GRI RESEARCH

Sensors and Modeling
Satellite technology has revolutionized our spatial perspective of global systems over the years. Under the Sensors and Modeling category, GRI researchers are developing programs to better understand how spatial and environmental processes affect the earth’s systems.





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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Coastal Ocean Color Trade Study
GRI scientists have created a system of unique data sets to enable a better understanding of environmental processes that occur in coastal environments. Coastal and inland waters and their environments were targeted for the initial mission due to their importance to various aspects of human activity and the inability of current systems to accurately sense these unique environments. This mission works in support of the planned GEO-CAPE satellite mission that monitors these environments and is critical for evaluating and understanding the spatial variations and dynamics associated with coastal environments.
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Coastal Resiliency from Hurricane Impacts
Coastal wetlands provide a line of defense for coastal communities against hurricane impacts. The wetlands can reduce wind, wave, and surge energy which will in-turn reduce the damaging effects of hurricanes on coastal infrastructure and communities. Research has been developed to improve our understanding of coastal resiliency from hurricane impacts in regards to wetland areas. This was achieved by using integrated numerical modeling and in-situ observations and remote sensing techniques.
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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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Cost Effective BMPs for Resilient Communities
This project developed a tool that will enable the development industry to design and build more resilient and sustainable communities through the inclusion of BMPs (Best Management Practices) in new commercial and residential construction.
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Data Software Development
GRI has developed software, a NetCDF-Java Toolbox for MATLAB, along with NOAA which would allow MATLAB users to standardize access to IOOS (Integrated Oceans Observing Systems)-compliant gridded data.
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Disruptions to Rail-Impacts Analysis and Decision Support (DRIADS)
This research seeks to explore the positive effects of combining Homeland Security issues with regional transportation infrastructure decision-making and economic development potential within the State of Mississippi and southeast region. This combined approach provides a geographically specific, but highly transferable demonstration of a solution relevant to the Department of Homeland Security (DHS) which integrates currently disparate geospatial and transportation analysis and modeling systems with policy and decision-making.This new generation of modeling capabilities can significantly improve regional transportation system resiliency.
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Earth Dams and Levees (EDLs) Sustainability
Research in using remote sensing to improve earth dam and levee sustainability has the potential to affect tens of millions of people who live or work behind levee-protected areas. MSU/GRI researchers in an international partnership are conducting research on multi-scale monitoring science to enable a sustainable future for the vast worldwide array of earth dam and levees. The research examines EDL critical infrastructure that provides flood protection, fresh water storage and renewable energy to developed and underdeveloped nations. This project is currently in year two and uses polarimetric and interferometric synthetic aperture radar (SAR) to examine earth deformations at a very small scale.
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Earth Science Knowledge Base
Under this project led by the Geosystems Research Institute, the NASA Applied Sciences Program has funded the Mississippi Research Consortium (MRC) to develop information technology that will facilitate searches for potential applications of NASA assets to various needs in the earth sciences community. In particular, it will help generate ideas for new ways to use NASA missions, research, and/or models in conjunction with operational decision-making processes (or decision support systems) to achieve a particular benefit to society. The main output of this work is the development of information technology that will facilitate that ability. The resulting system is called the Earth Science Knowledge Base (ESKB).
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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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Geospatial and Education Outreach Project
The Geospatial and Education Outreach Project is training Mississippi's workforce to become more organized and efficient. GEO's value is realized in various applications by different business entities and government organizations. For instance logistic employees use geographical information systems to plan optimal delivery routes; insurance assessors use GIS to measure risk and vulnerability; emergency personal use it to share street name/location and building floor plans with first responders; farmers use it to improve their yield per bushel of grain; and the business industry uses it to offer consumers optimal service. Since 2006 more than 3,000 Mississippians have participated in over 300 workshops across the state.
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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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Health and Productivity of Louisiana Salt Marshes
This study will allow the identification of hotspots of marsh degradation in Louisiana by evaluating marsh biophysical characteristics including distribution of chlorophyll content, green leaf area and green marsh canopy cover. This assessment of marsh health and productivity is due to the Deepwater Horizon oil spill. NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images will be used to retrieve and map these characteristics across the coastal Louisiana salt marshes before and after the spill. The maps and tools produced from the study will be helpful to coastal managers across Louisiana as they evaluate and prioritize the marsh restoration effort which will take place due to the oil spill. Tangible map products will be generated for the first time that can quantitatively assess the effect of the restoration activities and speed of marsh ecosystem recovery.
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Hurricane Debris Model
Based on GRI's researcher's experiences in dealing with Hurricane Katrina and other natural and man-made disasters, researchers have developed a plan for applications of geospatial technologies to disaster response and recovery, dealing primarily with data flow to and from emergency management personnel, especially for hurricane response.
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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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Levee Evaluation through Remote Sensing
GRI researchers are developing a means to use remote sensing to determine the strength of river levees through the utilization of airborne synthetic aperture radar for levee condition assessment and develop classification software. The team has set out to develop new methods and software to improve knowledge of levee conditions and help levee managers prioritize their efforts to inspect, test and repair levees.
