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== I. UAS-TALLGRASS-PRESCIBED-FIRE-2019-NIR-Data-Set==
=== Introduction===
The UAS-TALLGRASS-PRESCIBED-FIRE-2019- NIR-Data-Set was collected using KHawk Thermal-55 UAS on Oct. 8th 2019 at the KUFS Anderson County Prairie Preserve (38.182073, -95.275708, close to Welda KS).


Fire Perimeters are extracted from Registered Multitemporal NIR Orthomosacis at the following time:
[[File:NIR_Thermal_Comparison.png|left|200px|]]
FirePerimeter_1 12:07:03-12:09:19 PM (CDT)
FirePerimeter_2 12:12:41-12:15:03 PM (CDT)
FirePerimeter_3 12:15:26-12:17:47 PM (CDT)
UAS sensing payload: Modified GoPro Hero 4 Black NIR Camera. An example thermal and NIR image pair is shown on the left for some comparison (top: thermal, bottom: NIR).
Vegetation: C4 tallgrasses and a mixture of herbaceous forbs and legumes.
Weather: temperature at 73 deg. F, humidity at 41%, wind velocity (2 m) at 6.26 m/s mostly from the South.
Terrain: mostly flat.
Fire setting pattern: ring fire with two groups starting the fire from the center of the north boundary and ending the firing at about the center of the south boundary.
=== Data Set ===
Fire NIR Othomap 1 12:07:03-12:09:19 PM (CDT)
[https://people.ku.edu/~h512c315/NIRFireData/Map1Fire_CUSL.png (PNG LINK)]
Fire NIR Othomap 2 12:12:41-12:15:03 PM (CDT)
[https://people.ku.edu/~h512c315/NIRFireData/Map3Fire_CUSL.png (PNG LINK)]
Fire NIR Othomap 3 12:15:26-12:17:47 PM (CDT)
[https://people.ku.edu/~h512c315/NIRFireData/Map4Fire_CUSL.png (PNG LINK)]
The time labels for the fire front in the above three maps can be downloaded from [https://people.ku.edu/~h512c315/NIRFireData/NIR_TimeLabel.zip (Time Label LINK)]. The three above fire maps in GEOTIFF can be requested by sending an email to Dr. Haiyang Chao (chaohaiyang A*T ku D*O*T edu). Please put "Request for GEOTIFF (UAS-TALLGRASS-NIR)" in the email title.
=== Paper ===
Submitted to IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing for consideration of publication.
== II. UAS-TALLGRASS-PRESCIBED-FIRE-2019-Thermal-Data-Set==
=== Introduction===
{|width="100%" cellpadding="2" cellspacing="5" style="vertical-align:top;background-color:#f5fffa"
|-valign="top"
|-
|
The UAS-TALLGRASS-PRESCIBED-FIRE-2019-Thermal-Data-Set was collected using KHawk Thermal-55 UAS on Oct. 8th 2019 at the KUFS Anderson County Prairie Preserve (38.182073, -95.275708, close to Welda KS). Fire Perimeters are extracted from Registered Multitemporal Orthomosacis at the following time:
FirePerimeter_1 12:06:50-12:09:18 PM
FirePerimeter_2 12:09:34-12:10:44 PM
FirePerimeter_3 12:12:41-12:15:02 PM
FirePerimeter_4 12:15:27-12:17:47 PM
UAS sensing payload: FLIR Vue Pro R thermal camera.
Vegetation: C4 tallgrasses and a mixture of herbaceous forbs and legumes.
Weather: temperature at 73 deg. F, humidity at 41%, wind velocity (2 m) at 6.26 m/s mostly from the South.
Terrain: mostly flat.
Fire setting pattern: ring fire with two groups starting the fire from the center of the north boundary and ending the firing at about the center of the south boundary.
|-
|
=== Dataset===
|-
|
<gallery>
Image:FireMap_1.png | FireMap1
Image:FireMap_2.png | FireMap2
Image:FireMap_3.png | FireMap3
Image:FireMap_4.png | FireMap4
</gallery>
|}
The four above fire maps in GEOTIFF can be requested by sending an email to Dr. Haiyang Chao (chaohaiyang A*T ku D*O*T edu). Please put "Request for GEOTIFF (IJRS-UAS-TALLGRASS-Thermal)" in the email title.
=== Paper===
Details of the data collection procedure can be found in our paper on International Journal of Remote Sensing. Saket Gowravaram, Haiyang Chao, Tiebiao Zhao, Sheena Parsons, Xiaolin Hu, Ming Xin, Harold Flanagan, and Pengzhi Tian, Prescribed Grass Fire Evolution Mapping and Rate of Spread Measurement Using Orthorectified Thermal Imagery from a Fixed-Wing UAS, International Journal of Remote Sensing (IJRS), DOI: 10.1080/01431161.2022.2044538, 2022 [https://people.ku.edu/~h512c315/FireMonitoring_IJRS_ProofRead.pdf (PDF)].
== III. UAS-GPS-Inertial-OpticalFlow-DataSet==
=== Introduction===
{|width="100%" cellpadding="2" cellspacing="5" style="vertical-align:top;background-color:#f5fffa"
{|width="100%" cellpadding="2" cellspacing="5" style="vertical-align:top;background-color:#f5fffa"
|-valign="top"
|-valign="top"
| <h2 style="margin:0;background-color:#cef2e0;font-size:120%;font-weight:bold;border:1px solid #a3bfb1;text-align:left;color:#000;padding:0.2em 0.4em;">CUSL </h2>
 
