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The Best Management Practices Statistical Estimator (BMPSE) was developed by the U.S. Geological Survey (USGS), in cooperation with the Federal Highway Administration (FHWA) Office of Project Delivery and Environmental Review to provide planning-level information about the performance of structural best management practices for decision makers, planners, and highway engineers to assess and mitigate possible adverse effects of highway and urban runoff on the Nation's receiving waters (Granato 2013, 2014; Granato and others, 2021a,b). The BMPSE was used to calculate statistics and create input files for fitting the trapezoidal distribution to data from studies documenting the performance of individual structural stormwater...
Categories: Software;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Best Management Practice (BMP),
Ecology,
Environmental Health,
Event Mean Concentration,
Federal Highway Administration,
This R code (Nest_Cards_QC.R) is used to process the raw legacy nest card data (1985 - 2019) and produce the quality controlled legacy nest card data for analysis and sharing. This code does not quality control the double searched plots (R2 plots in 1995-99), which is done in the file ‘PrepData.R’. Basic operations include transforming missing value to a common code, transforming other variable to match the data dictionary for nest cards, and resolving non-unique observer initials. The code requires the raw data (“1985-2019_Nest Cards_10-24-19_cleaned.xlsx”) and the table of observer names (“Observer Names_1985-2019_10-24-19.xlsx”). The code writes the QC nest card file “Nest_Cards_1985_2019_QC.csv”. Mostly obseration...
Categories: Data,
Software;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
Inventories of landslides and liquefaction triggered by major earthquakes are key research tools that can be used to develop and test hazard models. To eliminate redundant effort, we created a centralized and interactive repository of ground failure inventories that currently hosts 32 inventories generated by USGS and non-USGS authors and designed a pipeline for adding more as they become available. The repository consists of (1) a ScienceBase community page where the data are available for download and (2) an accompanying web application that allows users to browse and visualize the available datasets. We anticipate that easier access to these key datasets will accelerate progress in earthquake-triggered ground...
Categories: Project;
Tags: 2017,
All Funded Projects,
Completed,
Computational Tools and Services,
Software,
Deep learning is a computer analysis technique inspired by the human brain’s ability to learn. It involves several layers of artificial neural networks to learn and subsequently recognize patterns in data, forming the basis of many state-of-the-art applications from self-driving cars to drug discovery and cancer detection. Deep neural networks are capable of learning many levels of abstraction, and thus outperform many other types of automated classification algorithms. This project developed software tools, resources, and two training workshops that will allow USGS scientists to apply deep learning to remotely sensed imagery and to better understand natural hazards and habitats across the Nation. The tools and...
Categories: Project;
Tags: 2018,
All Funded Projects,
Completed,
Computational Tools and Services,
Data and Information Assets,
This is a macro-embedded EXCEL program that calculates and displays indicators representing valued characteristics or processes in Black Canyon of the Gunnison National Park based on input of daily flows of the Gunnison River. The program is designed to easily accept input from downloaded stream gage records or output from the RIVERWARE reservoir operations model being used for the upstream Aspinall Unit. The decision support system is structured to compare as many as eight alternative flow regimes, where each alternative is represented by a daily sequence of at least 20 calendar years of streamflow. Indicators include selected flow statistics, riparian plant community distribution, clearing of box elder by inundation...
Insect pests cost billions of dollars per year globally, negatively impacting food crops and infrastructure and contributing to the spread of disease. Timely information regarding developmental stages of pests can facilitate early detection and control, increasing efficiency and effectiveness. To address this need, the USA National Phenology Network (USA-NPN) created a suite of “Pheno Forecast” map products relevant to science and management. Pheno Forecasts indicate, for a specified day, the status of the insect’s target life cycle stage in real time across the contiguous United States. These risk maps enhance decision-making and short-term planning by both natural resource managers and members of the public. ...
Categories: Project;
Tags: 2018,
All Funded Projects,
Completed,
Computational Tools and Services,
Data and Information Assets,
2012 Updates (from the FY12 Annual Review) The NWIS Web Services Snapshot represents the next generation of data retrieval and management. The newest Snapshot tool allows instant access to NWIS data from four different web services through ArcGIS, software available to all USGS scientists in all mission areas. Increased data retrieval efficiency reduces the steps required to retrieve and compile water data from multiple sites from what can be more than 30 steps to just a few clicks. As an end-user education tool, it promotes use of NWIS data from both web services and the NWIS database, which increases the production of scientific research and analysis that uses NWIS data. The Snapshot database design enables efficient...
