Leveraging Satellite Imagery to Track Crop Health

By Laura Williams, Data Scientist

Leveraging Satellite Imagery to Track Crop Health

Data Solutions for the Agriculture Industry

Tracking plant health throughout the growing season is essential for a good crop yield. Monitoring disease, pests, weeds, weather conditions, damage, or any other uncontrollable factors affecting crop health allows farmers to intervene before irreparable damage can occur. Satellite imagery offers the ability to monitor the growth and overall health of crops across entire fields as well as smaller areas for site-specific management without the use of ground sensors, field surveyors, or other devices such as drones or other unmanned aerial vehicles (UAVs). Besides real-time field tracking, historical satellite images can be leveraged to make crop yield predictions and inform crop rotation and planning.

How satellite imagery allows farmers to discover and solve crop issues quickly

Leveraging Satellite Imagery for Crop Health - Data Solutions - Keiter Technologies

The Landsat 8 (launched in 2013) and 9 (launched in 2021) carry an Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) to capture images (725/day) of global landmass for a total of 13 spectral bands including the visible, infrared, near-infrared (NIR), short-wave infrared (SWIR) bands, a panchromatic (black and white) band, a band for detecting cirrus clouds, a band for coastal zone observations, and two thermal bands which cover spatial resolutions of 15, 30, and 100m.

Due to the structure and pigmentation of plants, different stages of plant growth and plant health can be determined by their reflectance (measurement of light energy at a given wavelength). For example, chlorophyll, the compound responsible for photosynthesis, strongly absorbs visible red light and the overall cellular structure of leaves reflects NIR light. To gleam insight into plant health and other land and plant-related factors influencing agriculture, spectral indices use combinations and/or ratios of various spectral bands to reflect different land and plant-based characteristics. There are many different indices used depending on which characteristics are of interest – including (but not limited to!) indices related to plant health, soil moisture levels, and cloud cover.

There are many vegetation indices widely used and reported in the literature to quantify and track plant health. Here are just a few examples:

  • Normalized difference vegetation index (NDVI)

    Used to estimate overall vegetation health during active crop growth by measuring photosynthetically active biomass in plants, NDVI employs a combination of the amount of absorbed visible red and reflected NIR light, as they are reflective of the amount of chlorophyll and strength of the plants’ cellular structure.

  • Normalized red edge vegetation index (NDRE)

    To estimate vegetation health during mid-to-late growing season when plants are mature, the normalized red edge vegetation index (NDRE) employs the NIR and red-edge (spectral band between visible red and NIR) bands to measure chlorophyll content of high-density canopy cover (upper plant layers).

  • The red-edge chlorophyll index (ReCI)

    This approach also uses the NIR and red-edge bands to measure chlorophyll content during mid-to-late growing season in terms of photosynthetic activity during active growth and vegetation stages, as it reflects levels of nitrogen nourishment, directly responsible for chlorophyll content.

The NDVI is one of the most commonly used vegetation indices. However, its value reaches a saturation point during the mid-late growing season (near/at maturation) when visible red absorbance reaches a maximum (for example, when plants develop several layers of green canopy) while the NIR reflectance continues to increase, causing the NDVI to lose reliability as an indicator of crop health.

To estimate vegetation health during mid-to-late growing season when plants are mature, the NDRE and ReCI employ the NIR and red-edge (spectral band between visible red and NIR) bands to measure chlorophyll content of mature plants and high-density canopy cover (upper plant layers). Though both indices measure chlorophyll content, they are calculated differently and the NDRE is more sensitive to leaf area than the ReCI. For example, the ReCI tends to be more useful for vineyards and orchards and the NDRE for row crops.

While there are many other vegetation indices used to track plant health and other related factors, the NDVI, ReCI, and NDRE highlight the way information from just a few satellite spectral bands can actively provide a lot of insight into overall crop health and nitrogen levels throughout the season. This allows farmers to discover issues in their fields and deploy solutions quickly, all without constant equipment monitoring, field surveyors, or UAVs.

Interested in learning how satellite imagery can help your agriculture business? Contact the Keiter Technologies team. We are here to provide innovative data solutions to help your business improve processes and drive growth.

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About the Author

Laura Williams

Laura Williams, Data Scientist

Laura leverages her education and experience in statistics, mathematics, and research to tackle a variety of business problems with data-driven solutions. Her client service approach includes forming a thorough understanding of a client’s project goals and data to provide well-informed insights and solutions.

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The information contained within this article is provided for informational purposes only and is current as of the date published. Online readers are advised not to act upon this information without seeking the service of a professional accountant, as this article is not a substitute for obtaining accounting, tax, or financial advice from a professional accountant.


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