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Scouting Analytics

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

MAP
DESIGNATION
DESCRIPTION
RGBBird View
Bird View
NDVINormalized 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.

NDRENormalized 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.

VARIVisible Atmospherically Resistant Index

Greenness : Map to discriminate green plants from the remaining, soil as an example.

MCARI2Modified Chlorophyll Absorption Index Ratio 2Green Biomass : Map that is a good predictor of green leaf area index to analyse biomass development.
PRIPhotochemical 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

MAP
DESIGNATION
DESCRIPTION
MSAVI2Modified 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.

CIRColored Infra-Red

False color photograph that highlights vegetation.

CCCICanopy 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 deviationValues are centered on the mean with 1 standard deviation discarded at each extemity.
AbsoluteAll values are displayed.
Cumulative % cutLower and upper values are discarded. You can set the % of value to discard (default is +/- 3%).
CustomSelect the range on which you want to display the map :
  • manually with mouse pointer
  • or inputting the min and max values

The color chart options are :

  • Spectral
  • Green-Yellow-Red (i.e. lower values are in green)
  • Red-Yellow-Green
  • Grayscale


7. 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.


8. Details about Base Scouting Maps

8.1. RGB (Bird View)

To view the orthomosaic, enable RGB from the BASE LAYERS section in Analytics left panel :

8.2. 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)

8.3. 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

8.4. VARI (Visible Atmospherically Resistant Index)

VARI serves to isolate soil from plant. Usually utilized if RGB sensor only, less accurate than NDRE or NDVI.

8.5. MCARI2 (Modified Chlorophyll Absorption Ratio Index 2)

MCARI2 is employed for Green biomass evaluation.

8.6. 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).


9. Details about Advanced Scouting Maps

9.1. 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).

9.2. CIR (Colored Infra-Red)

CIR serves to isolate vegetation from the surrounding environment.

9.3. 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 Generic and Scouting map, Microplot Vectorization


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