R code that takes in the nest capture history data (chdata.csv), reformats it for model fitting in Program Mark via the R package RMark. A series of models of increasing complexity are fit and compared using AIC. Output is written to text files for each model but is generally not used or saved. Code can be run to generate model results and R workspaces/ object to inspect parameter estimates. The primary purpose of this code is to explore model structures for predicting detection and as an attempt to reproduce historically used parameter estimates in past nest plot reports (e.g., Fischer et al. 2017 and earlier). Results from ‘Model 7’ are most similar to detection estimates used in the past.
Categories: Data,
Software;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
BIOLOGICAL CLASSIFICATION,
BIOLOGICAL CLASSIFICATION,
This R code (YKDsalinity_QC.R) is used to process the raw legacy salinity data for fixed and random plots (2006 - 2019) and produce the quality controlled legacy salinity data for analysis and sharing (YKDsalinity_QC.csv). Basic operations include transforming missing value to a common code, transforming other variables to match the data dictionary, and cleaning spatial location issues. Of special note is that this QC process discover significant error in location data due to a variety of reasons so the random plot centers are added to the data table and should be used for analysis. The code requires the raw data (“Official_YKD.SALINITY.DATA.MASTER.2020.csv”), a definition of the nest plot study area (“NestPlotStudyAreaBoundary.geojson”),...
Categories: Data,
Software;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: BIOSPHERE,
BIOSPHERE,
BIOSPHERE,
DATA INTEROPERABILITY,
DATA INTEROPERABILITY,
Advances in information technology now provide large volume, high-frequency data collection which may improve real-time biosurveillance and forecasting. But, big data streams present challenges for data management and timely analysis. As a first step in creating a data science pipeline for translating large datasets into meaningful interpretations, we created a cloud-hosted PostgreSQL database that collates climate data served from PRISM (https://climatedataguide.ucar.edu/climate-data) and water-quality data from the National Water Quality Portal (https://www.waterqualitydata.us/) and NWIS (https://waterdata.usgs.gov/nwis; fig 1). Using Python-based code, these data streams are queried and updated every 24 hours,...
Categories: Project;
Tags: 2019,
All Funded Projects,
Computational Tools and Services,
Data and Information Assets,
Software
Geotagged photographs have become a useful medium for recording, analyzing, and communicating Earth science phenomena. Despite their utility, many field photographs are not published or preserved in a spatial or accessible format—oftentimes because of confusion about photograph metadata, a lack of stability, or user customization in free photo sharing platforms. After receiving a request to release about 1,210 geotagged geological field photographs of the Grand Canyon region, we set out to publish and preserve the collection in the most robust (and expedient) manner possible (fig. 6). We leveraged and reworked existing metadata, JavaScript, and Python tools and developed a toolkit and proposed workflow to display...
Categories: Project;
Tags: 2017,
All Funded Projects,
Best Practices,
Completed,
Computational Tools and Services,
Artificial Intelligence (AI) is revolutionizing ecology and conservation by enabling species recognition from photos and videos. Our project evaluates the capacity to expand AI for individual fish recognition for population assessment. The success of this effort would facilitate fisheries analysis at an unprecedented scale by engaging anglers and citizen scientists in imagery collection.This project is one of the first attempts to apply AI towards fish population assessment with citizen science. Principal Investigator : Nathaniel P Hitt Co-Investigator : Natalya I Rapstine, Mona (Contractor) Arami, Jeff T Falgout, Benjamin Letcher, Nicholas Polys Cooperator/Partner : Sophia Liu, Fraser Hayes, Ky Wildermuth, Bryan...
Categories: Project;
Tags: 2020,
All Funded Projects,
Completed,
Computational Tools and Services,
Featured Projects,
Landscape Conservation Cooperatives (LCCs) have a critical need for information management processes that facilitate science product (i.e., data, analysis and decision tools, documents) sharing; data storage, security, and dissemination; and project tracking, communication and collaboration tools (Arctic LCC 2010, North Atlantic LCC 2011, Southern Rockies LCC 2011, California LCC 2011). LCCs and their partners are already developing and using a wide variety of data management systems to address LCC and project needs, but the LCC Network and all partners need better coordination across these efforts to develop and share common standards and services, improving the intellectual exchange needed to achieve the LCC mission....
