(IVAR) - Final Report - Strategic Environmental Research and ...

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Table 4-1 (cont.). Demonstrations Location Visual Confirmation Thermal Validation UAV Studies Sampling Protocols Data Streaming Data Integration Data Fusion Activity SEATAC Int’l Airport, Washington Edisto Island (Clemson), South Carolina ARTI Ontario, Canada X X X X X X X B B B X X X Moderate-size airport; bird activity; moderate-to-heavy air operations; Multiple radars; wired & wireless (WiFi) LAN & WAN. High seasonal and daily bird activity; no air operations; single radar (eBirdRad); thermal imager; wired & wireless LAN (WiFi). WAN (DSL). Moderate bird activity; endpoint for streamed data, data management, and data fusion tools; main backup site; multiple radars (eBirdRad & AR1); wired & wireless (WiFi) LAN & WAN; RDS. 47
4.1 MCAS CHERRY POINT Marine Corps Air Station, Cherry Point (MCASCP; 34°54'11.19"N, 76°53'16.20"W; Figure 4-2) is located along the coastal plain in Craven County, North Carolina, near the town of Havelock. MCASCP is roughly 90 miles (145 km) west-southwest of Cape Hatteras at the foot of the great Outer Banks. With an area of 5330 ha on the air station proper, MCASCP is the world's largest Marine Corps Air Station. It is home to the 2 nd Marine Aircraft Wing and to Marine Air Group 14, the primary East Coast operating unit for the Marine Corps AV-8B Harrier (four squadrons) and EA-6B Prowler (four squadrons). The Air Station also host to four squadrons of KC-130 tankers and an Unmanned Aerial Vehicle (UAV) squadron. Figure 4-2. MCAS Cherry Point, North Carolina, showing the location of the eBirdRad radar (RT-1) and the visual team (VT) observation sites used in the spring 2007 (’07) and fall 2008 (’08) studies. We selected MCASCP as an IVAR study location because it is a large air station and it had two operational eBirdRad units that were being used to fulfill multiple research objectives. It was being used there to monitor waterfowl movements in the vicinity of the airfield and had been used to detect two previously unrecorded patterns of movements near dawn of large flocks of waterfowl and Double-crested Cormorants. The USDA/WS staff at MCASCP was also using the radar to observe known Wood Duck roosting areas during morning departure flights from the roost and to monitor waterfowl movements on the Neuse River during the winter months. In addition, the USDA/WS staff was comparing the data collected by visual observers during their 48
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FINAL REPORT Integration and Valida
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Table of Contents List of Tables ..
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APPENDIX A. POINTS OF CONTACT .....
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Table 6-17. Altitudinal distributio
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List of Figures Figure 2-1. Chronol
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Figure 6-17. Plot of the northing c
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Figure 6-42. eBirdRad display based
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Figure 6-82. Hourly track count ove
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Figure 6-115: COP display showing f
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List of Acronyms Acronym AGL AIP AR
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Acronym RST RT SEA SQL SSC Pacific
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Carmen Lombardo Naval Air Station,
Page 25 and 26: EXECUTIVE SUMMARY Military bases an
Page 27 and 28: database and redistributed to other
Page 29 and 30: 1 INTRODUCTION 1.1 BACKGROUND Encro
Page 31 and 32: A seventh objective, the Functional
Page 33 and 34: Table 1-1 (cont.). IVAR TASK/ OBJEC
Page 35 and 36: environmental stewardship with miss
Page 37 and 38: 2 TECHNOLOGY/METHODOLOGY DESCRIPTIO
Page 39 and 40: The original BirdRad system was des
Page 41 and 42: 2.4 TECHNOLOGY/METHODOLOGY DEVELOPM
Page 43 and 44: Figure 2-2. Configuration of BirdRa
Page 45 and 46: 2.4.3 eBirdRad - Digital Radars wit
Page 47 and 48: Figure 2-5. Interior view of the eB
Page 49 and 50: accuracy and target continuity over
Page 51 and 52: permanently installed at SEA. Prior
Page 53 and 54: 2.5 ADVANTAGES AND LIMITATIONS OF T
Page 55 and 56: 3 PERFORMANCE OBJECTIVES Table 3-1
Page 57 and 58: Table 3-1 (cont.). Performance Obje
Page 65 and 66: For the third test, Validation Usin
Page 67 and 68: temporal domain by recording all bi
Page 69 and 70: 3.1.2.2.7 Provides Bird Abundance o
Page 71 and 72: difference in the time (i.e., the l
Page 73 and 74: 3.1.6.2.4 Maintenance [SE4.2] We es
Page 75: Table 4-1. Summary of the IVAR stud
Page 79 and 80: 2006 the primary eBirdRad unit from
Page 81 and 82: (directional WiFi) to the Internet.
