- An extreme climate gradient-induced ecological regionalization in the Upper Cretaceous Western Interior Basin of North America , GEOLOGICAL SOCIETY OF AMERICA BULLETIN (2021)
- Downscaling of real-time coastal flooding predictions for decision support , NATURAL HAZARDS (2021)
- Efficient Drone-Based Rare Plant Monitoring Using a Species Distribution Model and AI-Based Object Detection , DRONES (2021)
- Evaluating online and tangible interfaces for engaging stakeholders in forecasting and control of biological invasions , ECOLOGICAL APPLICATIONS (2021)
- Open Source Software Development , Geographic Information Science & Technology Body of Knowledge (2021)
- Space-time analytics of human physiology for urban planning , COMPUTERS ENVIRONMENT AND URBAN SYSTEMS (2021)
- Spatially Explicit Fuzzy Cognitive Mapping for Participatory Modeling of Stormwater Management , LAND (2021)
- Aboveground carbon loss associated with the spread of ghost forests as sea levels rise , ENVIRONMENTAL RESEARCH LETTERS (2020)
- Geospatial simulation steering for adaptive management , Environmental Modelling & Software (2020)
- High Resolution Viewscape Modeling Evaluated Through Immersive Virtual Environments , ISPRS International Journal of Geo-Information (2020)
North Carolina (NC) has launched the NC Wastewater Monitoring Network as part of the Centers for Disease Control and Prevention (CDC) National Wastewater Surveillance System (NWSS). This system provides information on the presence and persistence of SARS-CoV-2-like viruses in wastewater systems as a metric of community COVID-19 prevalence. This approach provides a relatively low-cost way to measure both symptomatic and asymptomatic COVID-19 infections in a community-wide sample. Wastewater surveillance can demonstrate trends in COVID-19 prevalence, direct action to protect public health, and allay concerns about the burden of disease when SARS-CoV-2 concentrations are low. The NC Wastewater Monitoring Network builds on an existing collaboration between NCDHHS and the NC Wastewater Pathogen Research Network (NC WW PATH) led by Dr. Rachel Noble in collaboration with University of North Carolina (UNC) system researchers including those from North Carolina State University, UNC Chapel Hill, UNC Charlotte, UNC Wilmington, and East Carolina University. NC WW PATH has developed laboratory methods for measuring the SARS- CoV-2 virus in samples from wastewater treatment plant influent wastewater and primary solids and completed weekly sampling at 20 wastewater treatment plants representative of urban, semi-urban, and rural wastewater sources across nine counties in 2020. NC WW PATH continues to compare wastewater and solids concentrations with data from NCDHHS and other community prevalence studies while applying epidemiological and geospatial tools to develop statewide interactive mapping to better inform public health decisions.
Participation and inclusion are highly sought and valued in urban and regional decision-making. However, processes for eliciting input from underrepresented populations and merging expert and local knowledge are often ineffective, undermining decision-making efforts. This RCN will collaboratively explore whether multi-user, web-based â€œseriousâ€ gamesâ€“â€“using real data and scientific models to show the connectedness of locationsâ€“â€“could increase equitable participation in local decision-making, elevating the voices of underprivileged groups and diverse perspectives. The RCN will unite researchers and stakeholders to plan the design of a futuristic game called TomorrowNow, which enables people to interact with spatially explicit models of urbanization and associated changes to stormwater hydrology (quantity) and biogeochemistry (quality), problems of increasing concern across urbanizing regions in the US. The RCN will convene leaders from local and regional governments, non-governmental organizations, and research teams specializing in natural, social, and computer sciences in the Research Triangle region of North Carolina; these leaders will collaboratively identify needs and approaches for improving inclusive participation and allowing a wider range of stakeholders to explore and visualize intervention strategies in the places where they live and work. Stakeholders will help researchers conceive the game while co-producing stormwater management strategies and technical specifications. The network will establish and maintain both personal interactions and a collaborative online space for knowledge-sharing that will cultivate smart connections among stakeholders in the Triangle and culminate in consensus for the best strategy to develop the models and interface for TomorrowNow. The RCN, led by PI Ross K. Meentemeyer (North Carolina State University), will facilitate cross-sector collaboration and bridge existing silos among academics and community leaders to define the boundaries of the public engagement and multi-municipal decision-making problems that have so far hindered implementation of large-scale stormwater management efforts in the Triangle. The RCN will also identify important cyber infrastructure requirements for addressing those problems through TomorrowNow. The input of diverse communities will be collected via surveys, semi-structured interviews, panels, discussions during in-person workshops and symposia, and through discussion threads in an open-source online community.
