What is being shown in my Plant Health maps?
Cameras compatible with DroneDeploy capture three bands of light. The Plant Health maps demonstrate the relative health of vegetation within the map by comparing the value of each band. (Single-band files are supported as SHP exports.)
Healthier vegetation reflects more of certain types of light than unhealthy vegetation. Your DroneDeploy Plant Health map creates a scale to highlight differences within your area of interest.
For more information on the basics behind Plant Health Maps, please see our Identifying Crop Variability with Drones blog post.
How does my drone's camera affect my NDVI map?
Cameras compatible with DroneDeploy capture three bands of light as input. They capture either: Red, Green, and Blue light OR some combination of Near-Infrared, Green, and Blue light.
Cameras that capture Red, Green and Blue light (RGB) apply the VARI algorithm to assess plant health.
Cameras that capture Near Infrared light can apply the following algorithms:
NDVI
ENDVI
GNDVI
SAVI
OSAVI
RDVI
Visible Atmospherically Resistant Index (VARI)
VARI was designed and tested to work with RGB data rather than near-infrared (NIR) data. It is a measure of "how green" an image is. VARI is not intended as a substitute for a NIR camera, but it is meaningful when working with non-NDVI imagery. VARI also measures the reflectance of vegetation versus soil.
Please visit our blog post for more information on the differences between VARI and NDVI here.
VARI algorithm used with an RGB camera.
Normalized Difference Vegetation Index (NDVI)
The traditional formula for NDVI compares Near Infrared and Red light. It is great for measuring healthy, green vegetation over a wide range of conditions.
Below is an NDVI map calculated with the standard formula. We'll use this to compare to the other formulas in order to present different aspects of your data.
Enhanced Normalized Difference Vegetation Index (ENDVI)
ENDVI includes a comparison of Green and Blue light in addition to the NIR and Red in order to give a more sensitive result. This isolates the indicators of plant health and can be used to assess the presence and health of a crop.
Notice the darker reds that create more contrast compared to the above NDVI image.
Green Normalized Difference Vegetation Index (GNDVI)
GNDVI is a modified version of the NDVI algorithm that combines Green and NIR light to better indicate the variation of chlorophyll content in the vegetation. It is also useful to analyze deficit/excess of water and nitrogen in the crop.
Soil Adjusted Vegetation Index (SAVI)
SAVI uses a soil brightness correction factor to analyze areas of the crop that are not covered with vegetation and the soil surface is exposed.
Optimized Soil Adjusted Vegetation Index (OSAVI)
OSAVI is a variation of SAVI, with a lower calibration factor. Using OSAVI, there is more variation with the soil than with SAVI, but it is also more sensitive to vegetation. In the example below, we see more subtle vegetation differences with OSAVI than with SAVI above. OSAVI would work well in an area with a dense canopy and a wider spectrum of vegetation.
OSAVI is more sensitive to vegetation than SAVI and would work well in denser canopies.
Renormalized Difference Vegetation Index (RDVI)
RDVI is similar to SAVI in that it suppresses the effects of soil and sun. Unlike SAVI, however, it does not work as well in sparsely vegetated or dry areas.
