Merge pull request #26 from smathermather/publish

reorder tutorials, add images to index

source/index.rst

@@ -1,15 +1,34 @@
 .. figure:: https://www.opendronemap.org/wp-content/uploads/2018/07/odm-logo.svg
    :alt: OpenDroneMap Logo
-   :align: center
+   :align: left
+   :height: 60
+   :width: 60
 
-Welcome to OpenDroneMap's documentation!
-========================================
+Welcome to OpenDroneMap's documentation
+=======================================
+
+| 
+| 
+
+.. figure:: images/seedling.png
+    :alt: image of seedling
+    :align: right
+    :height: 70
+    :width: 70
 
 .. toctree::
-    :maxdepth: 3
-    :caption: Contents:
 
     installation
+
+
+.. figure:: images/pencil.png
+    :alt: image of pencil
+    :align: right
+    :height: 60
+    :width: 60
+		
+.. toctree::
+
     tutorials
     arguments
     outputs
@@ -18,5 +37,4 @@ Welcome to OpenDroneMap's documentation!
     flying
     contributing
 
-
 `Help edit these docs! <https://github.com/OpenDroneMap/docs/blob/publish/source/index.rst>`_

source/tutorials.rst

@@ -20,6 +20,35 @@ Without any parameter tweaks, ODM chooses a good compromise between quality, spe
  * ``--texturing-data-term`` should be set to `area` in forest areas.
  * ``--mesh-size`` should be increased to `300000-600000` and `--mesh-octree-depth`` should be increased to `10-11` in urban areas to recreate better buildings / roofs.
 
+Calibrating the Camera
+^^^^^^^^^^^^^^^^^^^^^^
+
+Camera calibration is a special challenge with commodity cameras. Temperature changes, vibrations, focus, and other factors can affect the derived parameters with substantial effects on resulting data. Automatic or self calibration is possible and desirable with drone flights, but depending on the flight pattern, automatic calibration may not remove all distortion from the resulting products. James and Robson (2014) in their paper `Mitigating systematic error in topographic models derived from UAV and ground‐based image networks <https://onlinelibrary.wiley.com/doi/full/10.1002/esp.3609>`_ address how to minimize the distortion from self-calibration.
+
+.. figure:: images/msimbasi_bowling.png
+   :alt: image of lens distortion effect on bowling of data
+   :align: center
+
+Bowling effect on point cloud over 13,000+ image dataset collected by World Bank Tanzania over the flood prone Msimbasi Basin, Dar es Salaam, Tanzania.
+
+To mitigate this effect, there are a few options but the simplest are as follows: fly two patterns separated by 20°, and rather than having a nadir (straight down pointing) camera, use one that tilts forward by 5°.
+
+.. figure:: images/flightplanning.gif
+  :alt: animation showing optimum
+  :align: center
+  :height: 480
+  :width: 640
+
+As this approach to flying can be take longer than typical flights, a pilot or team can fly a small area using the above approach. OpenDroneMap will generate a calibration file called cameras.json that then can be imported to be used to calibrate another flight that is more efficiently but, from a self calibration perspective, less accurately.
+
+Vertically separated flight lines also improve accuracy, but less so than a camera that is forward facing by 5°.
+
+.. figure:: images/forward_facing.png
+   :alt: figure showing effect of vertically separated flight lines and forward facing cameras on improving self calibration
+   :align: center
+
+From James and Robson (2014), `CC BY 4.0 <https://creativecommons.org/licenses/by/4.0/>`_
+
 Creating Digital Elevation Models
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
@@ -108,32 +137,5 @@ Create a GCP list that only includes gcp name (this is the label that will be se
 
 Then one can load this GCP list into the interface, load the images, and place each of the GCPs in the image.
 
-Calibrating the Camera
-^^^^^^^^^^^^^^^^^^^^^^
-
-Camera calibration is a special challenge with commodity cameras. Temperature changes, vibrations, focus, and other factors can affect the derived parameters with substantial effects on resulting data. Automatic or self calibration is possible and desirable with drone flights, but depending on the flight pattern, automatic calibration may not remove all distortion from the resulting products. James and Robson (2014) in their paper `Mitigating systematic error in topographic models derived from UAV and ground‐based image networks <https://onlinelibrary.wiley.com/doi/full/10.1002/esp.3609>`_ address how to minimize the distortion from self-calibration.
-
-.. figure:: images/msimbasi_bowling.png
-   :alt: image of lens distortion effect on bowling of data
-   :align: center
-
-Bowling effect on point cloud over 13,000+ image dataset collected by World Bank Tanzania over the flood prone Msimbasi Basin, Dar es Salaam, Tanzania.
-
-To mitigate this effect, there are a few options but the simplest are as follows: fly two patterns separated by 20°, and rather than having a nadir (straight down pointing) camera, use one that points forward by 5°.
-
-.. figure:: images/flightplanning.gif
-  :alt: animation showing optimum
-  :align: center
-
-As this approach to flying can be take longer than typical flights, a pilot or team can fly a small area using the above approach. OpenDroneMap will generate a calibration file called cameras.json that then can be imported to be used to calibrate another flight that is more efficiently but, from a self calibration perspective, less accurately.
-
-Vertically separated flight lines also improve accuracy, but less so than a camera that is forward facing by 5°.
-
-.. figure:: images/forward_facing.png
-   :alt: figure showing effect of vertically separated flight lines and forward facing cameras on improving self calibration
-   :align: center
-
-From James and Robson (2014), `CC BY 4.0 <https://creativecommons.org/licenses/by/4.0/>`_
-
 `Help edit these docs! <https://github.com/OpenDroneMap/docs/blob/publish/source/using.rst>`_