Anthropogenic nutrient loading is a critical driver of water quality throughout North Carolina and much of the world. Nutrient loading has increased over the last century due to fertilization of crops and green spaces, as well as waste from humans, pets, and livestock. The most salient outcome of nutrient loading is increased eutrophication (organic matter accumulation in surface waters), often leading to harmful algal blooms and hypoxia, which jeopardize water supplies and public recreation. As such, developing nutrient criteria and management strategies is a timely objective for state water resources managers. While sources of nutrients have been identified and many nutrient control measures have been proposed, there remains a need to quantitatively assess these sources and controls, particularly at the watershed scale. In this study, we propose a modern, data-driven approach to update our knowledge of the magnitudes of various sources and the effectiveness of various nutrient control strategies. The approach leverages large databases of water quality, hydro-meteorology, and watershed attributes, which have been developed by federal, state, and local governments over the last few decades. The approach will also leverage a sophisticated â€œhybridâ€ watershed model that combines a mechanistic representation of nutrient fate and transport within a probabilistic (Bayesian) framework where prior knowledge of loading and transport rates is updated through data-driven inference, and where uncertainty is rigorously quantified. Our project will focus on the Falls and Jordan Lake watersheds of North Carolina, for which preliminary models and data are already available. Key objectives include (1) development of an integrated geospatial database on watershed development, (2) adaptation of the hybrid watershed model to assess watershed development practices, and (3) application of the model to assess future management scenarios. Expected outcomes include quantitative guidance for developing nutrient reduction goals and watershed management strategies.
The GAPS (Geospatial Applications for Problem Solving) for Hi-Tech Teens program is a collaborative effort between NC State University, Wade Edwards Learning Lab (WELL), and RTI International. The program is designed to introduce high school students to Geospatial science, Geographic Information Systems (GIS), and advanced geovisualization technologies through an intensive after-school STEM learning experience. The GAPS for Hi-Tech Teens program will consist of 2 unique 8-week cohorts (20 students) during the academic year, including 2 mandatory contact hours per week, plus a 2-hour open lab where students can work with mentors on project activities, for a potential of 64 contact hours. The program will also include a 1-week summer program focused on college and career preparedness. The four primary goals of the program are to 1) engage students in community-focused decision making using Geospatial science, 2) increase student capacity for creating and using interactive geovisualization technologies, 3) expose students to GIS-STEM related college programs and careers, and 4) support students with tutoring in mathematics and science. Another mission of the program is to reach historically underserved populations in STEM fields, including African Americans, Hispanics, American Indian, and female students. Therefore, we will utilize WELLâ€™s experience and established relationships with several Wake County schools to provide a diverse base of possible participants in the GAPS for Hi-Tech Teens program, with a goal of at least 60% of participants being minority. To achieve goal 1 the curriculum will be designed around an 8-week project activity that focuses on relevant community topics. Students will work in pairs to identify a spatial topic, acquire the necessary data, develop relevant geospatial models (through student-built tangible landscape systems), analyze and visualize their results, and communicate findings to peers and the public. To achieve goal 2 students will design and build their own tangible landscape system coupled with GIS. Students will also learn how to map using GIS software. In addition, each cohort will participate in a technology field trip to NC Stateâ€™s Geovisualization Lab where they will interact with advanced geospatial technologies, including Virtual Reality, GazeGIS, SimTable sandbox models, 3-D glasses, GigaPan cameras, and GPS units. To achieve goal 3 students will interact and observe geospatial professionals through an expert panel, and college and career field trips during the 1-week summer program. The semester cohorts will also be mentored by our professional collaborators at RTI International and NC State, community partners, as well as the graduate and undergraduate assistants. To achieve goal 4 students will have access to a dedicated mathematics and science tutor at the WELL for 6 hrs/week outside of the regular program activities.
