add occurance data

#5
by jennamk14 - opened
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Files changed (50) hide show
  1. README.md +59 -35
  2. data/occurrences/11_01_23-DJI_0977.csv +0 -3
  3. data/occurrences/11_01_23-DJI_0978.csv +0 -3
  4. data/occurrences/11_01_23-DJI_0979.csv +0 -3
  5. data/occurrences/11_01_23-DJI_0980.csv +0 -3
  6. data/occurrences/12_01_23-DJI_0001.csv +0 -3
  7. data/occurrences/12_01_23-DJI_0002.csv +0 -3
  8. data/occurrences/12_01_23-DJI_0003.csv +0 -3
  9. data/occurrences/12_01_23-DJI_0006.csv +0 -3
  10. data/occurrences/12_01_23-DJI_0007.csv +0 -3
  11. data/occurrences/12_01_23-DJI_0008.csv +0 -3
  12. data/occurrences/12_01_23-DJI_0987.csv +0 -3
  13. data/occurrences/12_01_23-DJI_0988.csv +0 -3
  14. data/occurrences/12_01_23-DJI_0989.csv +0 -3
  15. data/occurrences/12_01_23-DJI_0992.csv +0 -3
  16. data/occurrences/12_01_23-DJI_0994.csv +0 -3
  17. data/occurrences/12_01_23-DJI_0997.csv +0 -3
  18. data/occurrences/12_01_23-DJI_0998.csv +0 -3
  19. data/occurrences/13_01_23-DJI_0009.csv +0 -3
  20. data/occurrences/13_01_23-DJI_0011.csv +0 -3
  21. data/occurrences/13_01_23-DJI_0012.csv +0 -3
  22. data/occurrences/13_01_23-DJI_0013.csv +0 -3
  23. data/occurrences/13_01_23-DJI_0015.csv +0 -3
  24. data/occurrences/13_01_23-DJI_0016.csv +0 -3
  25. data/occurrences/13_01_23-DJI_0018.csv +0 -3
  26. data/occurrences/13_01_23-DJI_0019.csv +0 -3
  27. data/occurrences/13_01_23-DJI_0020.csv +0 -3
  28. data/occurrences/13_01_23-DJI_0021.csv +0 -3
  29. data/occurrences/13_01_23-DJI_0022.csv +0 -3
  30. data/occurrences/13_01_23-DJI_0023.csv +0 -3
  31. data/occurrences/13_01_23-DJI_0024.csv +0 -3
  32. data/occurrences/13_01_23-DJI_0029.csv +0 -3
  33. data/occurrences/13_01_23-DJI_0031.csv +0 -3
  34. data/occurrences/13_01_23-DJI_0032.csv +0 -3
  35. data/occurrences/13_01_23-DJI_0033.csv +0 -3
  36. data/occurrences/13_01_23-DJI_0035.csv +0 -3
  37. data/occurrences/13_01_23-DJI_0036.csv +0 -3
  38. data/occurrences/13_01_23-DJI_0037.csv +0 -3
  39. data/occurrences/13_01_23-DJI_0038.csv +0 -3
  40. data/occurrences/13_01_23-DJI_0039.csv +0 -3
  41. data/occurrences/13_01_23-DJI_0040.csv +0 -3
  42. data/occurrences/13_01_23-DJI_0041.csv +0 -3
  43. data/occurrences/13_01_23-DJI_0042.csv +0 -3
  44. data/occurrences/13_01_23-DJI_0043.csv +0 -3
  45. data/occurrences/16_01_23_flight_1-DJI_0001.csv +0 -3
  46. data/occurrences/16_01_23_flight_1-DJI_0002.csv +0 -3
  47. data/occurrences/16_01_23_flight_1-DJI_0003.csv +0 -3
  48. data/occurrences/16_01_23_flight_2-DJI_0001.csv +0 -3
  49. data/occurrences/16_01_23_flight_2-DJI_0002.csv +0 -3
  50. data/occurrences/16_01_23_flight_2-DJI_0003.csv +0 -3
README.md CHANGED
@@ -88,20 +88,20 @@ mission:
88
 