The SeaDuckDetectoR is software designed to identify sea ducks and other avian species in aerial photographs. The program is run through R and RStudio. The product includes a .zip file “SeaDuckDetectoR.0.1.0.zip” with the files for installation, and a manual “SeaDuckDetectoR_Manual.docx” explaining how to run the program.
Categories: Data,
Software;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ANIMALS/VERTEBRATES,
BIOLOGICAL CLASSIFICATION,
BIRDS,
EARTH SCIENCE,
Science Keywords,
PHREEQCI is a widely-used geochemical computer program that can be used to calculate chemical speciation and specific conductance of a natural water sample from its chemical composition (Charlton and Parkhurst, 2002; Parkhurst and Appelo, 1999). The specific conductance of a natural water calculated with PHREEQCI (Appelo, 2010) is reliable for pH greater than 4 and temperatures less than 35 °C (McCleskey and others, 2012b). An alternative method for calculating the specific conductance of natural waters is accurate over a large range of ionic strength (0.0004–0.7 mol/kg), pH (1–10), temperature (0–95 °C), and specific conductance (30–70,000 μS/cm) (McCleskey and others, 2012a). PHREEQCI input files for calculating...
Executive Summary Traditionally in the USGS, data is processed and analyzed on local researcher computers, then moved to centralized, remote computers for preservation and publishing (ScienceBase, Pubs Warehouse). This approach requires each researcher to have the necessary hardware and software for processing and analysis, and also to bring all external data required for the workflow over the internet to their local computer. To explore a more efficient and effective scientific workflow, we explored an alternate model: storing scientific data remotely, and performing data analysis and visualization close to the data, using only a local web browser as an interface. Although this environment was not a good fit...
Categories: Project;
Tags: 2017,
All Funded Projects,
Completed,
Computational Tools and Services,
Software,
Land-use researchers need the ability to rapidly compare multiple land-use scenarios over a range of spatial and temporal scales, and to visualize spatial and nonspatial data; however, land-use datasets are often distributed in the form of large tabular files and spatial files. These formats are not ideal for the way land-use researchers interact with and share these datasets. The size of these land-use datasets can quickly balloon in size. For example, land-use simulations for the Pacific Northwest, at 1-kilometer resolution, across 20 Monte Carlo realizations, can produce over 17,000 tabular and spatial outputs. A more robust management strategy is to store scenario-based, land-use datasets within a generalized...
Categories: Project;
Tags: 2016,
All Funded Projects,
Completed,
Computational Tools and Services,
Data Release,
USGS scientists often face computationally intensive tasks that require high-throughput computing capabilities. Several USGS facilities use HTCondor to run their computational pools but are not necessarily connected to the larger USGS pool. This project demonstrated how to connect HTCondor pools by flocking, or coordinating, within the USGS. In addition to flocking the Upper Midwest Environmental Science Center and the Wisconsin Water Science Center, we have flocked with the USGS Advanced Research Computing Yeti supercomputing cluster and other water science centers. We also developed tutorials on how to sandbox code using Docker within the USGS environment for use with high-throughput computing. A main accomplishment...
Categories: Project;
Tags: 2017,
All Funded Projects,
Completed,
Computational Tools and Services,
Docker,
R code that takes in the nest capture history data (chdata.csv), reformats it for model fitting in the Bayesian MCMC software JAGS via the R package jagsUI. Various generalized linear mixed models are fit using a Huggins two occasion capture history model structure as in Program Mark. A series of models of increasing complexity are fit and compared using DIC. Model text is written to text files for each model but is generally not used or saved. Posteriors are saved as Rworkspaces or written to text files for use in population estimation (nostpop.R). Code can be run to generate model results and R workspaces/objects to inspect parameter estimates. The primary purpose of this code is to compare various mixed model...
Categories: Data,
Software;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
BIOLOGICAL CLASSIFICATION,
BIOLOGICAL CLASSIFICATION,
This R code (eggs.R) inputs the quality controlled nest card data and (1) performs additional quality control on the egg code data, (2) reformat the eggs data into a tidy file of egg observations, (3) summarizes egg data into yearly means of initiation and hatch date based on incubation model, and (4) writes csv files for tidy egg data (eggs.csv) and yearly nest stats (yearstats.csv).
Categories: Data,
Software;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
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