1. Cyber-Infrastructure for Agro-Threats Steve Goddard Computer Science & Engineering University of Nebraska-Lincoln

2. Background In addition to the “normal” threats from natural hazards, today we must worry about deliberate attacks on our agricultural infrastructure, communities or economy In addition to the “normal” threats from natural hazards, today we must worry about deliberate attacks on our agricultural infrastructure, communities or economy Agro-terrorism becomes a new risk that must be evaluated by decision makers Agro-terrorism becomes a new risk that must be evaluated by decision makers UNL scientists have already developed many of the models needed to answer questions related to the risk of certain agro-events occurring UNL scientists have already developed many of the models needed to answer questions related to the risk of certain agro-events occurring Much of the crop land cover, and agricultural census information is already available Much of the crop land cover, and agricultural census information is already available A cyber-infrastructure building on this data and existing systems is needed to integrate the tools and data to identify agro-threats A cyber-infrastructure building on this data and existing systems is needed to integrate the tools and data to identify agro-threats

3. Our Mission To develop a decision support system of geospatial analyses to enhance risk assessment To develop a decision support system of geospatial analyses to enhance risk assessment Our initial research in drought risk and exposure analysis allows us to: Our initial research in drought risk and exposure analysis allows us to: Compute and map drought indices at increased spatial and temporal resolutions Compute and map drought indices at increased spatial and temporal resolutions Provide transparent access to distributed geospatial, and relational databases Provide transparent access to distributed geospatial, and relational databases Provide new algorithms (using data mining and knowledge discovery techniques) that seek out patterns between ENSO events and droughts or crop yields Provide new algorithms (using data mining and knowledge discovery techniques) that seek out patterns between ENSO events and droughts or crop yields Develop new geospatial analyses to better visualize the emergence, evolution, and movement of drought Develop new geospatial analyses to better visualize the emergence, evolution, and movement of drought

4. Current Tools Our current tools apply risk analysis methodologies to the study of drought Integration of basic models with data generates “information” for analysis by decision makers Information can be gathered at any resolution for which we have data http://nadss.unl.edu

5. Layered Architecture HTTP IIOP RMI TCP Data cache Distributed Spatial and Relational Data e.g., Climatic Variables, Agricultural Statistics HTTP IIOP RMI TCP Presentation (User Interface) e.g., Web Interface, Java applet Knowledge Layer e.g., Exposure Analysis, Risk Assessment Data cache Knowledge Layer e.g., Data Mining, Exposure Analysis, Risk Assessment Data cache Distributed Spatial and Relational Data e.g., Climatic Variables, Agricultural Statistics Data cache e.g., Drought Indices, Regional Crop Losses Information Layer Data cache e.g., Drought Indices, Regional Crop Losses Information Layer

6. Building a Spatial View Data from information and knowledge layers are translated spatially and interpolated to provide a “risk view” for a defined area Data from information and knowledge layers are translated spatially and interpolated to provide a “risk view” for a defined area Risk Indicators Drought Indices Soil Data Climate Data Reported Yields Surfacing Raster interpolation of data points within various windows Inverse Distance Weighting Spline Kriging Display Re-summarization of raster data Generation of displayable images

7. Building a Spatial View Spatial data from information and knowledge layers can be combined with various overlays to create unique views of data Spatial data from information and knowledge layers can be combined with various overlays to create unique views of data

8. Risk Assessment in Practice By combining several domain specific factors from our “information layer” we are able to create maps displaying the risk of crop failure for states, regions or counties By combining several domain specific factors from our “information layer” we are able to create maps displaying the risk of crop failure for states, regions or counties The user adjusts weight factors for each variable The risk calculator combines the variables The result is a “spatial” view of risk

9. Risk Assessment Applications By combining “information” from different sources we create “knowledge” By combining “information” from different sources we create “knowledge” Total Market Value Dairy FarmsBeef Farms We can project potential impacts for decision makers at various levels We can project potential impacts for decision makers at various levels State, county, farm an even field level projections State, county, farm an even field level projections

10. Benefits and Impacts Improving spatial and temporal analysis for risk management Improving spatial and temporal analysis for risk management State level to County level to Field level State level to County level to Field level Responding to risk events more effectively Responding to risk events more effectively Predict risk levels for areas early Predict risk levels for areas early Predict the effects of the occurrence of a risk event Predict the effects of the occurrence of a risk event Application of our risk analysis research can provide the same benefits to various domains, including assessment of agro-threats Application of our risk analysis research can provide the same benefits to various domains, including assessment of agro-threats

11. Conclusion A cyber-infrastructure for risk analysis can provide experts and non-experts alike access to tools to evaluate the risk and impact of an event in real-time A cyber-infrastructure for risk analysis can provide experts and non-experts alike access to tools to evaluate the risk and impact of an event in real-time Moving forward we hope to apply our expertise to other agriculture risk factors including analysis of agro-terrorism Moving forward we hope to apply our expertise to other agriculture risk factors including analysis of agro-terrorism Tools can be developed to help identify “safe islands” -- locations that may be naturally protected from the factors contributing to risk Tools can be developed to help identify “safe islands” -- locations that may be naturally protected from the factors contributing to risk Identified regions could then be used to grow crops if major growing regions are compromised Identified regions could then be used to grow crops if major growing regions are compromised