Resource for Advanced Modeling (RAM) Active
The RAM room VisWall display uses 24 individual monitors
Branch scientists have developed the Resource for Advanced Modeling (RAM), a modeling facility for collaborative research both within the U.S. Geological Survey (USGS) and with the wider research community. The facility provides a collaborative working environment for up to 20 scientists from within the USGS and the wider research community. There are networked, wireless computing facilities with the ability to run and test various models (e.g., Maxent, Boosted Regression Trees, Logistic Regression, MARS, Random Forest) for a variety of spatial scales (county, state, region, nation, or global). These techniques use predictor layers from MODIS time-series data as well as current and future climate layers.
Resource for Advanced Modeling (RAM)
In 2009, the USGS Fort Collins Science Center renovated its Resource for Advanced Modeling (RAM) room, a modeling facility for collaborative research within the USGS and the wider research community. The main purpose of the RAM is to bring together remote sensing and climate forecasting experts, habitat modelers, field ecologists, and land managers in a synergistic environment.
The RAM provides a collaborative working environment for up to 20 scientists, supported with networked, wireless computing capability for running and testing various scientific models (e.g., various species distribution models) at a variety of spatial scales, from county to global levels. Models use predictor layers that can include current and future climate layers (near- and long-term projections), remote-sensing derivatives (such as MODIS phenology metrics), land cover, topography, and anthropogenic features.
The RAM works with a variety of clients from various government and non-government agencies from the national to local level. Those interested in having a RAM session should contact Catherine Jarnevich.
The “VisWall,” a bank of 24 wall-mounted monitors in a 6x4 array, can be used for displaying large or numerous GIS datasets, photos, or other data products. The monitor array can be configured to show a single map spread across all 24 monitors, 24 individual monitor outputs, or a combination of intermediate-sized outputs, such as three 4x2-monitor maps. Investigative teams and working groups using the RAM can employ VisWall for demonstrations and robust data exploration.
In addition, the RAM offers WebEx and phone conferencing capability, a SMART board with screen-capture capability, white boards, and wireless internet. The collaborative workroom’s projection system can quickly alternate between 6 laptops to project their content. The RAM also hosts several computers, totaling 132 cores, each with at least 2 GB of RAM per core. There is a separate work area and a small lounge for break-out discussions.
Software for Assisted Habitat Modeling (SAHM)
The RAM is equipped with a modeling program called the Software for Assisted Habitat Modeling (SAHM). The software was created to both expedite habitat modeling and help maintain a record of the various input data, pre- and post-processing steps and modeling options incorporated in the construction of a species distribution model and is a set of modules within the established workflow management and visualization VisTrails software. SAHM is used to create habitat suitability models for species of management interest. The code provides a significant capability to run, in a consistent and repeatable manner, five different habitat models (Maxent, Boosted Regression Trees, Logistic Regression, Multivariate Adaptive Regression Splines, and Random Forest) along with allowing user’s to define response curves themselves to develop a model. Details are included in the paper by Morisette et al., linked below.
SAHM combines predictor layers (environmental raster data layers of the study area, such as those available in the RAM) with user-collected field sampling measurements for a particular species. The program uses these data to run statistical models that analyze habitat requirements of a species of interest and predict the potential distribution based on habitat suitability. Model outputs can help users, such as land and natural resource managers, generate predictive maps or reports to aid in predicting and managing the spread of invasive species. SAHM is freely available to interested parties. The RAM also can host a two day training session based on need that is also free to attend. SAHM Fact Sheet
VisWall
In November 2012, the Fort Collins Science Center (FORT) officially implemented a powerful new capability within its Resource for Advanced Modeling: a bank of 24 wall-mounted, 27-inch monitors, arrayed 6 across and 4 high, that can be used for displaying large or numerous GIS datasets, photos, or other data products. This visualization wall, or “VisWall” for short, was built to support interactive exploration of model input and model output. The 6x4 VisWall monitor array can be configured to show a single map spread across all 24 monitors, 24 individual monitor outputs (Fig. 1), or a combination of intermediate-sized outputs, such as six 2x2- or three 4x2- monitor maps (Fig. 2).
The software used to run the displays—a combination of VisTrails1 and a VisWall package developed here at FORT—is relatively user friendly and easy to get started with. The 6x4 array of monitors can be used to explore and visualize differences across two variables—for example, showing habitat maps for 4 different species as they might change across 6 different time steps. Alternatively, using all 24 monitors to show one image enhances the display resolution well beyond that of the standard LCD projector, from the approximately 2 million pixels of a standard LCD projector to 50 million pixels for VisWall. The number of pixels directly relates to the resolution at which map output can be displayed. For example, the VisWall can display every pixel in a map of the 48 contiguous states of the U.S. with 1-km pixels. A region encompassing the western half of the United States, presented in a 4x2 array, can display at approximately 600-m resolution (Fig. 3). For a state-level map, the VisWall can show the area at roughly a 90-m resolution.
