Agricultural Applications of Remote Sensing April 2001

Chris J. Johannsen, Extension Agronomy Specialist

Introduction

Remote sensing technology has seen many changes in the past five years. Because of improvements in sensors, computer chips, software and services, agriculture is reaping benefits at ground and space altitudes. The term, “precision farming” has captured the essence of what is happening related to remote sensing but also that of other important technologies, namely geographic information systems (GIS) and global position systems (GPS). I personally don’t like the term, precision farming as it denotes a level of “preciseness” that we have yet to achieve. I prefer the term “site specific farming” but the news media says this term doesn’t have as much excitement to it. There are other terms such as “prescription farming,” and “variable rate technology” that are also used. I have also heard it incorrectly called “GPS” when referring to this technology. Whatever it is called, we are seeing an information revolution occurring and once farmers have been provided additional information about their crops, soil and land, they will keep asking for more!

We have literally taken "agriculture into the space age." Farmers now have services available that involve satellites collecting data, transmitting locational information, or providing data from a variety of sources. Some of these sources involve having sensors on their tractors, combines, and other equipment; receiving data from sensors on airplanes to aid in crop scouting; and receiving or analyzing satellite information. They can also rely on companies to do this all of these services for them for a fee.

Soil Properties or Soil Inventory

Soil investigations, surveys, and mapping are three types of applications using remote sensing information. They include three different approaches: the effects of soil properties on reflectance or image response, the influence of soil surface conditions on the response, and the use of imagery in mapping soil patterns. Satellite images from satellites such as the US Landsat and the French SPOT data can be used in assisting the development of soil surveys. Responses on these images can be related to soil properties such as organic matter content since the dark soils contrast to lighter soils (lower organic matter); iron oxides where variations in red vary with soil drainage and soil erosion can be distinguished by lighter areas within a mapping unit. Vegetation spectral response during the growing season can also be used to infer various soil conditions such as water holding capacity, erosion and organic matter content. Researchers have used vegetation responses to define management zones within fields. These zones are an aid to soil sampling as they may be used in “directed soil sampling” where one can select areas of similar patterns. The management zones would also become the basis for adjusting nutrient application rates using variable rate technologies.

Crop Stress

Crop stress occurs when the plants are subjected to conditions that alter growth patterns such as nutrient deficiency, soil erosion, damage from pests (weeds, insects and diseases) and weather damage such drought, standing water, wind, frost and hail. In most cases, these stresses cause anomaly or distinctly different patterns within the field. To determine the causes of stress takes a trained eye. When trying to identify these types of stress using remote sensing one can utilize some of the computer aided methods or simply use visual methods to discriminate. The ratio of the red response to the near-IR scene reflectance can indicate plant stress before it becomes evident on the ground.

A vegetation index (brightness or greenness) is a conversion of several spectral bands into one "index" number. Radiation as measured in thermal IR bands can indicate plant health conditions as plants under stress have lower evapotranspiration and therefore are warmer then well watered plants. Methods of detection may also include change detection (subtraction of one image from an earlier image to see where the vegetation changed) and vegetation classification methods to enhance or group areas that are similar. Identifying crop stress due to frost damage with the aid of Landsat TM or similar images has shown promise of being an affordable application if one can receive the image within a few days after it was collected. Methods have been developed to utilize color-infrared images to classify weeds in no-till cornfields and have been established to identify water stress in plants with the difference of remotely sensed surface temperatures and the measurement of ground based air temperatures.

Nutrient Detection

Using remote sensing information to detect field nutrient situations requires a thorough knowledge of what effects nutrient variations can have on the plant and of your soils. Soil characteristics such as soil color relate to organic matter content from which one can predict nitrogen release to the plant. Other soil properties such as pH, texture and nutrients such as phosphorous and potash are difficult to detect and almost impossible to measure remotely. Plant leaf greenness can be related to plant leaf chlorophyll content. Chlorophyll is directly related to plant nitrogen content. Discoloration such as plant leaf chlorosis of leaf margins is correlated to potassium deficiency while purplish leaves are correlated with phosphorous deficiency. Most of the nutrient work in remote sensing has focused on nitrogen. There have been some encouraging results. For instance in Iowa research, leaf color measurements made at ground level have correlated well with corn plant nitrogen status.

Images in the green response band and near infrared bands highlight the amount of vegetation and give an indication of plant vigor. Some companies have been providing “crop vigor” maps to farmers to assist them in seeing where vegetation growth is occurring and to determine areas within the field were vegetation is not progressing as it should. Change detection can be accomplished by overlaying images from two flight dates and showing the vegetation change occurring between the two dates. This information can be helpful for applying additional nitrogen or other nutrients.

Weather Data

The National Oceanic and Atmospheric Administration (NOAA) monitors the weather with the use of dedicated satellites and they have become very accurate at short-range prediction of weather. Through these predictions farmers are in a better position to manage many of their operations, such as hay production. In addition to aiding in weather prediction, satellite and ground radar data and can estimate weather variables like precipitation for particular points becoming virtual weather stations for a farmer's field. One example of how a farmer might access such data is a service offered by the EMERGE company. The service compiles information keyed to geographical location so that the farmer can acquire the weather data such as rainfall, growing degree days, minimum and maximum temperatures, etc. for each field or area.