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

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Method We explored the plots and tracks data structure using the TDV application to illustrate the data fields that are saved for each scan of the radar, including those fields that would be required as input to a GIS. We exported selected tracks in the kml format, which is a widely used language that links target data to its corresponding location in earth coordinates so the data can be represented in 2- or 3-dimensions in a GIS application. Finally, we viewed some of these data in a 3-dimensional earth browser. Results The DRP saves GIS-relevant data in every track update. The relevant data fields can be extracted from plots and tracks data files or from the RDS database. Once extracted, the data can be exported in kml, a widely used open-source GIS format. The extraction process can be done in real time or by post-processing archived data. The following are three examples of extracting geospatial data from plots and tracks data and using a GIS to display these data. Real-Time Data to a GIS We demonstrated the near real-time extraction of GIS data in Performance Criterion SD2.1 (Section 6.4.1.2). In the present demonstration, we extracted and wrote target data to kml, and served the data from the RDS, all in real time. We then used Google Earth to view the live target data (served from the RDS) from all three SEA radars simultaneously - see Figure 6-75. To distinguish between the different feeds from the three radars, we configured Google Earth to color-code the targets and the corresponding timestamps from each radar. Figure 6-75. Live feed from three radars at SEA, as viewed in Google Earth. 184
Archived Data to a GIS We used the TDV application to illustrate extracting GIS data from archived data. The TDV can extract and display the following information from any set of plots and tracks files: date, track ID, scan time, number of updates, latitude, longitude, speed, heading, height, RCS, intensity, range, azimuth. [Section 6.1.1.2 provides a more detailed description of the information available from the plots and tracks data files using the TDV application.] Once a user selects an individual track, s/he can export the track data to the kml format and view them with 3- dimensional earth browser (e.g., Google Earth); Figure 6-76 is an example of such a display. Figure 6-76. An individual track exported to kml format and viewed in Google Earth. Track Histories to a GIS A third method to extract GIS data from real-time or archived target data is to use the TVW application to generate track histories. As described in PB5.2 (Section 6.2.2.5), a track history provides a spatial distribution of bird activity over any user-defined period of time. Histories can be saved in kml format for viewing in a 3-dimensional earth browser such as Google Earth, as illustrated in Figure 6-77: 185
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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,
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EXECUTIVE SUMMARY Military bases an
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database and redistributed to other
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1 INTRODUCTION 1.1 BACKGROUND Encro
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A seventh objective, the Functional
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Table 1-1 (cont.). IVAR TASK/ OBJEC
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environmental stewardship with miss
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2 TECHNOLOGY/METHODOLOGY DESCRIPTIO
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The original BirdRad system was des
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2.4 TECHNOLOGY/METHODOLOGY DEVELOPM
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Figure 2-2. Configuration of BirdRa
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2.4.3 eBirdRad - Digital Radars wit
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Figure 2-5. Interior view of the eB
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accuracy and target continuity over
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permanently installed at SEA. Prior
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2.5 ADVANTAGES AND LIMITATIONS OF T
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3 PERFORMANCE OBJECTIVES Table 3-1
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Table 3-1 (cont.). Performance Obje
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For the third test, Validation Usin
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temporal domain by recording all bi
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3.1.2.2.7 Provides Bird Abundance o
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difference in the time (i.e., the l
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3.1.6.2.4 Maintenance [SE4.2] We es
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Table 4-1. Summary of the IVAR stud
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4.1 MCAS CHERRY POINT Marine Corps
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2006 the primary eBirdRad unit from
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(directional WiFi) to the Internet.
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• Large (several thousand) flocks
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location for demonstrating the capa
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5.1 CONCEPTUAL TEST DESIGN 5 TEST D
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5.3 DESIGN AND LAYOUT OF TECHNOLOGY
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Assuming these lines evidence confi
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that dataset [Section 6.5.1.3]. 5.5
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6 PERFORMANCE ASSESSMENT The Perfor
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ecord the time, Track ID, and other
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Figure 6-1. Percentage of targets c
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Comparing the performance of dish v
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Figure 6-4. The basic sensor elemen
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Figure 6-6. The polygon around the
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Figure 6-8. Diagram of sampling “
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• It takes several scans (nominal
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Session Correla tions 600 500 y = 1
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To evaluate the capabilities of the
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Figure 6-15. Runway 3 at SEA, showi
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comparisons between the RCH-GPS dat
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Figure 6-18. Plot of the northing c
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Figure 6-20. Plot of the easting co
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Conclusion In the quantitative perf
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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
Page 157 and 158: Figure 6-42. eBirdRad display based
Page 159 and 160: Figure 6-44. A partial history of t
Page 161 and 162: 6.2 SAMPLING PROTOCOL 6.2.1 Quantit
Page 163 and 164: Figure 6-46. Image from the track h
Page 165 and 166: Table 6-14. Dates, times and names
Page 167 and 168: Figure 6-48. Fifteen-minute (06:04-
Page 169 and 170: Figure 6-50. Fifteen-minute (02:24-
Page 171 and 172: We used a TVW to process the plots
Page 173 and 174: Figure 6-53. In an example of night
Page 175 and 176: 6.2.1.4 Efficiently Stores Bird Tra
Page 177 and 178: Figure 6-56 shows sites 13-24 in th
Page 179 and 180: We extracted the radar data for thi
Page 181 and 182: Figure 6-57. Digital image of the d
Page 183 and 184: Table 6-17. Altitudinal distributio
Page 185 and 186: hours apart, showed considerable va
Page 187 and 188: • The sampling event time period
Page 189 and 190: underwent a 4-minute initialization
Page 191 and 192: Figure 6-62. DRP Live application l
Page 193 and 194: commands we issued to the radar; th
Page 195 and 196: 4. Range Decrease (x7) 5. Range Inc
Page 197 and 198: Figure 6-65, Figure 6-66, and Figur
Page 199 and 200: 6.2.2.4 Provides Spatial Distributi
Page 201 and 202: Figure 6-69. A plot of all track ac
Page 203 and 204: Figure 6-71. Twelve 2-hour historie
Page 205 and 206: Figure 6-72. TVW application displa
Page 207: Conclusion Figure 6-74. Oblique vie
Page 211 and 212: (SQL). Extracting target data from
Page 213 and 214: Figure 6-78. Daily, unfiltered, tra
Page 215 and 216: Figure 6-79. Time periods selected
Page 217 and 218: Figure 6-82. Hourly track count ove
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Page 221 and 222: As can be seen in Figure 6-83, the
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Page 225 and 226: Conclusion We have successfully dem
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Page 229 and 230: All reference times were recorded i
Page 231 and 232: Description of Remote Display - As
Page 233 and 234: mounted laptop computer (Figure 6-8
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Page 239 and 240: Figure 6-90. Alarm status pane and
Page 241 and 242: Figure 6-92. Alarm triggered as a f
Page 243 and 244: Figure 6-95. Screen capture of the
Page 245 and 246: Figure 6-96. An example from a data
Page 247 and 248: Table 6-29. Differences found betwe
Page 249 and 250: 6.4 DATA INTEGRATION 6.4.1 Quantita
Page 251 and 252: Figure 6-100. Screen captures for S
Page 253 and 254: We used a screen-capture program at
Page 255 and 256: Results Table 6-32 records the time
Page 257 and 258: 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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