GRI RESEARCH

Visualization
GRI scientists are striving to advance the technology and utilization of scientific visualization, information visualization, visual analysis, and image processing for the computational sciences. The fundamental goal of visualization is to enable and enhance human comprehension of complex phenomena.





Aquatic Invasive Species- Habitat Suitability Modeling
GRI researchers are using Habitat Suitability Modeling which uses computer algorithms to manipulate data that create models to predict, control and narrow the expansive search area required for detection of new non-native species of likely avenues for the spread of existing plant populations. Researchers have found four ways to control aquatic invasive species. They include chemical, biological, physical and mechanical methods. These methods can control or eradicate invasive plant species in an area.
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Corn crop density assessment using texture analysis on visible imagery collected using unmanned aerial vehicles
Determining corn crop density on a large field is of tremendous value to monitor plant health and damages caused by hogs and deer. Texture modelling techniques are investigated to map three different densities (Low, Medium and High) on a corn field by using visible imagery collected using an Unmanned Aerial Vehicle (UAV).
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Detecting Aflatoxin using Hyperspectral Imaging
Hyperspectral imaging is a way of seeing what is invisible to the human eye. GRI researchers are using this to detect biological and chemical toxins that contaminate crops. This is done by splitting the electromagnetic spectrum into many spectral bands, which expose hidden information invisible to the natural eye. The specific contaminant being studied is a fungal metabolite called aflatoxin. This lethal toxin is produced by a fungus called Aspergillus. It is a known carcinogen associated with liver and lung cancers in humans. Many external stresses cause the fungi to react but hot and humid weather conditions increase its production of aflatoxin that invades corn and other commodities. The goal is to help improve detection and accuracy.
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Enhanced Soils Mapping For Productive Capacity Assessments
This research uses geospatial technologies to create methodology used in defining soil management zones that address soil variability in distinct areas and identify the soil properties that limit crop production while increasing soil conservation. Determining appropriate soil management zones can lead to an increased profit by either increasing yield in areas of fields that are being underutilized or decreasing fertilization in areas of fields where maximum economic yield has already been attained. Moreover, robust and repeatable methodology for construction of management zones will provide an empirical basis for developing variable rate fertilizer prescriptions that optimize profitability and minimize off-site nutrient transport, thereby benefiting the producer, the public, and the environment.
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FloodViz: Visual Analytics for Assessment and Interpretation of Simulated River Flooding
The FloodViz project involves the development and testing of visual analytics software to enable scientists and forecasters to better interpret and distribute hydrologic information. This software will be useful in the research community as an interpretation tool for river level and flood data. The tools developed serve as a useful platform for hydrologic forecasters within the National Weather Service to more quickly and accurately determine areas at risk for flooding and allow NOAA river forecasters to better visualize the extent of flooding. Additionally, these tools allow forecasters to relay more information to the emergency management community while issuing forecasts to help protect lives, property and the nation.
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GeoVol-Geospatial Volume Rendering
This project created software using direct volume rendering techniques that achieved real-time performance and high image quality. A user study was conducted to compare the implemented volume rendering technique with state-of-the-art isosurface rendering to examine hurricane data. The results of the study established that both volume rendering and isosurface visualizations were effective in examining data from computer simulations of hurricanes. Because of the higher image quality and the interactive frame rates, direct volume rendering was preferred. Future studies will be conducted to quantify performance differences between using the traditional 2D methods and the 4D methods.
Hurricane Lili Visualization Email Contact





