or July) and a later month (August or September). The narrow 2.55 nm bandwidth of DESIS provided numerous spectral features along the 400–1000 nm spectral range relative to smoother Hyperion spectral signatures with 10 nm bandwidth in the 400–2500 nm spectral range. Out of 235 DESIS HNBs, 29 were deemed optimal for agricultural study. Advances in ML and cloud-computing can greatly facilitate HS data analysis, especially as more HS datasets, tools, and algorithms become available on the Cloud.

Remote Sensing↗