Attribution Concepts for Sub-meter Resolution Ground Physics Models

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Attribution Concepts for Sub-meter Resolution Ground Physics Models 76 th MORS Symposium US Coast Guard Academy Approved for public release distribution. 2

Report Documentation Page Form Approved OMB No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE 01 JUN 2008 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE Attribution Concepts for Sub-meter Resolution Ground Physics Models 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) US Coast Guard Academy 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR S ACRONYM(S) 12. DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release, distribution unlimited 11. SPONSOR/MONITOR S REPORT NUMBER(S) 13. SUPPLEMENTARY NOTES See also ADM202527. Military Operations Research Society Symposium (76th) Held in New London, Connecticut on June 10-12, 2008, The original document contains color images. 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU a. REPORT unclassified b. ABSTRACT unclassified c. THIS PAGE unclassified 18. NUMBER OF PAGES 20 19a. NAME OF RESPONSIBLE PERSON Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18

Focus for ERDC R&D In Military Engineering Adaptive Maneuver and Protection Developing Solutions Faster Than The Threat Can Adapt First-Principles Phenomenology Emerging Materials Multi-Scale Physics Collaborators - Stakeholders - Partners Academia Warfighters Multi-Use Integrated Materiel Solutions Engineer Assessments Phenomenological Understanding Government Labs Industry Protection Maneuver Integrated Adaptive Warfighter Solutions Adaptive Protection Scalable Weapons Effects Near Surface Computational Testbed Austere Entry and Maneuver Near Surface Physics Experimental Characterization & Validation Multi-Scale Modeling Scene Generation High Performance Computational Testbeds 3

Virtual Autonomous Navigation Environment (VANE) Scene Generation Models Colors, Stereo Images, Geology, Vegetation, Material Databases Component Models Vehicle Dynamics, Sensor, Power Requirements Controlled, Repeatable Statistically Significant Performance Evaluations of Sensors and UMS Missions Sensor Designs and Evaluations of Autonomous Tactical Behaviors Global and Local Data Fusion Environment For Local Sensor Perception Autonomous Tactical Behavior Evaluations Accurate Local Sensor Evaluations Vegetation Models Thermal, Geometry, Reflectivity, Ray Casting Soil Models Strengths, Moistures, Thermal, Electromagnetics 4

Global Databases Supporting Geospatial Attribution Historic Soils Dataset TR-08-2 14000 Records From 10 TR s Physical Properties of Soils, Location, Attribution Consistent with CTB Inputs 5

Geostatistical Data Needs How to Define Rocks within Strata Layering and Variance in Layers What are the Input Data correlations Correlations with Time and Distance 6

Spatial Distribution of Rocks In Soil Mass Y distance (cm ) 450 400 350 300 250 200 150 100 50 Rocks are extracted and Highlighted in Red 0 0 100 200 300 400 500 600 X distance (cm) 7

Spatial Distribution of Rocks In Soil Mass γ ( h) =.8324(1 e 2 h.0924 ) 8

Spatial Distribution of Rocks In Soil Mass 0 X distance (cm) 0 100 200 300 400 500 600 50 100 Y distance (cm) 150 200 250 300 350 400 450 500 Vertical Locations of Rocks Are Extracted in the Same Manner 9

Spatial Distribution of Rocks In Soil Mass Program to define distribution from digital photographs Number of Rocks Size Location Orientation 10

Spatial Distribution of Moisture, Density, and Porosity in Soil Mass Low Moisture indicates Changes whose Spatial Structure is Random However Density Variations were predictable Density Kg/m^3 3 1440 1420 1400 2 1380 1360 1340 1320 1 1300 1280 1260 0 0 1 2 3 4 5 6 7 8 9 10 11 11 1240

High Resolution Data 0.20 0.18 0.16 Measured Predicted Read Field Data Generate Matching SemiVariagram and Frequency For High Resolution Grid 0.14 0.12 0.10 0.08 0.06 0.04 0.02 0.00 0.45 0.46 0.47 0.48 0.49 0.49 0.50 0.51 0.52 0.53 Probability of State Change When Starting with State 1 Create Transitional Probability Matrix Generate Multiple Realizations 2.2 2 1.8 1.4 1.2 Lag Distance 1 0.8 0.6 0.4 0.2 0% 20% 40% 60% 80% 100% 1 to 1 1 to 2 1 to 3 1 to 4 1 to 5 1 to 6 1 to 7 1 to 8 1 to 9 1 to 10 12

Correlations for Missing Data 13

Layering Effect in Density and Porosity 3 1440 1420 1400 2 1 1380 1360 1340 1320 1300 1280 1260 0 0 1 2 3 4 5 6 7 8 9 10 11 12 1240 14

Summary ERDC research is now heavily focused on using high performance computing simulation testbeds Simulations like VANE involving sensor-terrain interaction will require relevant and realistically heterogeneous attributions for large scale, high resolution, numerical models Techniques for characterizing spatial variability at multiple scales including sub-meter resolutions Techniques for populating sparsely measured attributions using material attribute correlations to densely measured attributions 15

BACKUP SLIDES BACKUP SLIDES 16

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8 7 6 Variance (%) 5 4 3 2 1 0 0 0.5 1 1.5 2 2.5 Lag Distance BACKUP SLIDES 18

The Generation of Moisture & Density for Subsurface Changes. Low Moisture indicates Changes whose Spatial Structure is Random Density & Porosity Increase with Depth BACKUP SLIDES 19

BACKUP SLIDES 20

Initial Soil Moisture From LSM and Satellites BACKUP SLIDES 21