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Linking Cultural, Biological and Economic Values into Wetland Programs: Mississippi Band of Choctaw Indians' Pearl River Wetland Demonstration Project
This project aims to develop procedures for more reliably regenerating rivercane and for planting potential restoration sites in the Coastal Plain, and for maintenance of stands for cultural use by native peoples. We are assessing ecological factors associated with the establishment and maintenance of rivercane stands, developing methods for vegetative propagation of rivercane from rhizome segments, and attempting to transfer our findings directly to the Choctaw and other American Indian groups through local and regional symposia, workshops, and field days.
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Naval Coastal Ocean Model (NCOM)/Hybrid Coordinate Ocean Model (HYCOM)
NOAA's Office of Oceanic and Atmospheric Research entrusted GRI to study two versions for each of these models- their global and Gulf of Mexico adaptations. Data was analyzed from instruments tethered to floating and moored buoys, as well as unmanned gliders that look like miniature submarines. The goal was to determine the accuracy of the four model forecasts, as well as their ranking with respect to each other.
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New Data Compression Process
GRI is investigating the use of a new type of dimensionality reduction and data compression for principal component analysis. GRI researchers have developed a process to shift the computational burden to a base-station decoder. This process is called compressive-projection PCA or CPPCA. CPPCA dramatically departs from traditional PCA because it allows its dimensionality-reduction and compression performance to be realized with a system that puts computational burden on the decoder. Continued development of the process could help the conservation, protection, utilization and enhancement of natural resources in the rural South.
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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 Variation and Temporal Trend of Water Quality
NGI conducted ground truth observations and standardize algorithms to produce and evaluate the spatial and temporal variations of water quality parameters in the Northern Gulf of Mexico (NGOM). The effort is aimed at improving the monitoring of the NGOM ecosystem based on remote sensing and understanding the dynamics of harmful algae blooms in the region.
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The Mississippi Digital Earth Model
The Mississippi Digital Earth Model (MDEM) is composed of seven framework layers as defined by the Federal Geographic Data Community's National Spatial Data Infrastructure. Data for the MDEM is acquired and managed through joint operations between the Mississippi Department of Environmental Quality and the Mississippi Department of Information Technology Services.
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Tools for Enhanced Mapping and Managing Post-Disaster Debris
The overall objective of this research effort is to enhance recovery from and resilience to large scale disasters by providing Mississippi state agency personnel, as well as Mississippi local governments with tools to enhance their ability to manage disaster related debris. The research in this proposal will be carried out in four general thrust areas: 1) Use of Remote Sensing Data to Enhance Effectiveness of Debris Management, 2) Evaluation of an Alternative Treatment Technology for Selected Waste Streams, 3) Development of a Preliminary Debris Disposal Cost Projection Model and 4) Filling in Technical Data Gaps for Debris Management.
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UAS with MicroSense RedEdge Payload Help Monitor and Manage Forest Resortation
Unmanned Aerial Systems (UAS) carry a multispectral senor that produce images that provides biologist and geographic information system specialists with changes in the woodlands and vegetation in almost real time. These systems also show the density and regrowth of woodland, marsh, and coastal areas. Mississippi State University’s Geosystems Research Institute is assisting the Grand Bay National Estuarine Research Reserve (GBNERR) and the U.S. Forestry Service with surveying the 4,200 acres that were burned during a large wildfire that reaches from southeast Jackson County into Alabama. These experts utilized the Altavian Nova Block III to inspect the area from 1,000 feet, and they deployed the MicaSense RedEdge. The MicaSense RedEdge has the ability to sense energy at five different wavelengths. Two of the five wavelengths exceed our vision in the Near Infrared Region (NIR) of the electromagnetic spectrum. The senor provides researchers with accurate data that projects the status of vegetation and stress of areas within the ecosystem. With this knowledge, researchers and specialists can aid in the revegetation of the burned woodlands and marsh of the GBNERR, the Grand Bay National Wildlife Refuge and neighboring lands.
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Unmanned Aerial Systems
GRI scientists are researching the effective use of unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USV's) commonly referred to as drones, in how they can be used safely to assess crops, evaluate woodlands, conduct wildlife surveys, gauge river flow and monitor the Gulf of Mexico environmental health and watershed, as well as helping NOAA increase the accuracy of severe weather forecasts. These unmanned aerial and surface/water systems use remote sensing, global positioning--and geographic information systems to collect and analyze sites specific data that farmers, foresters, wildlife rangers, oceanographers and marine scientists can use to create and apply effective prescriptions for every inch of an agricultural field, ocean, river, forest and wildlife management areas.
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Weather Research and Forecasting Modeling System
This research includes assimilation of NEXRAD radial winds in a regional mesoscale model and the use of Lagrangian models to estimate the transport and dispersion of gasses/particles over the Southeastern United States. It is our plan to provide daily plume (smoke) forecast information, as well as atmospheric wind and other conditions over the Gulf coast. Therefore, the information can be used to assess how the smoke due to burning oil over the Gulf of Mexico propagates in time.
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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