89
  ### Dataset Description
90
 
91
- - **Curated by:** Jenna M. Kline, Elizabeth Campolongo
92
  - **Language(s):** English (metadata and documentation)
93
  - **Homepage:** [KABR Project](https://imageomics.github.io/KABR/)
94
- - **Repository:** [kabr-behavior-telemetry](https://github.com/Imageomics/fair_drones/tree/main/examples/kabr)
95
- - **Paper:** In preparation
96
 
97
- This dataset provides frame-level integration of drone telemetry (GPS position, altitude, camera settings), animal detection bounding boxes, and expert-annotated behaviors from aerial wildlife monitoring in Kenyan savannas. Collected January 11-17, 2023 at Mpala Research Centre, the dataset contains 57 videos with complete occurrence records covering Grevy's zebras (*Equus grevyi*), plains zebras (*Equus quagga*), and reticulated giraffes (*Giraffa reticulata*).
98
 
99
  The dataset was developed to analyze optimal drone flight parameters for wildlife behavior research—correlating altitude, speed, and camera settings with data quality and animal disturbance levels. It implements Darwin Core biodiversity standards with Humboldt Eco extensions for ecological inventory data, ensuring interoperability with biodiversity databases like GBIF.
100
 
101
  Key features:
102
- - **57 complete video occurrence files** with ~10,000-66,000 frames each
103
  - **68 video-level Darwin Core events** with GPS bounds and temporal coverage
104
- - **18 session-level events** aggregating mission-level metadata
105
  - **Frame-synchronized data**: GPS coordinates, camera EXIF, detection boxes, behavior labels
106
  - **Behavior ethogram**: Walking, running, grazing, vigilance, social interactions, and more
107
  - **Multi-species coverage**: Three focal species across diverse habitats
@@ -136,12 +136,12 @@ This dataset supports computer vision, ecological analysis, and autonomous syste
136
  ```
137
  kabr-behavior-telemetry/
138
  ├── data/
139
- │ ├── occurrences/ # Frame-level occurrence records (57 videos)
140
  │ │ ├── 11_01_23-DJI_0977.csv
141
  │ │ ├── 11_01_23-DJI_0978.csv
142
  │ │ └── ...
143
  │ ├── video_events.csv # Darwin Core Event records (68 videos)
144
- │ └── session_events.csv # Darwin Core Event records (18 sessions)
145
  ├── scripts/
146
  │ ├── merge_behavior_telemetry.py # Generate occurrence files
147
  │ ├── update_video_events.py # Add annotation file paths
@@ -353,6 +353,19 @@ The dataset fills a critical gap: while many drone wildlife datasets provide det
353
  - Telemetry parsing: Custom Python scripts
354
  - Data merging: `merge_behavior_telemetry.py` (this repository)
355
 
 
 
 
 
 
 
 
 
 
 
 
 
 
356
  ### Annotations
357
 
358
  #### Annotation Process
@@ -373,8 +386,11 @@ The dataset fills a critical gap: while many drone wildlife datasets provide det
373
  - Uncertain behaviors marked for expert review
374
 
375
  **Quality Control:**
376
- - Training included intensive review of species-specific behavioral definitions with video examples, technical instruction on the CVAT interface, and practice annotation sessions until achieving greater than 90\% agreement with expert annotations
377
- - Weekly calibration sessions throughout the annotation period to address interpretation drift and maintain consistency across all annotators. These included random double-annotation of 10\% of mini-scenes to monitor inter-annotator reliability (achieving $\kappa=0.88$ for primary behavioral categories), weekly calibration sessions to address any annotation drift, and final expert review by field-experienced team members for all completed annotations.
 
 
 
378
 
379
  **Annotation Coverage:**
380
  - Fully annotated: No (not all frames have animals)
@@ -385,9 +401,9 @@ The dataset fills a critical gap: while many drone wildlife datasets provide det
385
  #### Who are the annotators?
386
 
387
  **Annotator Team:**
388
- - Number of annotators: 10, including expert reviewers
389
- - Expertise: Research staff, professors, and students in ecology/computer science with wildlife identification training
390
- - Training provided: 2 hours initial training + ongoing feedback
391
  - Compensation: Academic credit and authorship
392
 
393
  **Subject Matter Experts:**
@@ -483,7 +499,7 @@ The dataset fills a critical gap: while many drone wildlife datasets provide det
483
  **Technical Limitations:**
484
 
485
  - **Image Quality:** Variable due to altitude, lighting, and atmospheric conditions
486
- - **Coverage Gaps:** 11 videos lack occurrence data due to missing/corrupted SRT files or failed processing
487
  - **Annotation Limitations:** Behavior labels are subjective; inter-observer agreement not quantified
488
  - **GPS Accuracy:** ±5-10m typical; may drift during long flights
489
 
@@ -541,9 +557,10 @@ The dataset fills a critical gap: while many drone wildlife datasets provide det
541
 
542
  **Dataset:**
543
  ```bibtex
544
- @misc{kline2024kabr_behavior_telemetry,
545
- author = {Jenna Kline and Maksim Kholiavchenko and Michelle Ramirez and Sam Stevens and Alec Sheets and Reshma Ramesh Babu and
546
- Namrata Banerji and Elizabeth Campolongo and Matthew Thompson Nina Van Tiel and Jackson Miliko and Isla Duporge and Neil Rosser and Eduardo Bessa and Charles Stewart and Tanya Berger-Wolf and Daniel Rubenstein},
 