Eradication and/or containment of an invasive pest species is one of the most difficult, expensive and critical decisions that engage state, federal and private sector affected parties and stakeholders. Deciding whether or not to engage an eradication or containment program can vary according to complex factors that are difficult to predict. First, pest incursions are affected by many site-specific characteristics â€“ such as the landscape configuration of the affected host(s) and distribution of pests â€“ that make it challenging to define an action area, where containment or eradication would occur. Second, the timeline for making the decision to enter a program is not consistent among pests because of their life histories and response to the new environment. The response timeline can have a positive or negative effect, depending on whether or not the program is initiated before a critical threshold. Third, pest biology and treatment options could range from well-known to unknown and treatment efficacies could vary drastically. Even when treatment options are well-known and effective, these resources must be deployed in a timely and organized manner for containment or eradication to be successful. When there is little information on pest biology or treatment options, knowledge in these areas must be derived or developed to determine if containment or eradication is feasible. A decision to not enter a program that is not technically feasible will result in no program related costs, but a negative perception from affected parties; a win-lose. Alternatively, entering a program that is not technically feasible will result in high costs and a negative perception from the affected parties because the program is likely to fail; a lose-lose. If, however, a program is both technically feasible and successful, the affected industry benefits and regulatory resources are optimized, a win-win. Identifying the conditions that are likely to lead to each of these outcomes is a central question for those that manage invasive pests and diseases. While it is not feasible to predict the conditions surrounding an incursion a priori, we can address key factors surrounding an incursion once it occurs using the Eradication Analysis & Decision Support (eRADS) tool. First, eRADS identifies the area of concern using data on the pest distribution (e.g., from the Cooperative Agricultural Pest Survey Program) and its associated hosts (e.g. NASS Cropland Data Layer) and what is known about the biology of the pest (e.g. Global Pest and Disease Database and other data sources). Next, eRADS quantifies landscape metrics in the action area â€“ specifically the connectivity of suitable hosts â€“ to determine how likely the pest could disperse. Then, eRADS leverages what is known about the pest from CAPS datasheets or New Pest Response Guidelines, to evaluate treatment options and determine how quickly they might be deployed. eRADS evaluates the technical feasibility of implementing a program and provides a score ranging from â€œFeasibleâ€ to â€œNot Feasible,â€ along with an epidemiological description. eRADS allows decision makers to evaluate how technically feasible a program might be and determine what modifications are required to make it feasible.
Invasive pests are a serious threat to the nations forest and agricultural systems. Planning and optimizing management of these pests at large-scales often requires input from a variety of stakeholders, many of which often disagree with the suggestions of experts due to different evidentiary bases and experiences. Forecasts to support planning and response rely on model predictions of future spread and risk. Tangible landscape brings this modeling process to life and makes it easier to understand for all stakeholders. Up until today there has been no framework to both communicate and test different scenarios and assumptions held by different farmers, land managers, regulators, researchers and other stakeholders. Tangible Landscape is a novel modeling platform that allows users to guide complex geospatial models via physical interaction. Users can designate treatment zones on a physical representation of a landscape, which are then incorporated into the pest and pathogen spread model. Results are projected back onto the landscape, allowing users to quickly and intuitively visualize how proposed management scenarios are likely to affect spread across the landscape. Tangible landscape brings this modeling process â€œto lifeâ€ by making evident the processes, assumptions and the relationship between forecast system outputs and three-dimensional reproductions of actual agricultural or pest management settings. Tangible landscapes make it easier to understand complex dynamics between production and management scenarios for all stakeholders. Plant Protection and Quarantine (PPQ) is an agency within APHIS that â€œsafeguards agriculture and natural resources from risks associated with the entry, establishment, or spread of plant pests and noxious weeds to ensure an abundant, high-quality, and varied food supplyâ€. Each year PPQ manages a large number of invasive species and faces challenges to determine the most viable, high-impact decisions given limited resources and complex epidemiological settings. The Tangible Landscape technology assists making such decisions by allowing stakeholders, decision makers, and land managers to interact physically with simulation models to facilitate visualization and understanding of the situation. It allows both subject matter experts and non-technical users to analyze multiple control scenarios in an instantaneous manner and enables users and policy makers to explore alternative decisions based on the available resources and user-driven variable assumptions regarding management assumptions. The goal of this project is to integrate pest and disease frameworks with existing current Tangible Landscape interface and to then validate management scenarios using multiple case studies that have real-world applications and actual production settings. Developing a tool that is useful for farmers and for regulatory agencies like PPQ would require validating models and technologies used in the Tangible Landscape. We plan to accomplish this using well-known exotic pests and diseases that are part of current programs and real-world challenges.
Accurately mapping wetlands at the road planning stage is critical for timely, cost-effective, and compliant projects. Assessing wetland impacts on proposed road corridors have required trained personnel to identify, measure and evaluate acreage impacts to jurisdictional wetland. NCDOTâ€™s Wetland Predictive Model (WPM) is a GIS and remote sensing-based tool designed to reduce the need for these costly and time-consuming activities by creating a preliminary map of wetlands without the need for field measurements. To do so, the WPM uses lidar-derived terrain variables such as elevation and slope alongside soil maps and other geospatial data as inputs to a predictive model. WPM inputs such as lidar data are expensive and time-consuming to collect, and so are available only infrequently. Likewise, other geospatial data such as high-resolution satellite imagery and digital soil maps are not always available at the frequency necessary for accurate wetland mapping in potential corridors. Even when up-to-date observations are available, they may lack the spatial or spectral resolution necessary to aid in wetland identification.