VisWall is an outgrowth of a FORT-hosted, joint project with the U.S. Department of the Interior (DOI) and NASA to use FORT’s Resource for Advanced Modeling (RAM) to connect climate drivers to biological responses. To that end, a primary objective of the project is to support and enhance computational and visualization capabilities at the RAM. The project’s primary client is the DOI North Central Climate Science Center, located at Colorado State University; however, VisWall is available to FORT scientists and RAM clientele, any of whom can take advantage of VisWall for data exploration.
Below are publications associated with this project.
Habitat suitability of patch types: a case study of the Yosemite toad
Buffelgrass-Integrated modeling of an invasive plant
Ensemble habitat mapping of invasive plant species
NASA and USGS invest in invasive species modeling to evaluate habitat for Africanized Honey Bees
Invasive species information networks: Collaboration at multiple scales for prevention, early detection, and rapid response to invasive alien species
Non-native plant invasions of United States National parks
Risk assessment of invasive species
The RAM is equipped with a modeling program called the Software for Assisted Habitat Modeling (SAHM). The software was created to both expedite habitat modeling and help maintain a record of the various input data, pre- and post-processing steps and modeling options incorporated in the construction of a species distribution model.
- Overview
Branch scientists have developed the Resource for Advanced Modeling (RAM), a modeling facility for collaborative research both within the U.S. Geological Survey (USGS) and with the wider research community. The facility provides a collaborative working environment for up to 20 scientists from within the USGS and the wider research community. There are networked, wireless computing facilities with the ability to run and test various models (e.g., Maxent, Boosted Regression Trees, Logistic Regression, MARS, Random Forest) for a variety of spatial scales (county, state, region, nation, or global). These techniques use predictor layers from MODIS time-series data as well as current and future climate layers.
Resource for Advanced Modeling (RAM)
In 2009, the USGS Fort Collins Science Center renovated its Resource for Advanced Modeling (RAM) room, a modeling facility for collaborative research within the USGS and the wider research community. The main purpose of the RAM is to bring together remote sensing and climate forecasting experts, habitat modelers, field ecologists, and land managers in a synergistic environment.
The RAM provides a collaborative working environment for up to 20 scientists, supported with networked, wireless computing capability for running and testing various scientific models (e.g., various species distribution models) at a variety of spatial scales, from county to global levels. Models use predictor layers that can include current and future climate layers (near- and long-term projections), remote-sensing derivatives (such as MODIS phenology metrics), land cover, topography, and anthropogenic features.
The RAM works with a variety of clients from various government and non-government agencies from the national to local level. Those interested in having a RAM session should contact Catherine Jarnevich.
The “VisWall,” a bank of 24 wall-mounted monitors in a 6x4 array, can be used for displaying large or numerous GIS datasets, photos, or other data products. The monitor array can be configured to show a single map spread across all 24 monitors, 24 individual monitor outputs, or a combination of intermediate-sized outputs, such as three 4x2-monitor maps. Investigative teams and working groups using the RAM can employ VisWall for demonstrations and robust data exploration.
In addition, the RAM offers WebEx and phone conferencing capability, a SMART board with screen-capture capability, white boards, and wireless internet. The collaborative workroom’s projection system can quickly alternate between 6 laptops to project their content. The RAM also hosts several computers, totaling 132 cores, each with at least 2 GB of RAM per core. There is a separate work area and a small lounge for break-out discussions.
Software for Assisted Habitat Modeling (SAHM)
The RAM is equipped with a modeling program called the Software for Assisted Habitat Modeling (SAHM). The software was created to both expedite habitat modeling and help maintain a record of the various input data, pre- and post-processing steps and modeling options incorporated in the construction of a species distribution model and is a set of modules within the established workflow management and visualization VisTrails software. SAHM is used to create habitat suitability models for species of management interest. The code provides a significant capability to run, in a consistent and repeatable manner, five different habitat models (Maxent, Boosted Regression Trees, Logistic Regression, Multivariate Adaptive Regression Splines, and Random Forest) along with allowing user’s to define response curves themselves to develop a model. Details are included in the paper by Morisette et al., linked below.
SAHM combines predictor layers (environmental raster data layers of the study area, such as those available in the RAM) with user-collected field sampling measurements for a particular species. The program uses these data to run statistical models that analyze habitat requirements of a species of interest and predict the potential distribution based on habitat suitability. Model outputs can help users, such as land and natural resource managers, generate predictive maps or reports to aid in predicting and managing the spread of invasive species. SAHM is freely available to interested parties. The RAM also can host a two day training session based on need that is also free to attend. SAHM Fact Sheet
VisWall
In November 2012, the Fort Collins Science Center (FORT) officially implemented a powerful new capability within its Resource for Advanced Modeling: a bank of 24 wall-mounted, 27-inch monitors, arrayed 6 across and 4 high, that can be used for displaying large or numerous GIS datasets, photos, or other data products. This visualization wall, or “VisWall” for short, was built to support interactive exploration of model input and model output. The 6x4 VisWall monitor array can be configured to show a single map spread across all 24 monitors, 24 individual monitor outputs (Fig. 1), or a combination of intermediate-sized outputs, such as six 2x2- or three 4x2- monitor maps (Fig. 2).