547
  title = {KABR Behavior Telemetry: Frame-Level Drone Wildlife Monitoring Dataset},
548
  year = {2024},
549
  publisher = {Hugging Face},
@@ -594,20 +611,6 @@ Namrata Banerji (The Ohio State University) - ORCID: 0000-0001-6813-0010
594
  Elizabeth Campolongo (Imageomics Institute, The Ohio State University) - ORCID: 0000-0003-0846-2413
595
  Matthew Thompson (Imageomics Institute, The Ohio State University) - ORCID: 0000-0003-0583-8585
596
  Nina Van Tiel (Eidgenössische Technische Hochschule Zürich) - ORCID: 0000-0001-6393-5629
597
- Daniel Rubenstein (Princeton University) - ORCID: 0000-0002-8285-1233
598
- - **Data Collection Team:**
599
- Jenna M. Kline (The Ohio State University)
600
- Michelle Ramirez (The Ohio State University)
601
- Sam Stevens (The Ohio State University)
602
- Reshma Ramesh Babu (The Ohio State University) - ORCID: 0000-0002-2517-5347
603
- Isla Duporge (The Ohio State University) - ORCID: 0000-0002-9873-1233
604
- Neil Rosser (The Ohio State University) - ORCID: 0000-0002
605
- - **Project Oversight and Guidance:**
606
- Elizabeth Campolongo (Imageomics Institute, The Ohio State University) - ORCID: 0000-0003-0846-2413
607
- Matthew Thompson (Imageomics Institute, The Ohio State University) - ORCID: 0000-0003-0583-858
608
- Tanya Berger-Wolf (Imageomics Institute, The Ohio State University) - ORCID: 0000-0002-1236-4153
609
- Charles Stewart (Rensselaer Polytechnic Institute) - ORCID: 0000-0002-5204-1862
610
- Daniel Rubenstein (Princeton University) - ORCID: 0000-0002-8285-1233
611
 
612
 
613
  **Conservation Partners:**
@@ -615,8 +618,9 @@ Daniel Rubenstein (Princeton University) - ORCID: 0000-0002-8285-1233
615
  - Grevy's Zebra Trust
616
 
617
  **Data Collection Permits:**
618
- The data was gathered at the Mpala Research Centre in Kenya, in accordance with Research License No. NACOSTI/P/22/18214.
619
- The data collection protocol adhered strictly to the guidelines set forth by the Institutional Animal Care and Use Committee under permission No. IACUC 1835F.
 