A team from Center for Geospatial Analytics, North Carolina State University (CGA-NCSU), City of Raleigh (City), and the North Carolina Next Generation Network (NCNGN) propose to develop a framework for generating high resolution 3D data needed to update 3D city base map that can be processed in hours rather than days. This would facilitate deployment of geospatial analytics for wide range of applications that are not currently possible, especially those where time is critical. Examples include analysis of impacted areas of sanitary sewer overflows, estimation of water depth in flooded neighborhoods, post-storm debris mapping and many others. CGA-NCSU will use data collected by sUAS at a City location to develop workflow for computing a georeferenced 3D model of the mapped area from the sUAS-acquired set of overlapping imagery using Structure from Motion (SfM) technique and provide it in a format suitable for merging with the City elevation model. The test area will be approx. 0.5 km2. The workflow will be developed and tested at CGA-NCSU using OpenDronemap (ODM) and WebODM to determine the baseline time and computational requirements. The workflow will be then ported to the gigabit connected networks and cloud-based high-end computers (GENI) capable of parallel computing available through NCNGN to facilitate fast processing of images and efficient transfer of data between the sUAS source (NCSU), computing (Duke) and 3D base map (City). The resulting updated 3D City map will then be available through 3D WebGIS application InVision, developed recently by CGA-NCSU in collaboration with the City.
Fort Bragg military base in the Sandhills of North Carolinaâ€™s Piedmont is situated on more than 150,000 acres. Sections of the base are used for military training, others serve as refugia for endangered and threatened species. Recent stream surveys conducted at Fort Bragg documented the presence, abundance and distribution of freshwater mussels on Post. Villosa delumbis, a species listed as state endangered was found in the Little River, which is part of the Cape Fear River basin. Ellipitio complanata, and Uniomerus caroliniana were found in both the Little River and in Drowning Creek, which is part of the Lumber River basin. Stream channel substrate size, availability, and stability were the primary factors contributing to habitat suitability for freshwater mussel species. Measurements of stream channel grain size distributions from study reaches were used to calibrate a sediment transport model. The model serves as a predictive tool for identifying areas with greater potential for future in-channel mussel augmentation and enhancement efforts. Catchment-average erosion rates, measured from in-situ cosmogenic nuclide 10Be extracted from quartz-bearing stream sediments indicates that the Little River basin is eroding at about 25 m/Ma (0.025 cm/yr) over timescales of ~104 years. These first 10Be results from the Sandhills region of North Carolina provided baseline reference frame estimates of the upland erosion and sediment transport rate through the Little River basin prior to anthropogenic modifications of the landscape. This proposal builds on these prior studies and the recommendations contained within the Levine et al. (2015) final report for continued study of Fort Braggâ€™s freshwater mussel populations and river and hillslope landscape factors important to their present distribution and future fate. In this document we propose to: 1) Establish a routine monitoring program to document the presence of freshwater mussel fauna in Fort Bragg streams; 2) Survey streams upriver of Fort Bragg to determine if they can serve as sources of freshwater mussel stock for population augmentation; 3)Determine the value of using freshwater mussels as environmental monitors; 4) Develop a dynamic model of upland soil erosion potential paired with tributary stream sediment transport and delivery to the Little River and Drowning Creek trunk channels, which can be used to predict the potential viability of stream sites for sustainable restoration; 5) Develop an environmental education poster that demonstrates the importance of preserving Fort Braggâ€™s aquatic fauna; and 6) Develop a demonstration of a Tangible Landscape system as a collaborative environment for communication of spatial patterns and sediment transport. â€ƒ
Mean transit times (MTT) for the water and contaminants in a groundwater system (from recharge at the water table to discharge at streams and rivers), and magnitudes of water and contaminant fluxes from groundwater to streams, are fundamental, linked properties of groundwater systems. These fluxes and MTT values may be estimated using three distinct approaches that combine groundwater age-dating and other measurements related to groundwater ? surface water interaction: the streambed point approach (SPA), streambed blanket approach (SBA), and mass balance approach (MBA). The spatial scales of integration inherent in these approaches are very different, suggesting different capabilities and likely pros and cons for each, but side-by-side evaluation of the approaches has not yet been done. We will evaluate SPA, SBA, and MBA side by side in two streams, in an environment (North Carolina Coastal Plain) where the results obtained will be directly relevant to the critical water resource issue of non-point-source N contamination in groundwater and discharge from groundwater to streams, especially the time scale (possibly controlled by the MTT) on which this contamination and discharge can be expected to respond to management initiatives. Comparison among the 3 approaches will be based on the following results from each: (1) groundwater MTT, (2) N and water flux from groundwater to the streams, and (3) estimation (from excess N2) of the total amount of denitrification in the groundwater systems feeding the streams. The proposed work is needed to evaluate the pros and cons of different approaches for combining groundwater age and other hydrologic data to estimate the magnitude and time scale of non-point-source pollutant fluxes from groundwater to surface water. This is of direct relevance to many areas of groundwater hydrology: groundwater age-dating, N contamination and non-point-source pollutant transport through groundwater, groundwater ? surface water interaction, and the design and evaluation of management efforts related to non-point-source pollutants.