Publications

Coastal imaging systems have been developed to measure wave runup and total water level (TWL) at the shoreline, which is a key metric for assessing coastal flooding and erosion. However, extracting quantitative measurements from coastal images has typically been done through the laborious task of hand-digitization of wave runup timestacks. Timestacks are images created by sampling a cross-shore ar

The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 12 projects funded in fiscal year 2020, outlining their goals, activities, and accomplishments.

Urban land cover types influence the urban microclimates. However, recent work indicates the magnitude of land cover's microclimate influence is affected by aridity. Moreover, this variation in cooling and warming potentials of urban land cover types can substantially alter the exposure of urban areas to extreme heat. Our goal is to understand both the relative influences of urban land cover on lo

The purpose of this study is to increase understanding of how the U.S. Geological Survey (USGS) is developing decision-support tools (DSTs) by documenting successes and barriers across all levels of USGS scientific tool creation and outreach. These findings will help streamline future tool design and development processes. We provide a synthesis of lessons learned and best practices across a spect

Knowing subsurface drainage (tile-drain) extent is integral to understanding how landscapes respond to precipitation events and subsequent days of drying, as well as how soil characteristics and land management influence stream response. Consequently, a time series of tile-drain extent would inform one aspect of land management that complicates our ability to explain streamflow and water-quality a

South Manitou Island, part of Sleeping Bear Dunes National Lakeshore in northern Lake Michigan, is a post-glacial lacustrine landscape with substantial geomorphic changes including landslides, shoreline and bluff retreat, and sand dune movement. These changes involve interrelated processes, and are influenced to different extents by lake level, climate change, and land use patterns, among other fa

The U.S. Geological Survey Community for Data Integration annually supports small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 14 projects supported in fiscal year 2019 and outlines their goals, activities, and accomplishments. Proposals in 2019 were encouraged to addre

The world’s coastlines are spatially highly variable, coupled-human-natural systems that comprise a nested hierarchy of component landforms, ecosystems, and human interventions, each interacting over a range of space and time scales. Understanding and predicting coastline dynamics necessitates frequent observation from imaging sensors on remote sensing platforms. Machine Learning models that carry

To advance national efforts for the detection and biosurveillance of aquatic invasive species (AIS), we employed a community consensus process to enable the incorporation of environmental DNA (eDNA) detection data into the U.S. Geological Survey’s (USGS) Nonindigenous Aquatic Species (NAS) database (https://nas.er.usgs.gov/eDNA/). Our goal was to identify minimum standards and best practices for t

The Community for Data Integration is a community of practice whose purpose is to advance the data integration capabilities of the U.S. Geological Survey. In fiscal year 2020, the Community for Data Integration held 11 monthly forums, facilitated 13 collaboration areas, and supported 13 projects. The activities supported the broad U.S. Geological Survey priority of producing building blocks for do

In 2016, an interdisciplinary, international group of 53 scientists introduced a framework named “the FAIR Principles” for addressing 21st century scientific data challenges. The FAIR Principles are increasingly used as a guide for producing digital scientific products that are findable, accessible, interoperable, and reusable (FAIR), especially to enable use of such products in automated systems.

Natural resource management and supporting research teams need computational fluency in the data and model-rich 21st century. Computational fluency describes the ability of practitioners and scientists to conduct research and represent natural systems within the computer's environment. Advancement in information synthesis for natural resource management requires more sophisticated computational ap