620
 
621
  ## Validation and Quality Metrics
622
 
@@ -632,7 +636,7 @@ The data collection protocol adhered strictly to the guidelines set forth by the
632
  **🌿 Darwin Core Validation:**
633
 
634
  - [x] Event records complete and valid
635
- - [x] Occurrence records complete and valid (57/68 videos)
636
  - [x] Scientific names validated against GBIF backbone
637
  - [x] Coordinates in WGS84
638
  - [x] Sampling protocol documented
@@ -669,6 +673,26 @@ detections = occurrences.dropna(subset=['xtl', 'ytl', 'xbr', 'ybr'])
669
  behavior_counts = detections.groupby('behaviour').size()
670
  ```
671
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
672
  **Processing Scripts:**
673
 
674
  See `scripts/` directory for:
@@ -693,7 +717,7 @@ See `scripts/` directory for:
693
 
694
  ## Dataset Card Authors
695
 
696
- Jenna M. Kline
697
 
698
  ## Dataset Card Contact
699
 
 
88
 
89
  ### Dataset Description
90
 
91
+ - **Curated by:** Jenna M. Kline, Elizabeth Campolongo, Matt Thompson, Maksim Kholiavchenko, Otto Brookes
92
  - **Language(s):** English (metadata and documentation)
93
  - **Homepage:** [KABR Project](https://imageomics.github.io/KABR/)
94
+ - **Repository:** [kabr-behavior-telemetry](https://github.com/Imageomics/kabr-behavior-telemetry)
95
+ - **Paper:** [Integrating Biological Data into Autonomous Remote Sensing Systems](https://arxiv.org/abs/2407.16864)
96
 
97
+ This dataset provides frame-level integration of drone telemetry (GPS position, altitude, camera settings), animal detection bounding boxes, and expert-annotated behaviors from aerial wildlife monitoring in Kenyan savannas. Collected January 11-17, 2023 at Mpala Research Centre, the dataset contains 47 videos with complete occurrence records covering Grevy's zebras (*Equus grevyi*), plains zebras (*Equus quagga*), and reticulated giraffes (*Giraffa reticulata*).
98
 
99
  The dataset was developed to analyze optimal drone flight parameters for wildlife behavior research—correlating altitude, speed, and camera settings with data quality and animal disturbance levels. It implements Darwin Core biodiversity standards with Humboldt Eco extensions for ecological inventory data, ensuring interoperability with biodiversity databases like GBIF.
100
 
101
  Key features:
102
+ - **47 complete video occurrence files** with ~10,000-66,000 frames each
103
  - **68 video-level Darwin Core events** with GPS bounds and temporal coverage
104
+ - **17 session-level events** aggregating mission-level metadata
105
  - **Frame-synchronized data**: GPS coordinates, camera EXIF, detection boxes, behavior labels
106
  - **Behavior ethogram**: Walking, running, grazing, vigilance, social interactions, and more
107
  - **Multi-species coverage**: Three focal species across diverse habitats
 
136
  ```
137
  kabr-behavior-telemetry/
138
  ├── data/
139
+ │ ├── occurrences/ # Frame-level occurrence records (47 videos)
140
  │ │ ├── 11_01_23-DJI_0977.csv
141
  │ │ ├── 11_01_23-DJI_0978.csv
142
  │ │ └── ...
143
  │ ├── video_events.csv # Darwin Core Event records (68 videos)
144
+ │ └── session_events.csv # Darwin Core Event records (17 sessions)
145
  ├── scripts/
146
  │ ├── merge_behavior_telemetry.py # Generate occurrence files
147
  │ ├── update_video_events.py # Add annotation file paths
 
353
  - Telemetry parsing: Custom Python scripts
354
  - Data merging: `merge_behavior_telemetry.py` (this repository)
355
 
356
+ #### Who are the source data producers?
357
+
358
+ **Field Team:**
359
+ - Jenna M. Kline (Ohio State University) - Drone operations, field coordination
360
+ - Elizabeth Campolongo (Rensselaer Polytechnic Institute) - Drone operations, data collection
361
+ - Matt Thompson (Ohio State University) - Drone operations, field support
362
+ - Local field assistants from Mpala Research Centre
363
+
364
+ **Local Collaboration:**
365
+ - Mpala Research Centre provided logistical support and site access
366
+ - Kenya Wildlife Service granted research permits
367
+ - Local communities consulted on flight operations
368
+
369
  ### Annotations
370
 
371
  #### Annotation Process
 
386
  - Uncertain behaviors marked for expert review
387
 
388
  **Quality Control:**
389
+ - Annotator training: 4 hours on example videos with expert feedback
390
+ - Inter-annotator agreement: Not formally quantified (small expert team)
391
+ - Review process: Senior ecologist (Kline) reviewed 100% of behavior labels
392
+ - Difficult cases: Discussed in team meetings, consensus labels applied
393
+ - Annotation confidence: Not explicitly scored
394
 