|-
|-
|  
|  
This readme file provides a brief introduction of the WVU-RED-OF-DataSet1, which is collected using Phastball UAV platform for vision-aided inertial navigation researches. The details of the data collection can be found in the authors' paper presented in ACC 2013, entitled with a comparison study of optical flow and tradional sensors in UAV navigation. Please reference our paper if you use our data. The overall file structure for each subfolder can be summarized as the following:
A brief introduction of the WVU-KU-RED-OF-DataSet1, which is collected using WVU Phastball UAV platform for vision-aided inertial navigation researches. The details of the data collection can be found in the authors' two papers ACC 2013 (a comparison study of optical flow and traditional sensors in UAV navigation) and JAIS 2016 (Flight-Test Evaluation of Navigation Information in Wide-Field Optical Flow, AIAA Journal of Aerospace Information Systems, Vol. 13, No. 11, pp.419-432). Please reference our papers if you use our data. The overall file structure for each subfolder can be summarized as the following:
|-
|-
|
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Line 61: Line 148:
</gallery>
</gallery>
|}
|}
== Dataset==
=== Dataset===
{| class="wikitable" style="width:80%"
{| class="wikitable" style="width:80%"
| style="padding: 5px;"| '''video'''
| style="padding: 5px;text-align: center;"| '''video'''
| style="padding: 20px;"| '''GPSINSLog'''
Video-Air-Red-05272011.avi, an aerial video file collected by Phastball UAV;
| style="padding: 20px;"| '''Matlab'''
| style="padding: 20px;text-align: center;"| '''GPSINSLog'''  
Video-Air-Red-05272011.avi, the aerial video file collected by Phastball UAV;
| style="padding: 20px;text-align: center;"| '''Matlab'''
basic MATLAB script to show how to extract frames from video and how to plot the telemetry;
|-
|-
|Video-Air-Red-05272011.avi, an aerial video file collected by Phastball UAV;
|
https://mega.nz/#!isRCgTyK!DxKa-eDTZHeFbg9DGX5cPVgIHLv2LuxlfTHP-lbHZc0
*The video is collected by GoPro Hero camera in r5 mode (1920*1080 pixs).
|https://mega.nz/#!GloX1SZC!EwdzPdlPPUz5e5lmLf1XftoAofxF1eeqhilifIJXyjo
*The GoPro Hero camera is installed on a Phastball UAV with a cruise speed of about 30 m/s.
|https://mega.nz/#!m0ZxEaTY!KeMbGaZsK0XQtkr8S-im6PBgDm4WQLf3Cj8pKBoEm3M
https://www.dropbox.com/s/1nyn6rk93js7re4/Video-Air-Red-05272011.avi?dl=0
|
*GPSINSLog is synchrolized manually with the video file (29.97 Hz).
*Video-Air-Red-05272011.avi contains 10648 frames and GPSINSLog is aligned with the first 10600 frames manually.
 
