May 28, 2017

Project: High resolution topographic features controlling water retention in agricultural landscapes, Iowa (part of Intensively Managed Landscapes Critical Zone Observatory)

Objective: Capture resolutions of less than 2-cm with UAS and terrestrial lidar following a heavy rain event on two farm plots with differing slopes and land practices

Flight Date: May 21-25, 2017

Flight Location: Near Williamsburg, Iowa at Maas (large slope variation) and Trimpe (low slope variation) farms

Airframe: Phantom 4 Pro

Sensors: Phantom 4 Pro camera

Crew: Michael Wing, Chris Sladek, and henry pai

  •  Successful flights at both farms
    • Maas (May 22) and Trimpe (May 23) flight characteristics
      • 30 m altitude
      • 2.9 m/s
      • Cross-grid pattern, 40-50 minute total flight time (~20 min per battery)
      • 0.8 cm resolution
      • >1000 images
  • Comments
    • Phantom 4 Pro handled heavy winds quite well (on May 22)
    • Only pushed Phantom 4 Pro to 30% battery warning
    • Return to launch feature more reliable than pilot control in heavy winds
    • Issues with tablet obtaining live view using UgCS for DJI app
      • Tablet was only 2.4 GHz capable 
      • Changed Connectify (wifi hotspot) setting so that 2.4 GHz device could connect
      • Worked on Chris's cell phone (may be only dual band device; 2.4 & 5 GHz)
      • Check Android OS versions
      • Email UgCS for any updates
    • Issues with blurry images
      • Initial settings for shutter priority set in DJI Go app (ISO 200, shutter 1/1000 sec)- blurry
      • Changed settings to Auto (ISO 200) and image quality was good (ISO 400 was washed out)
      • Test Auto (ISO 100); could not see red tape on white lids while visible on blue (Maas site with blue and white target in same frame seen below)

    • Issues with continuing mission on power down
      • When replacing battery, mission was not found on Phantom 4 Pro
      • Email UgCS about DJI functionality with "Continue" mission feature
    • Issues on takeoff from ground software?
      • At Trimpe, takeoff caused one flip (slow motor ramp up then flip on take off)
      • Adjusted for faster vertical takeoff speed but still slow motor ramp up
      • Removed takeoff command and takeoff & mission completed without issue; though hard to predict initial waypoint
    • Logistics were challenging given target requirements for both terrestrial lidar and UAS requirements
    • Locus Map Free remains a workhorse app for my phone for laying out targets, importing kml polygons and points, and saving survey points
      • Recommend bringing battery packs for phone for all-day app usage
    • Generous hotel wifi (500 mb/s upload) allowed for data to be uploaded (~3-4 hrs) on work desktop and initial alignment and DSM reconstructions for next-day assessments

May 9, 2017

Project: Medusahead identification invasive plant identification with high resolution multispectral and surface roughness

Objective: Exploratory data collection and proof of concept for automated invasive species (Medusahead) mapping with high resolution multispectral and surface roughness characterization

Flight Date: Weekly starting May 2, 2017 to ?

Flight Location: Reno, NV (39.580312, -119850044)

Airframe: Tarot, DJI Mavic (other faculty)

Sensors: Micasense RedEdge, Mapir, Sony a5100

Crew: Chris Sladek, Chris Kratt, henry pai

Mission 1 (2017/5/2)
  • Successful flights (no crashes!)
    • RedEdge
      • 30 m altitude
      • 4 m/s air speed
      • 1.23 sec camera interval
      • 2.05 cm/pixel resolution
      • ~750 images (x 5 per band)

    • Mapir
      • 35 m altitude
      • 4 m/s air speed
      • 2.72 sec camera interval
      • 1.18 cm/pixel resolution
      • ~210 images

  • Cameras collected data
    • Challenges
      • RedEdge downwelling light sensor and GPS unit cable was loose (did not register data)
      • Mapir did not trigger consistently (different number of camera trigger commands than Mapir photos)
      • Atlas RedEdge post-processing requires GPS coordinates
      • Visible imagery has poor automated alignment (<50 percent of collected images)
    • Adjustments (in progress)
      • Geotag RedEdge images (equal number of trigger commands with photos make this possible)
          • This was successful, steps
          1. Mission planner > download .bin and .log telemetry files > review a log > choose log > left click column "0", header row > filter "CAM" command > right click table and export visible to csv
          2. Used R-script to create new csv file with file names + path seen in above link
          3. Used ExifTool command from prompt from directory of csv:
            ExifTool -csv="panel_firstImg_000.csv" D:\hank\_medusahead_offSync\data\imagery\20170502_flight1\rededge\000\
          4. Used ExifTool from command prompt to tie XMP data to standard Exif geotag data:
            ExifTool "-GPS:all<XMP-exif:all" "-GPS:GPSLongitudeRef<Composite:GPSLongitudeRef" "-GPS:GPSLatitudeRef<Composite:GPSLatitudeRef" "-GPS:GPSAltitudeRef<Composite:GPSAltitudeRef" D:\hank\_medusahead_offSync\data\imagery\20170502_flight1\rededge\000\
          5. Used R-script to organize photos by band
          6. Add dummy location to reflectance panel shot
          7. Atlas Uploader > upload folders (photo locations should appear in map) > click select all and include (claims doesn't see GPS but appears in map)
        • Method 2 (to be done)- script to organize files by band per folder then use Mission Planner to geotag photos  Forgot, Mission Planner can not geotag tiffs.
      • Slow Mapir flight speed to 3 m/s (3.63 sec camera interval) 
      • Use Sony a5100 @ 45 m altitude (0.88 cm/pixel resolution)
      • Use collaborating professor's DJI Mavic (using DJI Go app and Drone Deploy) not registered

May 2, 2017


RCTimer Legacy 3-Axis Aerial Version DSLR Brushless Gimbal


  • Multispectral camera: 
      • Common Uses: Remote sensing analysis of vegetation health status and/or landcover type classification
  • Thermal Imaging Infrared Camera:  
      • Common Uses: Thermographic analysis of a large area where results in C or F are desired (e.g. surface temperature analysis of a grassland prairie)
  • Hyperspectral camera: 
    • Headwall Nano-Hyperspec 
      • Common Uses: Various spectral analysis related to: water quality, plant physiology, vegetative cover classification, and mineral detection


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