Page 83 and 84: • Large (several thousand) flocks
Page 85 and 86: location for demonstrating the capa
Page 87 and 88: 5.1 CONCEPTUAL TEST DESIGN 5 TEST D
Page 89 and 90: 5.3 DESIGN AND LAYOUT OF TECHNOLOGY
Page 91 and 92: Assuming these lines evidence confi
Page 93 and 94: that dataset [Section 6.5.1.3]. 5.5
Page 95 and 96: 6 PERFORMANCE ASSESSMENT The Perfor
Page 97 and 98: ecord the time, Track ID, and other
Page 99 and 100: Figure 6-1. Percentage of targets c
Page 101 and 102: Comparing the performance of dish v
Page 103 and 104: Figure 6-4. The basic sensor elemen
Page 105 and 106: Figure 6-6. The polygon around the
Page 107 and 108: Figure 6-8. Diagram of sampling “
Page 109 and 110: • It takes several scans (nominal
Page 111 and 112: Session Correla tions 600 500 y = 1
Page 113 and 114: To evaluate the capabilities of the
Page 115 and 116: Figure 6-15. Runway 3 at SEA, showi
Page 117 and 118: comparisons between the RCH-GPS dat
Page 119 and 120: Figure 6-18. Plot of the northing c
Page 121 and 122: Figure 6-20. Plot of the easting co
Page 123 and 124: Conclusion In the quantitative perf
Page 125 and 126: Table 6-8. Column headings of the T
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Table 6-9 demonstrates quantitative
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Table 6-10. The parameters of targe
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Table 6-11. The position of Visual
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Table 6-12. Solitary targets at MCA
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Figure 6-23. The track of target T2
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intended to demonstrate these syste
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Figure 6-34. Screen capture of bird
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6.1.2 Qualitative Performance Crite
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upper right have completely converg
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Figure 6-38. The progression of the
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The slight difference in alignment
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Figure 6-42. eBirdRad display based
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Figure 6-44. A partial history of t
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6.2 SAMPLING PROTOCOL 6.2.1 Quantit
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Figure 6-46. Image from the track h
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Table 6-14. Dates, times and names
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Figure 6-48. Fifteen-minute (06:04-
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Figure 6-50. Fifteen-minute (02:24-
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We used a TVW to process the plots
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Figure 6-53. In an example of night
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6.2.1.4 Efficiently Stores Bird Tra
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Figure 6-56 shows sites 13-24 in th
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We extracted the radar data for thi
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Figure 6-57. Digital image of the d
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Table 6-17. Altitudinal distributio
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hours apart, showed considerable va
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• The sampling event time period
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underwent a 4-minute initialization
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Figure 6-62. DRP Live application l
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commands we issued to the radar; th
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4. Range Decrease (x7) 5. Range Inc
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Figure 6-65, Figure 6-66, and Figur
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6.2.2.4 Provides Spatial Distributi
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Figure 6-69. A plot of all track ac
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Figure 6-71. Twelve 2-hour historie
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Figure 6-72. TVW application displa
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Conclusion Figure 6-74. Oblique vie
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Archived Data to a GIS We used the
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(SQL). Extracting target data from
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Figure 6-78. Daily, unfiltered, tra
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Figure 6-79. Time periods selected
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Figure 6-82. Hourly track count ove
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esults are displayed in Figure 6-83
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As can be seen in Figure 6-83, the
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Figure 6-84 clearly demonstrates th
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Conclusion We have successfully dem
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LAN within a facility to the operat
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All reference times were recorded i
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Description of Remote Display - As
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mounted laptop computer (Figure 6-8
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very good because the system was sa
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operations personnel or their contr
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Figure 6-90. Alarm status pane and
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Figure 6-92. Alarm triggered as a f
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Figure 6-95. Screen capture of the
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Figure 6-96. An example from a data
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Table 6-29. Differences found betwe
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6.4 DATA INTEGRATION 6.4.1 Quantita
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Figure 6-100. Screen captures for S
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We used a screen-capture program at
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Results Table 6-32 records the time
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We acquired the appropriate plots a
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Figure 6-105. Track histories of ta
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synchronized, both spatially and te
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0.004687 seconds ahead of the NTP t
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Figure 6-108: COP display showing f
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Figure 6-110: TVW display showing t
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The next example from NASWI involve
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Figure 6-114: TVW display showing t
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Figure 6-116: COP display showing a
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Fusion processing was enabled in th
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processing associated with this dat
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Figure 6-122: Track IDs shown for b
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Conclusion We successfully demonstr
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Of course, many other factors contr
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one, Jim Swift, had been exposed to
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Methods The US military 27 designat
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Natural R.esoan:es Br.mch 22541Jolm
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Given these considerations, the IVA
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Results No maintenance was required
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acquired and is testing JRC S-band
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areas of overlap. Data fusion algor
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6.8 FUNCTIONAL REQUIREMENTS AND PER
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Table 7-1. Cost Model for a Standal
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additional processors account of th
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Installation Site Assessment - Rada
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e incurred, depending on what infor
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eal time, avian radars and can dete
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Network Connectivity. The US Depart
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Airport Improvement Program (AIP) f
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9 REFERENCES Anderson, C., and S. O
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APPENDIX A. POINTS OF CONTACT POINT
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POINT OF CONTACT Name Ryan King Mat
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APPENDIX B. ANALYTICAL METHODS SUPP
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METHOD #2: VALIDATION BY IMAGE COMP
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The pattern of yellows and blues in
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Radar Team (RT) Site Selection Sinc
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will measured the magnetic bearing
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Figure B-6. Using a GPS to record s
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• Visual Observer - observes bird
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Figure B-9. Flowchart of target con
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VT: “Radar, Team 2-Alpha copies T
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eam and the VTs have difficulty loc
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why it was changed, who made the ch
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METHOD #4: CONFIRMATION OF BIRD TAR
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Figure B-12. Duplexed image showing
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Table B-2. Dates, times, and antenn
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For the analysis of the simultaneou
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Table B-3. Altitude of the radar be
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Figure B-17. Diagram of sampling
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METHOD #6: DEMONSTRATING REAL-TIME
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APPENDIX C. DATA QUALITY ASSURANCE/
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APPENDIX D. SUPPORTING DATA D.1 Par
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Table D-1 (cont.). Date Track ID Up
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D.2 Listing of One-Hour Track Histo
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Table D-2 (cont.). 07:00-08:00 WI_A
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APPENDIX E. SURVEY OF AIRPORT PERSO
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used as the real-time target becaus
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Table E-1. Remote radar display lat
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7. Please rate the following where
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