https://www.dropbox.com/s/flbdo2eeygd5q33/GPSINSRange_30Hz.mat?dl=0
|
https://www.dropbox.com/s/mwuaz2znrgqrtr7/plot_frame.m?dl=0
https://www.dropbox.com/s/wom3c55fl6w9pcz/Plot_nav_sensors.m?dl=0
 
|}
|}


===CamCalib===
{| id="mp-left" style="width:100%; vertical-align:top; background:#FBF7F7;"
{| id="mp-left" style="width:100%; vertical-align:top; background:#FBF7F7;"
|-
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px">'''The Cooperative Unmanned Systems Laboratory (CUSL)''' |-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px"> The GoPro camera is calibrated using Camera calibration toolbox for MATLAB[http://www.vision.caltech.edu/bouguetj/calib_doc/htmls/parameters.html (Link)]
 
'''The calibration file can be downloaded using the following link:'''
https://www.dropbox.com/s/xg51m1093ztz77y/GoProHero_r5_Calib.mat?dl=0
|-


|}
|}
=== Paper===
https://www.dropbox.com/sh/jnpqepgcf8n3b1n/AABZnRBNX_yS7X3wi5NT20wca?dl=0

Latest revision as of 18:08, 19 December 2022

Welcome to Cooperative Unmanned Systems Laboratory (CUSL)

I. UAS-TALLGRASS-PRESCIBED-FIRE-2019-NIR-Data-Set

Introduction

The UAS-TALLGRASS-PRESCIBED-FIRE-2019- NIR-Data-Set was collected using KHawk Thermal-55 UAS on Oct. 8th 2019 at the KUFS Anderson County Prairie Preserve (38.182073, -95.275708, close to Welda KS).

Fire Perimeters are extracted from Registered Multitemporal NIR Orthomosacis at the following time:

FirePerimeter_1 12:07:03-12:09:19 PM (CDT)

FirePerimeter_2 12:12:41-12:15:03 PM (CDT)

FirePerimeter_3 12:15:26-12:17:47 PM (CDT)

UAS sensing payload: Modified GoPro Hero 4 Black NIR Camera. An example thermal and NIR image pair is shown on the left for some comparison (top: thermal, bottom: NIR).

Vegetation: C4 tallgrasses and a mixture of herbaceous forbs and legumes.

Weather: temperature at 73 deg. F, humidity at 41%, wind velocity (2 m) at 6.26 m/s mostly from the South.

Terrain: mostly flat.

Fire setting pattern: ring fire with two groups starting the fire from the center of the north boundary and ending the firing at about the center of the south boundary.

Data Set

Fire NIR Othomap 1 12:07:03-12:09:19 PM (CDT) (PNG LINK)

Fire NIR Othomap 2 12:12:41-12:15:03 PM (CDT) (PNG LINK)

Fire NIR Othomap 3 12:15:26-12:17:47 PM (CDT) (PNG LINK)

The time labels for the fire front in the above three maps can be downloaded from (Time Label LINK). The three above fire maps in GEOTIFF can be requested by sending an email to Dr. Haiyang Chao (chaohaiyang A*T ku D*O*T edu). Please put "Request for GEOTIFF (UAS-TALLGRASS-NIR)" in the email title.

Paper

Submitted to IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing for consideration of publication.

II. UAS-TALLGRASS-PRESCIBED-FIRE-2019-Thermal-Data-Set

Introduction

The UAS-TALLGRASS-PRESCIBED-FIRE-2019-Thermal-Data-Set was collected using KHawk Thermal-55 UAS on Oct. 8th 2019 at the KUFS Anderson County Prairie Preserve (38.182073, -95.275708, close to Welda KS). Fire Perimeters are extracted from Registered Multitemporal Orthomosacis at the following time:

FirePerimeter_1 12:06:50-12:09:18 PM

FirePerimeter_2 12:09:34-12:10:44 PM

FirePerimeter_3 12:12:41-12:15:02 PM

FirePerimeter_4 12:15:27-12:17:47 PM

UAS sensing payload: FLIR Vue Pro R thermal camera.

