Delair.ai provides a wide range of basic to advanced scouting maps for crop monitoring. This tutorial explains how to extract and analyze data and statistics from these analytics.
Read about currently supported agriculture assets :
1. Available Maps
NB: An orthomap with reflectance maps, and a DSM, are generated from the photogrammetry processing.
1.1. Base Scouting Maps
|NDVI||Normalized Difference Vegetation Index|
Crop Vigor : Map to analyse vigor, that is mix of biomass development and crop health. The basic tool to scout for field anomalies.
|NDRE||Normalized Difference Red Edge|
Chlorophyll Content : Map to analyse chlorophyll content, thanks to an index that correlates well with chlorophyll. The basic tool for nitrogen recommendation based on chlorophyll analysis.
|VARI||Visible Atmospherically Resistant Index|
Greenness : Map to discriminate green plants from the remaining, soil as an example.
|MCARI2||Modified Chlorophyll Absorption Index Ratio 2||Green Biomass : Map that is a good predictor of green leaf area index to analyse biomass development.|
|PRI||Photochemical Reflectance Index|
Map that values spectral bands where photosynthetic pigments might be affected by water stress conditions such as chlorophyll and carotenoids.
1.2. Advanced Scouting Maps
|MSAVI2||Modified Soil-Adjusted Vegetation Index 2|
Soil-Ajusted Crop Vigor : Map to analyse crop vigor, that is mix of biomass development and crop health to scout for field anomalies. Main difference with NDVI is that it removes partly the effect of soils. Thus, this index is more suitable to use at early stage of crop development or where canopy is not closed. This is an MSAVI2 map, that is a combination of red and NIR infrared.
False color photograph that highlights vegetation.
|CCCI||Canopy Chlorophyll Content Index|
Map that is correlated to N Status / Chlorophyll concentration and can be valued to benchmark chlorophyll status or feed nitrogen variable rate maps.
2. Required Inputs
Following chart shows which sensor bands are used from the multispectral camera to calculate scouting maps. Please note that for Bird View, either a RGB sensor or separate R,G,B bands, may be used :
3. Output File Formats
All maps listed above are output as rasters, in .tif file format.
4. Generating Maps
During Site creation step, before launching upload, available outputs for used sensor will be displayed; in example below, the Photochemical Reflectance Index (PRI) will not be calculated. Base scouting maps shown as Outputs are calculated by default if used sensor allows for.
During this step, you can add advanced scouting maps :
If you upload your dataset without photogrammetry these maps are not computed and will be displayed as barred :
5. Exploring Maps
Open your site, and from the left panel, go to the BASE LAYERS section. You can rearrange this layer organization if needed (read here).
6. Analyzing Maps
Clicking one layer from the left panel results in opening the current map information panel on right side, with tools to analyze the map.
6.1. Value at point
This tool allows to check agriculture indice value at any point of the scouting map :
6.2. Data Extraction from a point annotation
Draw a point annotation and press Extract data from point information panel :
All available indices values at point will be displayed :
6.3. Scouting Map Value Distribution
Read the value distribution in a scouting map from the information panel, under STYLE section. Value distributions can be displayed with these modes :
|Mean and standard deviation||Values are centered on the mean with 1 standard deviation discarded at each extemity.|
|Absolute||All values are displayed.|
|Cumulative % cut||Lower and upper values are discarded. You can set the % of value to discard (default is +/- 3%).|
|Custom||Select the range on which you want to display the map :|
The color chart options are :
- Green-Yellow-Red (i.e. lower values are in green)
7. How to extract Statistics from Maps
In order to get Statistics on a trait, a vector first has to be created for the Area of Interest among the field, in which the statistics must be extracted. This can be achieved for example by uploading a kml file containing a polygon describing the boundaries for this area of interest.
NB : For Field Trials, microplot vectorization shall be preliminary completed.
Step 1 - From the Uploads section, add the kml to the project pressing New / Import a New file.
Step 2 - Then select how the file shall be attached.
Step 3 - Select the appropriate CRS options.
After this upload operation is completed, kml becomes visible in Layers, and a Statistics icon will appear as available to be run under the Analytics menu.
Step 4 - Input a Deliverables suffix (optional) if necessary, and tick for the traits to be computed. During this step, you can choose to use and define a value for the Data filter factor.
8. Exporting Scouting Maps & Statistics
All generated Maps and Statistics can be exported from the Downloads section. Maps are available under .tif format, and statistics under .json and .csv formats.
9. Details about Base Scouting Maps
9.1. RGB (Bird View)
To view the orthomosaic, enable RGB from the BASE LAYERS section in Analytics left panel :
9.2. NDVI (Normalized Difference Vegetation Index)
NDVI gives indication of the photosynthetic activity, crop vigor and helps spot anomalies. NDVI of dense vegetation canopy will tend to positive values (0.3 to 0.8).
- Soils generally exhibit a near-infrared spectral reflectance somewhat larger than the red, and thus tend to also generate rather small positive NDVI values (0.1 to 0.2).
- Moderate values represent shrub and grassland (0.2 to 0.3)
- High values indicate temperate and tropical rainforests (0.6 to 0.8)
9.3. NDRE (Normalized Difference Red Edge)
NDRE is used to assess field chlorophyll content, and thus nitrogen content or stress detection (at the earliest stage possible, before NDVI).
- Soil typically has the lowest values
- Unhealthy plants have intermediate values
- Healthy plants have the highest values
9.4. VARI (Visible Atmospherically Resistant Index)
VARI serves to isolate soil from plant. Usually utilized if RGB sensor only, less accurate than NDRE or NDVI.
9.5. MCARI2 (Modified Chlorophyll Absorption Ratio Index 2)
MCARI2 is employed for Green biomass evaluation.
9.6. PRI (Photochemical Reflectance Index)
PRI serves to identify areas of the field suffering from water stress, evident by clusters of pigments (such as chlorophyll and carotenoids).
10. Details about Advanced Scouting Maps
10.1. MSAVI2 (Modified Soil-Adjusted Vegetation Index 2)
MSAVI2 is for use with early stage crops or where the canopy is not closed to help analyze crop vigor and identify anomalies (similar to NDVI, this excludes soil).
10.2. CIR (Colored Infra-Red)
CIR serves to isolate vegetation from the surrounding environment.
10.3. CCCI (Canopy Chlorophyll Content Index)
CCCI serves for Chlorophyll concentration evaluation, to correlate nitrogen and chlorophyll concentration responses or feed nitrogen variable rate maps.
Learn more on how to use delair.ai Field Inventory Analytics.