Remote Sensing

As turfgrass managers, you are continually monitoring fertilization and irrigation programs to ensure optimal visual quality while minimizing losses to the environment and maximizing profit. This requires much time and attention due to the wide variability in soil type and soil quality that exists on many turfgrass sites. In many cases, when nutrient deficiency symptoms appear, blanket applications of fertilizer are applied to correct them. This disregards the fact that surrounding areas may have adequate nutrient reserves and may not require fertilization for some time. You could collect soil and tissue samples throughout the site on a regular basis and submit them for analysis by a laboratory, but that is very labor intensive, expensive and is subject to a delay between sample collection and receiving the results.

When it comes to irrigation, many turfgrass managers prefer to err on the side of applying too little water versus over-watering to avoid the associated problems with disease. To do this effectively, you are required to spend a significant amount of time scouting the site for signs of drought and making the required changes to the irrigation programs. You may have wondered at some point if there was any way to collect information about the nutrient and moisture status of the site without spending all of your time scouting. This would free time for more important things like managing employees and maintaining public relations with the membership.


Remote sensing may prove a possible solution to this problem. Remote sensing is defined as the collection of information from an object without physical contact with that object. There are three main levels from which remote sensing data can be obtained: satellite imagery, aerial photography and ground-based systems. One of the most prominent uses of remote sensing in our daily lives is the use of satellite imagery by local meteorologists in the evening weather forecast. In addition to the weather satellites, there are numerous commercial and government owned satellites in orbit that make regular observations of the Earth's surface, collecting information in the form of photographs, infrared imagery, spectral reflectance, etc. Before you run out to buy a satellite image for a bird's eye view of the golf course, take into consideration the resolution and usefulness of the images that are available. Most images will cost between $200 and $600 each and have a resolution (pixel size) of 15 to 30 meters, which is too coarse in many cases to be useful in turfgrass situations. There are images available with resolutions of less than one meter, but they can be very expensive. The frequency of availability for new pictures depends upon the provider, but is usually once every 2 to 4 weeks, which may not be adequate for monitoring the moisture status of turfgrass systems. In addition, there is no guarantee that the image will be useful. If it happens to be a cloudy day when the satellite passes overhead, you will not be able to use the image. It is obvious to see that satellite imagery is not a practical and reliable tool for use in managing most irrigation and fertility programs.

Aerial photography has a higher resolution (1 to 2 feet or less) and is cheaper than satellite imagery. However, you will face many of the same limitations in terms of shade and cloud cover. Shaded areas often appear to be black in satellite images and aerial photographs and provide no information about the current status of the turfgrass plants growing in those areas. This brings us to ground-based remote sensing systems. These are better able to account for differences in light intensity due to shade, either through measuring the incident radiation or blocking it out completely and providing an auxiliary light source. In all cases, data are acquired from the area of interest either through some form of photography or multi-spectral radiometry. Multi-spectral radiometry evaluates the amount of electromagnetic energy that is being reflected at particular wavelengths.


There have been a number of chlorophyll meters on the market in recent years that measure the “greenness” of the turfgrass stand by measuring the reflectance of light at two wavelengths, which is in turn related to the chlorophyll content of the plants. Handheld chlorophyll meters are subject to variability resulting from changes in light intensity from shade, cloud cover and sun intensity. While the chlorophyll content can be related to the nitrogen status in the plant, you should be careful basing fertility programs on these readings. Handheld chlorophyll meters are very useful for collecting quantitative visual quality data, which can be used to track changes over time. Research has shown that changes in nitrogen fertility have an impact on the entire reflectance spectrum of plants, which has led researchers to investigate this relationship in more detail.

In our study, we set out to determine if a ground-based spectrometer utilizing an auxiliary light source could be used to accurately detect deficiencies in moisture and nutrition. To do this, we used an Ocean Optics, Inc. S2000 fiber-optic spectrometer with the sensor mounted inside a black box to block out ambient sunlight. Two halogen automotive fog lights were used to provide a consistent energy source for collecting data. This construction allowed us to limit the variability in our data set that can result from changes in light due to shade and cloud cover. The radiance values collected by the spectrometer are expressed at percent spectral reflectance at each wavelength after calibration with a white standard.

Two separate studies were conducted — one to evaluate the remote sensing system for predicting moisture stress, and one for nitrogen stress. The moisture study was conducted on the fairways at Veenker Memorial Golf Course, and the nitrogen study was conducted on a United States Golf Association (USGA) green at the Iowa State University Horticulture Research Station, both located near Ames, Iowa.

The following previously published vegetative indices were calculated using the percent reflectance (R) at the indicated wavelengths and evaluated to determine which ones were best able to predict the nitrogen and/or moisture status:

Normalized Difference Vegetation Index (NDVI) growth indice computed as (R800 - R600/R800 + R600)

Infrared/Red (IR/R) stress indice computed as R780/R600

Far Red/Infrared (FR/IR) stress indice computed as R695/R760

Water Band Index (WBI) stress indice computed as R970/R902

Water Index 1 (WI1) stress indice computed as R895/R972

Water Index 2 (WI2) stress indice computed as R900/R1200

In addition to the previously mentioned vegetative indices, we are investigating new ways of analyzing the reflectance data to identify relationships between specific deficiencies and the associated plant response. These have included using new wavelengths from the reflectance spectrum and using the area under the reflectance curve in hopes of increasing our ability to pinpoint specific problems.


In analyzing the results, it is important to keep in mind that the success of a remote sensing system depends on its ability to accurately identify turfgrass areas deficient in nutrients or moisture prior to the onset of visual symptoms. The true value in using these systems will be in their ability to save you time scouting for problems. We designed these studies to establish a range of plant responses, which were then correlated to the reflectance readings. Results indicate that there is a significant relationship between the nitrogen concentration in the plant tissue and the NDVI, IR/R and FR/IR indices at three out of the five sampling dates in 2002. We also observed strong relationships between the vegetative indices and the turfgrass quality, biomass production and chlorophyll content.


There are many different computerized irrigation systems available to turfgrass managers. While some of these are used to control pumps and traditional multi-head zone systems, others are capable of controlling each irrigation head individually. Turfgrass managers are able to monitor sites for signs of drought and make adjustments to the heads in areas that may be too dry or too wet. However, this requires a significant amount of time scouting and making adjustments in the computer system. Some of the newer technology available allows you to use a handheld computer complete with a map of the course and the irrigation system installed. This allows for adjustment of the irrigation rates of specific heads while you are out scouting the course. All of the changes are then uploaded to the irrigation control computer once you have synchronized it with the handheld computer. There has been a lot of interest in developing a remote sensing system to monitor the moisture status of the turfgrass on a regular basis, thus reducing the guesswork involved in deciding how much water needs to be applied each day. Preliminary results from our work indicate strong relationships between the vegetative indices being studied, the volumetric soil moisture content as measured via time domain reflectometry (TDR) and turfgrass quality.


In the future, remote sensing systems will be coupled with a Global Positioning System (GPS), which will track and record the location of the sensor on the Earth's surface. Using the location information, maps can be created indicating the areas that are stressed allowing for site-specific applications of fertilizer and water to be made to the golf course, thus improving the nutrient and water use efficiency and reducing environmental impacts. With the current interest in remote sensing technology and its potential to have a widespread impact on turfgrass management, you can expect to see several commercial offerings in the coming years.

Jason Kruse is a graduate student and Nick Christians, Ph.D., and Mike Chaplin, Ph.D., are professors of turfgrass science in the Department of Horticulture at Iowa State University (Ames, Iowa).

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