Over the past few decades, there has been a significant increase in the number of indices which exist to measure the health of plants and vegetation through digital imaging. A number of these indices can be categorized into six major categories: broadband greenness, narrowband greenness, light use efficiency, dry carbon, leaf pigment, and canopy water content. Because each category is quite broad and complex, this blog will focus on broadband greenness and the visual indices (VI) found in this category.
Broadband Greenness – A broad spectrum approach
The category for broadband greenness encompasses, as the name suggests, a broad spectrum approach to the reflectance of vegetation to determine its health. The indices found in this category measure combinations of reflectance from the foliage in specific ranges of wavelengths in an attempt to determine the chlorophyll concentration found in the vegetation. The determination of a plant’s concentration of photosynthetic material is key in determining its health and potential growth capabilities. By measuring the vegetation’s reflectance of green and near infrared (NIR) wavelengths and comparing it to the plants absorption bands (blue and red) a number of health ratios can be calculated depending on the wavelengths observed. Such ratios, or Visual Indices (Vis), include: the Normalized Difference Vegetation Index (NDVI), the Enhanced Normalized Difference Index (ENDVI), the Enhanced Vegetation Index (EVI), the Chlorophyll Vegetation Index (CVI), and the Triangular Vegetation Index (TVI), to name a few.
These VIs use a combination of the red, green, blue, and NIR bands of light that are reflected from the vegetation to provide differing sets of information to determine the plant’s health. The most accurate method to measure broadband greenness VIs is to use one monochrome camera and a corresponding filter for each band to be computed by the index’s equation. The images are then co-registered via software and run through the index’s equation to determine plant health. They are then falsely colored using a lookup table resembling a heat map to illustrate healthy vegetation and pinpoint areas where growth is suboptimal.
NDVI – A well-known VI
Taking a closer look at some of the indices mentioned above, NDVI is perhaps the most well-known of all the VIs as it is a simple and effective approach for analysis of green vegetation. For more information about NDVI, consult the Lumenera Solution Sheet: How to Perform Vegetation Analysis With a Single Camera . Moving to some lesser known indices, ENDVI (Extended NDVI) is a more computationally intensive rendition of NDVI which takes into account the blue, green, and NIR bands. As mentioned earlier, this index is best calculated using three monochrome cameras with each one equipped with a filter to target a specific channel. However, recent developments by Midwestern Optical Systems allow this index to be covered with a single color camera equipped with a triple bandpass filter targeting 475 nm, 550 nm, and 850 nm wavelengths.
The aforementioned Lumenera Solution Sheet on NDVI covers similar filter algebra in detail and highlights that by removing the color camera’s NIR blocking filter and combining the response of the color camera with a triple bandpass filter, each color channel of the camera is responsible for reporting on one of the three targeted wavelengths. The data is then input into the ENDVI equation to produce a normalized index from -1 to +1 which is then color-coded to represent the health of the vegetation.
EVI – An interesting alternative
Another approach can be explored by using the enhanced vegetation index (EVI) in areas of dense foliage. It leverages the information in the blue band to further enhance NDVI calculations by correcting for atmospheric influences and soil background signals. EVI also uses a false-colored representation of the data ranging between -1 and +1.
For more information on cameras capable of performing precision agriculture or measuring vegetation indices, please contact Lumenera’s imaging experts. They can help with selecting the cameras to best meet your requirements, and they can also help with understanding what kind of camera customizations are possible to help optimize your particular solution (e.g. replacing the NIR cut filter on a color camera with a built-in dual bandpass or triple bandpass filter). Reach out at firstname.lastname@example.org..
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