Remote sensing and its application in agriculture

Remote sensing is the science of driving information about an object or phenomenon through analysis of data acquired by a device that is not in contact with object or phenomenon under investigation.

Remote sensing and its application in agriculture

Remote sensing is the collection of information about an object without being in direct physical contact with the object.

Since the Industrial Revolution, agriculture practices in developed countries have tended to support greater energy inputs using large machineries and increased applications of chemicals and fertilizers.

While these practices have negative societal and environmental implications such as;

  • Soil erosion and salinization
  • Soil fertility
  • Compaction of subsoils and soil
  • Water pollution

They have generally supported the food and fiber needs of a rapidly growing human population. A paradigm shift toward a new production method that ensures safe and sustainable agriculture is needed.

Across the globe, Precision Agriculture (PA) is changing the way people farm as it offers a myriad of potential benefits in profitability, productivity, sustainability, crop quality, environmental protection, on-farm quality of life, food safety and rural economic development.

Kinds of Remote Sensing:

  • Passive Remote Sensing:

Remote sensing systems which measure energy that is naturally available are called passive sensors. Passive sensors can only be used to detect energy when the naturally occurring energy is available. For all reflected energy, this can only take place during the time when the sun is illuminating the Earth.

There is no reflected energy available from the sun at night. Energy that is naturally emitted (such as thermal infrared) can be detected day or night, as long as the amount of energy is large enough to be recorded.

  • Active Remote Sensing:

Active sensors, on the other hand, provide their own energy source for illumination. The sensor emits radiation which is directed toward the target to be investigated. The radiation reflected from that target is detected and measured by the sensor. Advantages for active sensors include the ability to obtain measurements anytime, regardless of the time of day or season.

Active sensors can be used for examining wavelengths that are not sufficiently provided by the sun, such as microwaves, or to better control the way a target is illuminated. However, active systems require the generation of a fairly large amount of energy to adequately illuminate targets. Some examples of active sensors are a laser flourosensor and a synthetic aperture radar (SAR).

Types of remote sensing used in Agriculture

The most common types of remote sensing used in agriculture can be divided into four main categories of resolution, including spatial resolution, spectral resolution, radiometric resolution, and temporal resolution.

  • By Spatial Resolution:

In spatial resolution, information can be collected to identify physical traits in crops, such as size, relative distance and proximity patterns, height, width and diameter of plants, crop damage from pest infestation, weather, and more.

Spatial resolution is the distance between an image that is being observed, and the instrument that is sensing it. An easy example to help visualize the difference in spatial resolution is the difference between what an astronaut might see from space or a pilot can see from his or her plane. While a pilot might be able to distinguish houses or streets, the astronaut could most likely only see countries and continents.

Spatial resolution can help a farmer to get precise and high resolution pictures that show specific points on the field and show a smaller map-to-ground ratio. While on the other hand, spatial resolution can also show low resolution images that help to show the whole field or many fields at once, giving the farmer a more general idea the general state of his or her fields.

  • By Spectral Resolution:

Spectral resolution can collect information based on certain frequency ranges, including visible light, electromagnetic radiation, and non-visible light, such as infrared and near-infrared.

With spectral resolution, information can be collected regarding crop health by such determinations as the colour of leaves – bright green healthy leaves will have a different spectral wavelength than dying or decaying yellow or brown leaves. Nutrient concentrations within crops, such as Nitrogen and even moisture levels within the soil will also give of different spectral signatures.

By using these types of visual resolutions, a farm operator can determine the issues affecting their crops and apply appropriate remedies to affected areas. If spectral resolution has identified areas within the crop-field as having too little or too much of a given nutrient.

For example, farmers can apply less or more fertilizer to those areas as needed, as opposed to treating the entire field with an evenly metered dose. The same would be true for managing pest infestations with traditional pesticide treatments.

  • By Radiometric Resolution:

Radiometric resolution refers to the different levels of intensity that can be detected by a sensor. Usually the range of radiometric resolution is from 8 bit to 14 bit and 256 levels of grey scale to 16,384 diverse shades of color separately represented in each of the bands.

If radiometric resolution is used properly, it can be used to vastly help farmers by improving the image quality, accuracy, and readability so that aerial photographs and scans can be effectively used and understood

  • By Temporal Resolution:

Temporal resolution essentially refers to the time period over which data is collected. Longer collection periods will collect more data than shorter ones, thus providing more detailed patterns as they relate to nutrient and moisture loss, pest infestations, crop growth, and more.

Often there are factors that can make remote sensing difficult, things like clouds, storms, floods, and many others can get in the way. These factors can haze information and skew data, although when using temporal resolution these factors can be mitigated against.

When using a remote sensing system there are common trade-offs between the different resolutions. For example, if a farmer desired a much higher spatial resolution they would increase this by reducing the IFOV (Instantaneous Field of View).

If this were reduced it would decrease the ability to detect fine energy and therefore reduce the radiometric resolution and alter the image – making it hard to obtain data from. When using remote sensing there must be a balance between spatial resolution, spectral resolution, radiometric resolution, and temporal resolution – without its information that is collected could be inaccurate, or skewed.


 Proven benefits of airborne hyper spectral imaging monitoring and diagnostics of farmland include.

  1. Reduced chemical use due to optimum distribution of agrochemicals
  2. Decreased weed and disease-related losses due to early detection and timely treatment
  3. Reduced environmental impact
  4. Higher quality and healthier produce
  5. Better prediction and management of risks

When remote sensing produces precise prescriptions for precision agriculture, yields increase and expenses for chemicals, fertilizers, and water decrease. This combination results in higher profit margins for farmers and agricultural product.

Authors: Ali Hassan, Rana Abdul Qudoos, and Umer Hameed

Agro-climatology lab, Agriculture university Faisalabad.