Plant Count & Emergence for Microplot

1. Description

Estimates plant count and emergence for row crops

This article will cover the 3 analytics:

  • Plant Count & Emergence from spectral index for microplot
  • Plant Count & Emergence from orthomosaic  for microplot
  • Plant Count & Emergence from reflectance for microplot

2. Prerequisites

Required Definition
Spectral Index Maps‍ (for Plant Count & Emergence from spectral index for Microplot)
  • Multispectral sensor: 
    • NDVI (Normalized Difference Vegetation Index) is calculated from the photogrammetry or the Generic Scouting Map analytics.
  • RGBsensor: 
    • From the Spectral Index Map analytics: 
      • VARI (Visible Atmospherically Resistant Index) 
    • From the Custom scouting Map analytic: 
      • ExG (Excess Green) = 2*green-red-blue
      • TGI (Triangular Greenness Index) = green-0.39*red-0.61*blue
RGB orthomosaic map (for Plant Count & Emergence from orthomosaic  for Microplot) Raster issue from Photogrammetry or the Generic Scouting Map or Custom Composition Map analytics
Reflectance map (for Plant Count & Emergence from reflectance for Microplot) Raster map issue from Photogrammetry or imported in Aether
Inter-plants spacing Theoretical interplant spacing (within the row) 
It is mandatory to see the bare ground between two plants on the map
Microplots vector‍  Vector file containing microplot boundaries
Optional Definition
Row vectorization Vector file containing the digitized rows (if already available). 
Deliverables suffix A suffix applied to all deliverable names
Delete

Info

GSD size of input maps: ⩽ half canopy size (from above)

For row crops, with 6cm of GSD, the optimal corn stage will be 4 leaves and starbud for sunflowers. With enhanced resolution, earlier stages can be targeted.


3. Workflow

3.1 Plant Count & Emergence from spectral index for microplot

Step 1 - In the "Analytics" tab, search and select "Plant Count & Emergence from spectral index for microplot" and click on "LAUNCH".

Step 2 - Select the "Scouting Map" (spectral index map) (1) and the "field boundaries" (microplot file) (2) and click on "NEXT STEP" (3).

Step 3 - Fill in the "Inter plants spacing" (the unit is in meters) and "Deliverables suffix",

Delete

Info

The suffix is applied to all deliverable names.

Step 4 - Click on "LAUNCH PLANT COUNT & EMERGENCE FROM SPECTRAL INDEX FOR MICROPLOT".

Step 5 - Click on "FINISH" to leave the analytics.

3.2 Plant Count & Emergence from orthomosaic for microplot

Step 1 - In the "Analytics" tab, search and select "Plant Count & Emergence from orthomosaic for microplot" and click on "LAUNCH".

Step 2 - Select the "RGB orthomosaic" map (1) and the "Microplot Vector File" (2) and click on "NEXT STEP" (3).

Step 3 - Fill in the "Inter plants spacing", the unit is in meters.

Step 4 - Click on "LAUNCH PLANT COUNT & EMERGENCE FROM ORTHOMOSAIC FOR MICROPLOT".

Step 5 - Click on "FINISH" to leave the analytics.

3.3 Plant Count & Emergence from reflectance for microplot

Step 1 - In the "Analytics" tab, search and select "Plant Count & Emergence from reflectance for microplot" and click on "LAUNCH".

Step 2 - Select the "Raster" (reflectance map) (1) and the "microplot vector file" (2) and click on "LAUNCH PLANT COUNT & EMERGENCE FROM REFLECTANCE FOR MICROPLOT" (3).

Step 3 - Click on "FINISH" to leave the analytics.

4. Status and Progression

Check in the "LAUNCHED" tab that the analytics is in progress.

Aether will notify‍ the user that the analytics results are available.

5. Results

5.1 Layers

In the "Inventory" subgroup of "SURVEY DATA" a new subgroup  "Plant and gap counting" is created with 4 layers:

  • Plant count

Display the plant count layer, and the microplots appear. The microplots will also be colored depending on the selected attribute and its corresponding values.

Delete

Info

Click on one microplot to display its plant number and other attributes.

  • Gaps

You can also display the RGB map to identify where the gaps are located. Gaps are represented by small dots, and their color depends on the gap length. Refer to the "Legend" for color/distance definitions.

Delete

Info

Selecting the dot will also display the gap length and further attributes.

  • Rows with plant count

6. Deliverables

6.1 Files

In the "Download‍"  section find files issue from the analytics.

Once the analytics is run, the deliverables can be exported‍ in two standard formats, vector format such as "geoJSON," and "CSV".

6.2 Attributes

List of attributes for each format:

Deliverable File Format Attributes
Gaps geoJSON
  • parent_id: unique id of a group of microplots
  • block_plot_id: six-figure number composed by block_row_id, and block_col_id
  • row_id: row id
  • gap_id: id of the gap
  • gap_length: length of the gap in meters
  • at_line_end: boolean which determines if the gap is at the end of a line
Rows with plant count geoJSON
  • parent_id: unique id of a group of microplots
  • block_plot_id: six-figure number composed by block_row_id, and block_col_id
  • row_id: row id
  • row_length: row length in meter
  • plant_count: number of plants in the row
  • gap_length: total length of gaps in the row in meters
  • plant_length: total length of plants in the row in meters
  • veg_ratio: plant_length/row_length, between 0 and 1
  • row_anomaly: indicates if an anomaly occurred during the vectorization
  • canopy_radius: canopy radius in meters
Plant count geoJSON
  • parent_id: unique id of a group of microplot
  • block_plot_id: six-figure number composed by block_row_id, and block_col_id
  • row_count: number of rows in the microplot
  • plant_count: number of plants in the microplot
  • row_length: mean length of the rows in the microplot in meter
  • plant_length: total length of plants in the microplot in meters
  • gap_length: total length of gaps in the microplot in meters
  • canopy_radius: canopy radius in meters
  • veg_ratio : plant_length/row_length, between 0 and 1
  • row_anomaly: indicates if an anomaly occurred during the vectorization
  • anomaly: low_count, very_low_count, OR _empty_: informs the user if the plant count is far below the average number of plants
  • emergence: qualification of the early vigor of plants
  • theoretical_plant_count: theoretical number of plants
  • plant_count_ratio: ratio between the plants actually raised and the total number of plants sown
Delete

Important

Please note that the attributes "gap" and "length" that are displayed on the right side menu on the platform are not displayed in meters due to a conversion problem. In order to obtain this information in meters please refer to the "gap_length" and "row_length" attributes respectively, present in the downloadable CSV.

We are in the process of correcting this anomaly and apologize for the inconvenience caused. 

7. Quality check the results

This section allows identify potential anomalies on your trial plots.

7.1 Check the "anomaly" attribute

In a plant count vector output, click on a plot to see if there is an anomaly for that given plot. Or extract the CSV file to see a report of the anomalies for all plots.

7.2 Check the "theoretical_plant_count" attribute

In the plant count vector output, if the values are very different from your theoretical plant count, there is probably an anomaly.  

7.3 Check the microplot coregistration

If the plot contour isn't well located around the plants, the results can be impacted. Use a scouting map (like NDVI) in the background to better identify the plant rows and make corrective actions.

The example below shows an overlay of microplots on a plant row. The plants present in this row are therefore difficult to count, which affects the results delivered.


 


Knowledge Base Software powered by Helpjuice