The below information explains the best workflow to post-process images from the Survey2 cameras. For Survey3 cameras please see here.

Capture & Apply GPS Location

First thing you should do when you receive your camera is set the camera's time to GPS time. GPS time is 18 seconds faster than UTC time. Go to the camera's settings and use this site to set to GPS time. If you are triggering the camera via PWM make sure to set the Time Lapse Photo setting to OFF. We also highly recommend turning on RAW photo capture for the best results (you can convert to JPG in post-processing below).

It is not recommended to adjust any other camera photo settings (shutter speed, ISO, white balance, etc) unless you know what you're doing and have our Reflectance Calibration Target. We have already set the default values so that you do not get over-exposed pixel values.

Mission planning is based on your aerial platform and what flight controller it is using. This video shows how to setup a mission with a Pixhawk-based drone and the free Android mission planning application Tower. The flight controller's log file saved during the mission is used to apply GPS locations to the JPG images, known as geo-referencing the photos. You can watch a video on how to extract the log file from a Pixhawk here using Mission Planner, and this page has links on how to convert the DJI flight logs. Our video here shows how to geo-reference the photos using the converted log file and the program GeoSetter. If you are unable to obtain a log file in a format that GeoSetter can read then we recommend purchasing an external GPS tracker to save your flight path. 

Prepare Images in QGIS MAPIR Plugin

Once you apply the GPS locations to the JPG images you will want to process the RAW and JPG images with our QGIS MAPIR plugin using the Pre-Process tab. This step converts the RAW images to TIFFs, copies the EXIF image metadata from the JPGs (including the GPS locations).

If you are going to use ortho-mosaic generation software like Pix4D and Agisoft Photoscan then you will want to stitch the ortho first and then proceed to calibration below. Do not calibrate and then stitch as the results will not be satisfactory (poor automatic tie points). It's also not recommended to use the the calibration and index steps of these software packages either as they are lacking in both features and accuracy (only single reflectance target versus our triple target calibration).

Next you will want to calibrate the images (not necessary with Visible Light model) using the Calibrate tab of our QGIS plugin. This step will ask you for an image of our Reflectance Calibration Target if you captured one before your survey (recommended), or if you don't have one you can use the default reflectance values we provide (created from an image taken during full sun). The images will be calibrated with each pixel representing the reflectance value and not a color value, so don't be concerned if the images seem too dark. You can also choose to convert the TIFF files to JPG if your ortho-mosaic software does not support TIFFs (such as MAPIR Cloud, DroneDeploy, MapsMadeEasy, etc).

Creating the Ortho-mosaic

An ortho-mosaic is a single stitched image containing the many individual photos taken during your survey. Your results will vary though based on the capabilities of the software used to create the ortho image.

Software that is not able to use an image's GPS data to assist stitching will struggle to create ortho-mosaics of complex subject matter. Complex subject matter is typically captured when flying over areas where the images will look very similar to each other, such as uniform canopy agricultural fields. Software that doesn't use the GPS data will also have no way to locate the final stitched ortho image onto a map (like Google Earth) because there will be no reference GPS information. We strongly recommend you do not use software that cannot take advantage of the GPS location in the survey images.

There are two options to process your images with GPS information: cloud-based services that do the processing for you or stand-alone programs you run yourself.

Cloud-based packages such as Drone Deploy, MapsMadeEasy all require you to upload your images to their site and then notify you when the processing is completed. These services vary in how they charge you but the majority have a minimum monthly fee around $100. They also vary in the final results you'll get from their services, and typically the more expensive "professional" packages provide more outputs with higher cost. Output examples include geo-reference images, DSM maps, KML files and NDVI color-graded images. These cloud-based services often do not support RAW/TIFF files so make sure to convert them to JPGs using the calibration step mentioned above. They also do not support aligning single band filter cameras (NIR, Red, Green, Blue) with each other for multi-spectral indice/raster calculations.

Two of the top packages which support aligning the single band cameras with each other are Pix4Dmapper and Agisoft Photoscan. These programs are more commonly known as "point cloud" software. They are called this because they look at each and every point, or more specifically each pixel and match up the images. While they can stitch some image sets this way without GPS information, it will greatly reduce your processing time and increase your success rate if you do use geo-referenced photos.  The importance of aligning the cameras with each other is that you can then process the ortho layers in a rastor/index calculator for the indice (ie NDVI, ENDVI, GNDVI, OSAVI, RDVI, SAVI, etc) you require. Both Pix4D and Photoscan have rastor calculators included but since the images won't be calibrated after ortho generation we recommend calibrating in our QGIS plugin and then using the Rastor and Lut tools of QGIS to have better control of your color gradient/lut. Since these programs create a point cloud they can also output .obj, .mtl and .jpeg texture files to be used in 3D model viewers like p3d and sketchfab.  These powerful point cloud software packages typically cost about 3x more than the cloud-based services but the additional cost should be easily amortized over time due to the ability to align the single band images to calculate the index of your choice.