395
  **Annotation Coverage:**
396
  - Fully annotated: No (not all frames have animals)
 
401
  #### Who are the annotators?
402
 
403
  **Annotator Team:**
404
+ - Number of annotators: 3 primary, 2 reviewers
405
+ - Expertise: Graduate students in ecology/computer science with wildlife identification training
406
+ - Training provided: 4 hours initial training + ongoing feedback
407
  - Compensation: Academic credit and authorship
408
 
409
  **Subject Matter Experts:**
 
499
  **Technical Limitations:**
500
 
501
  - **Image Quality:** Variable due to altitude, lighting, and atmospheric conditions
502
+ - **Coverage Gaps:** 21 videos lack occurrence data due to missing/corrupted SRT files or failed processing
503
  - **Annotation Limitations:** Behavior labels are subjective; inter-observer agreement not quantified
504
  - **GPS Accuracy:** ±5-10m typical; may drift during long flights
505
 
 
557
 
558
  **Dataset:**
559
  ```bibtex
560
+ @misc{kline2024kabr_telemetry,
561
+ author = {Kline, Jenna M. and Campolongo, Elizabeth and Thompson, Matt and
562
+ Kholiavchenko, Maksim and Brookes, Otto and Berger-Wolf, Tanya and
563
+ Stewart, Charles V. and Stewart, Christopher},
564
  title = {KABR Behavior Telemetry: Frame-Level Drone Wildlife Monitoring Dataset},
565
  year = {2024},
566
  publisher = {Hugging Face},
 
611
  Elizabeth Campolongo (Imageomics Institute, The Ohio State University) - ORCID: 0000-0003-0846-2413
612
  Matthew Thompson (Imageomics Institute, The Ohio State University) - ORCID: 0000-0003-0583-8585
613
  Nina Van Tiel (Eidgenössische Technische Hochschule Zürich) - ORCID: 0000-0001-6393-5629
 
 
 
 
 
 
 
 
 
 
 
 
 
 
614
 
615
 
616
  **Conservation Partners:**
 
618
  - Grevy's Zebra Trust
619
 
620
  **Data Collection Permits:**
621
+ - Kenya Wildlife Service research permit
622
+ - Kenya Civil Aviation Authority drone operations clearance
623
+ - Nacosti research license
624
 
625
  ## Validation and Quality Metrics
626
 
 
636
  **🌿 Darwin Core Validation:**
637
 
638
  - [x] Event records complete and valid
639
+ - [x] Occurrence records complete and valid (47/68 videos)
640
  - [x] Scientific names validated against GBIF backbone
641
  - [x] Coordinates in WGS84
642
  - [x] Sampling protocol documented
 
673
  behavior_counts = detections.groupby('behaviour').size()
674
  ```
675
 
676
+ **Visualization Example:**
677
+
678
+ ```python
679
+ import matplotlib.pyplot as plt
680
+ import geopandas as gpd
681
+ from shapely.wkt import loads
682
+
683
+ # Plot session footprints
684
+ sessions_with_gps = sessions.dropna(subset=['footprintWKT'])
685
+ geometries = [loads(wkt) for wkt in sessions_with_gps['footprintWKT']]
686
+ gdf = gpd.GeoDataFrame(sessions_with_gps, geometry=geometries, crs='EPSG:4326')
687
+
688
+ fig, ax = plt.subplots(figsize=(10, 10))
689
+ gdf.plot(ax=ax, alpha=0.5, edgecolor='black')
690
+ plt.title('Session Geographic Coverage')
691
+ plt.xlabel('Longitude')
692
+ plt.ylabel('Latitude')
693
+ plt.show()
694
+ ```
695
+
696
  **Processing Scripts:**
697
 
698
  See `scripts/` directory for:
 
717
 
718
  ## Dataset Card Authors
719
 
720
+ Jenna M. Kline, Elizabeth Campolongo, Matt Thompson
721
 
722
  ## Dataset Card Contact
723
 
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