GIS for Aquatic Plant Management
Geographic Information Systems (GIS) have become the new tool for information management, planning and presentation for invasive aquatic plant management programs and is critical in every component of the program.
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Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (GCPO LCC)
GRI has partnered with the GCPO LCC to provide critical LCC research and computing capacity for LCC activities. As a research hub for the GCPO LCC, GRI has established over $4 million in cooperative agreements with the U.S. Fish and Wildlife Service to fund more than 20 different LCC research projects. This diverse research program includes exploration of ecosystem health, resilience to climate change and urbanization and interrelationships among species and their habitats.
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Hurricane Landfall Estimation and Storm Surge
The storm surge of Hurricane Katrina, which made landfall in Mississippi and Louisiana in 2005, was unprecedented for its elevation, area coverage, and levee breaches. Due to the storm surge, areas along the Gulf Coast were severely flooded and destroyed. GRI is addressing recent Mississippi and Louisiana storm surge issues using the finite element model ADCIRC. The research will facilitate answers to the sensitivity of the storm surge in Mississippi to wind profiles of major hurricanes, as well as to hurricane eye size and landfall estimation.
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Integrated Ecosystem Assessment (IEA) Tool
This research was implemented as part of an overall Ecosystem Approach to Management (EAM). It looks at all indicators, such as tourism and recreation, climate change, fish populations and conservation and energy demands to evaluate ocean health. In the past, scientists, because of the limits of scientific knowledge and technology could only concentrate on individual segments and species of the ocean. The EAM approach using IEA management assessment tool allows them to combine data and look at the ocean as a whole. Research is being carried out at four sites in the Northern Gulf of Mexico: Perdido Bay, Florida; Mississippi Sound, Mississippi; Barataria Basin, Louisiana; and Galveston Bay, Texas.
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Integrated Pest Management Systems and Resistance Management Using Geospatial Technologies
This research has evaluated the use of remote sensing technologies to detect and predict spatial distribution of weed populations for the purpose of designing site-specific herbicide prescriptions and monitoring the spread of herbicide resistant weed species. Associated spatial technologies have been used to generate guidelines for creation of site-specific harvest-aid, plant growth regulator, and insecticide prescriptions. A unique contribution of this research has been the development of novel statistical models that more fully characterize geographic, topographic, hydrological, edaphic, and producer-induced sources of variation in yield than previously understood. The research also highlights the immense complexity of spatial data collection, management, geoprocessing, and integration for decision support in site-specific agriculture. Outcomes of this study may increase efficiency and profitability, reduce the threat of off-target movement of residual herbicides in runoff to surface and groundwater, and reduce herbicide usage through precision applications.
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Invasive Species Program
GRI researchers actively study invasive plants that take over agricultural and natural areas, with expertise for studies ranging from regional impacts through use of remote sensing and GIS, to cellular and molecular studies of plant uptake, and genetic composition. GRI brings together multidisciplinary research teams comprised of university and government researchers to address diverse questions on the management of invasive species.
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IPAMS - Invasive Plant Atlas of the MidSouth
The Invasive Plant Atlas of the Mid-South (IPAMS) is an integrated research and extension project to develop an invasive plant program for the Mid-South states of Alabama, Arkansas, Louisiana, Mississippi, and Tennessee. Research activities include conducting systematic regional vegetation surveys to assess the distribution of key invasive plants, developing models for predicting the occurrence of target species based on land use and cover, and evaluating the relative effectiveness of professional versus volunteer surveys.
IPAMS Web Site Email Contact





Providing Accurate Data for Field Monitoring of Peanut Production
Reliable yield monitors have been developed for a variety of crops including corn, soybeans, wheat, and cotton. Due to the nature of harvesting and threshing peanuts, however, the ability to provide accurate yield data has been rudimentary, at best. The objective of this research is to use a system for yield measurement previously developed at Mississippi State University and commercialized through MSTX Agricultural Sensor Technologies (MAST), LLC to compare management zones, buy-point and field weights from adjusted and raw yield data in peanuts. The results of this study will potentially allow peanut producers to evaluate inputs, manage pests, make better land-use decisions and perform economic analysis in peanut production.
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Satellite Rainfall Applications for Surface Hydrology
GRI has evaluated results which examine how soil moisture states simulated by land surface models are impacted when forced with various precipitation datasets. These datasets are from a collection of Global Precipitation Mission satellite constellation configurations gathered over the continental United States.
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Spatial Detection of Agri-terrorism
This GRI project develops and deploys an automated target recognition system that utilizes hyperspectral imagery to detect biological or chemical contamination of vegetation. The Automated Target Recognition - ATR - system is applied to the problem of BioSecurity, i.e. the detection of crop contamination via biological or chemical agents.
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Visualization Techniques for Improving Understanding of Severe Storms
This project advances the visual analysis tools to increase a modeler or analyst's ability to understand hurricane structure, intensity and dynamics. The project focuses on developing new 2D and 3D visualization tools which produce visualization products that can be made publicly available, easily interpreted and can be viewed on personal computers or used in television coverage. The goal is to create a hurricane visualization system that accepts both simulated and measured data as input and put all the data into a single geographic context.
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WISDOM - Weather In-Situ Deployment Optimization Method
GRI scientists and students are participating in WISDOM, the Weather In-Situ Deployment Optimization Method research program that seeks to improve hurricane forecasting time by three to seven days before a storm's landfall by providing wind and atmospheric data in areas of the Atlantic basin that are poorly observed. The WISDOM program launches small super-pressure balloons with payloads that include GPS and satellite radio communications capabilities.
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Modified: May 17, 2016  •  WebMaster  •  Intranet