The software used to run the displays—a combination of VisTrails1 and a VisWall package developed here at FORT—is relatively user friendly and easy to get started with. The 6x4 array of monitors can be used to explore and visualize differences across two variables—for example, showing habitat maps for 4 different species as they might change across 6 different time steps. Alternatively, using all 24 monitors to show one image enhances the display resolution well beyond that of the standard LCD projector, from the approximately 2 million pixels of a standard LCD projector to 50 million pixels for VisWall. The number of pixels directly relates to the resolution at which map output can be displayed. For example, the VisWall can display every pixel in a map of the 48 contiguous states of the U.S. with 1-km pixels. A region encompassing the western half of the United States, presented in a 4x2 array, can display at approximately 600-m resolution (Fig. 3). For a state-level map, the VisWall can show the area at roughly a 90-m resolution.
VisWall is an outgrowth of a FORT-hosted, joint project with the U.S. Department of the Interior (DOI) and NASA to use FORT’s Resource for Advanced Modeling (RAM) to connect climate drivers to biological responses. To that end, a primary objective of the project is to support and enhance computational and visualization capabilities at the RAM. The project’s primary client is the DOI North Central Climate Science Center, located at Colorado State University; however, VisWall is available to FORT scientists and RAM clientele, any of whom can take advantage of VisWall for data exploration.
- Publications
Below are publications associated with this project.
Filter Total Items: 19Habitat suitability of patch types: a case study of the Yosemite toad
Understanding patch variability is crucial in understanding the spatial population structure of wildlife species, especially for rare or threatened species. We used a well-tested maximum entropy species distribution model (Maxent) to map the Yosemite toad (Anaxyrus (= Bufo) canorus) in the Sierra Nevada mountains of California. Twenty-six environmental variables were included in the model represenAuthorsChristina T. Liang, Thomas J. StohlgrenBuffelgrass-Integrated modeling of an invasive plant
Buffelgrass (Pennisetum ciliare) poses a problem in the deserts of the United States, growing in dense stands and introducing a wildfire risk in an ecosystem not adapted to fire. The Invasive Species Science Branch of the Fort Collins Science Center has worked with many partners to develop a decision support model and a data management system to address the problem. The decision support model evalAuthorsTracy R. HolcombeEnsemble habitat mapping of invasive plant species
Ensemble species distribution models combine the strengths of several species environmental matching models, while minimizing the weakness of any one model. Ensemble models may be particularly useful in risk analysis of recently arrived, harmful invasive species because species may not yet have spread to all suitable habitats, leaving species-environment relationships difficult to determine. We teAuthorsT.J. Stohlgren, P. Ma, S. Kumar, M. Rocca, J.T. Morisette, C. S. Jarnevich, N. BensonNASA and USGS invest in invasive species modeling to evaluate habitat for Africanized Honey Bees
Invasive non-native species, such as plants, animals, and pathogens, have long been an interest to the U.S. Geological Survey (USGS) and NASA. Invasive species cause harm to our economy (around $120 B/year), the environment (e.g., replacing native biodiversity, forest pathogens negatively affecting carbon storage), and human health (e.g., plague, West Nile virus). Five years ago, the USGS and NASAInvasive species information networks: Collaboration at multiple scales for prevention, early detection, and rapid response to invasive alien species
Accurate analysis of present distributions and effective modeling of future distributions of invasive alien species (IAS) are both highly dependent on the availability and accessibility of occurrence data and natural history information about the species. Invasive alien species monitoring and detection networks (such as the Invasive Plant Atlas of New England and the Invasive Plant Atlas of the MiAuthorsAnnie Simpson, Catherine S. Jarnevich, John Madsen, Randy G. Westbrooks, Christine Fournier, Les Mehrhoff, Michael Browne, Jim Graham, Elizabeth A. SellersNon-native plant invasions of United States National parks
The United States National Park Service was created to protect and make accessible to the public the nation's most precious natural resources and cultural features for present and future generations. However, this heritage is threatened by the invasion of non-native plants, animals, and pathogens. To evaluate the scope of invasions, the USNPS has inventoried non-native plant species in the 216 parAuthorsJ. A. Allen, C. S. Brown, T.J. StohlgrenRisk assessment of invasive species
No abstract available. - Software
The RAM is equipped with a modeling program called the Software for Assisted Habitat Modeling (SAHM). The software was created to both expedite habitat modeling and help maintain a record of the various input data, pre- and post-processing steps and modeling options incorporated in the construction of a species distribution model.