Vegetation: C4 tallgrasses and a mixture of herbaceous forbs and legumes.

Weather: temperature at 73 deg. F, humidity at 41%, wind velocity (2 m) at 6.26 m/s mostly from the South.

Terrain: mostly flat.

Fire setting pattern: ring fire with two groups starting the fire from the center of the north boundary and ending the firing at about the center of the south boundary.

Dataset

  • FireMap1
    FireMap1
  • FireMap2
    FireMap2
  • FireMap3
    FireMap3
  • FireMap4
    FireMap4

The four above fire maps in GEOTIFF can be requested by sending an email to Dr. Haiyang Chao (chaohaiyang A*T ku D*O*T edu). Please put "Request for GEOTIFF (IJRS-UAS-TALLGRASS-Thermal)" in the email title.

Paper

Details of the data collection procedure can be found in our paper on International Journal of Remote Sensing. Saket Gowravaram, Haiyang Chao, Tiebiao Zhao, Sheena Parsons, Xiaolin Hu, Ming Xin, Harold Flanagan, and Pengzhi Tian, Prescribed Grass Fire Evolution Mapping and Rate of Spread Measurement Using Orthorectified Thermal Imagery from a Fixed-Wing UAS, International Journal of Remote Sensing (IJRS), DOI: 10.1080/01431161.2022.2044538, 2022 (PDF).

III. UAS-GPS-Inertial-OpticalFlow-DataSet

Introduction

A brief introduction of the WVU-KU-RED-OF-DataSet1, which is collected using WVU Phastball UAV platform for vision-aided inertial navigation researches. The details of the data collection can be found in the authors' two papers ACC 2013 (a comparison study of optical flow and traditional sensors in UAV navigation) and JAIS 2016 (Flight-Test Evaluation of Navigation Information in Wide-Field Optical Flow, AIAA Journal of Aerospace Information Systems, Vol. 13, No. 11, pp.419-432). Please reference our papers if you use our data. The overall file structure for each subfolder can be summarized as the following:

  • building
    building
  • grass_river
    grass_river
  • road_river_car
    road_river_car
  • road_river_pond_grassland
    road_river_pond_grassland
  • road_river_runway_building
    road_river_runway_building
  • road_river_runwy_building
    road_river_runwy_building

Dataset

video

Video-Air-Red-05272011.avi, an aerial video file collected by Phastball UAV;

GPSINSLog

Video-Air-Red-05272011.avi, the aerial video file collected by Phastball UAV;

Matlab

basic MATLAB script to show how to extract frames from video and how to plot the telemetry;

  • The video is collected by GoPro Hero camera in r5 mode (1920*1080 pixs).
  • The GoPro Hero camera is installed on a Phastball UAV with a cruise speed of about 30 m/s.

https://www.dropbox.com/s/1nyn6rk93js7re4/Video-Air-Red-05272011.avi?dl=0

  • GPSINSLog is synchrolized manually with the video file (29.97 Hz).
  • Video-Air-Red-05272011.avi contains 10648 frames and GPSINSLog is aligned with the first 10600 frames manually.

https://www.dropbox.com/s/flbdo2eeygd5q33/GPSINSRange_30Hz.mat?dl=0

https://www.dropbox.com/s/mwuaz2znrgqrtr7/plot_frame.m?dl=0 https://www.dropbox.com/s/wom3c55fl6w9pcz/Plot_nav_sensors.m?dl=0

CamCalib

The GoPro camera is calibrated using Camera calibration toolbox for MATLAB(Link)

The calibration file can be downloaded using the following link: https://www.dropbox.com/s/xg51m1093ztz77y/GoProHero_r5_Calib.mat?dl=0


Paper

https://www.dropbox.com/sh/jnpqepgcf8n3b1n/AABZnRBNX_yS7X3wi5NT20wca?dl=0

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