Remote sensing, GIS and GPS in Agriculture
What is remote sensing?
“Remote” means away.
Remote sensing involves detecting or perceiving objects or phenomena from a distance, utilizing three of our primary senses.
- For instance, observing a football game from afar utilizes our sense of sight
- Detecting the aroma of freshly baked bread from a distance employs our sense of smell
- Hearing a telephone ring from another room or location engages our sense of hearing.
Remote sensing is the process of capturing images of the Earth’s surface, oceans, and atmosphere using the electromagnetic spectrum.
Remote sensing platforms
1. Ground-based platforms: These are remote sensing devices that are placed on or near the earth’s surface. Cameras, radars, and lidars are examples of such devices.
2. Airborne platforms: These are remote sensing devices used by aeroplanes or other aircraft. Cameras, radar systems, and spectrometers are examples of devices that can be used for a variety of applications such as environmental monitoring, mapping, and surveillance.
3. Space-based platforms: These are satellites that collect data and images from space. Satellites, which can be placed in low-earth, medium-earth, or geostationary orbits and provide continuous monitoring of the Earth’s surface, oceans, and atmosphere, are among them. Other devices, such as space shuttles, can also be included in space-based platforms.
Satellite Characteristics: Orbits and Swaths
- As a satellite revolves around the Earth, the sensor “sees” a certain portion of the Earth’s surface.
Two important characteristics of a satellite for remote sensing are its orbit and swath.
1. Orbit: The orbit of a remote sensing satellite determines its coverage area and frequency of imaging. There are three main types of orbits used for remote sensing satellites:
- Polar Orbit
- Sun-Synchronous Orbit (SSO)
- Geostationary Orbit (GEO)
2. Swath: The swath of a remote sensing satellite is the width of the area on the Earth’s surface that the satellite can image in a single pass. The swath of a satellite is determined by its altitude, sensor design, and scanning mechanism. A wider swath allows for larger areas of the Earth’s surface to be imaged in a single pass but may result in lower spatial resolution.
Types of Orbits that Satellites Can Be Placed
There are several types of orbits in that satellites can be placed. Here are four common types:
1. Sun-Synchronous Polar Orbit
- A sun-synchronous polar orbit is a type of polar orbit that is synchronized with the Earth’s rotation around the sun.
- Earth imaging satellites mostly follow a polar orbit, where they move in a north-south direction around the planet while the Earth rotates underneath them.
- Satellites in polar orbit cover the Earth’s surface at a constant local sun time, allowing for consistent lighting conditions for imaging.
- The typical altitude range for polar-orbiting satellites is between 500 to 1,500 kilometres.
2. Non-Sun-Synchronous Orbit
- Satellites in non-sun-synchronous orbits provide coverage over regions with different latitudes, including the tropics, mid-latitudes, and high latitudes. This leads to the varying sampling of the Earth’s surface.
- The typical altitude range for satellites in non-sun-synchronous orbits is between 200 to 2,000 kilometres.
- An example of a satellite in a non-sun-synchronous orbit is TRMM.
3. Geostationary Orbit
- Satellites in geostationary orbits are placed at a very high altitude of around 36,000 kilometres above the Earth’s surface.
- These satellites are designed to view the same portion of the Earth’s surface at all times and appear stationary due to their speed of revolution, which matches the rotation of the Earth.
- Geostationary satellites are primarily used for weather monitoring and telecommunications.
Types of remote sensing
Passive remote sensing
- Passive remote sensing systems measure the energy that is naturally available. For example Sun
- This can only take place during the time when the sun is illuminating the Earth.
Active remote sensing
- Active remote sensing uses its own energy source for illumination, unlike passive remote sensing.
- The sensor emits radiation that is aimed at the target being investigated.
- The sensor then detects and measures the radiation reflected from the target.
- Active remote sensing can obtain measurements at any time, regardless of the time of day or season.
Process of Remote Sensing
(A) Energy source or illumination: To illuminate the target area or object, an external energy source is used. This can be natural light or a man-made source such as radar.
(B) Radiation and the atmosphere: Radiation interacts with the atmosphere, where it can be absorbed, scattered, or reflected. The type of interaction is determined by the energy’s wavelength and the atmospheric conditions.
(C) Interaction with the target: Unabsorbed or scattered energy interacts with the target object or surface, where it can be reflected, transmitted, or absorbed.
(D) Energy recording by the sensor: A remote sensing sensor detects energy that is reflected, transmitted, or absorbed. The sensor saves the energy as an image or video.
(E) Data transmission, reception, and processing: The recorded data is sent to a ground station, where it is received and converted into a usable format.
(F) Analysis and interpretation: The processed data is interpreted and analyzed to extract meaningful information about the target object or surface.
(G) Application: Remote sensing data is used in a variety of fields, including agriculture, forestry, geology, and urban planning.
Radiation – Target Interactions
When energy strikes or falls on a surface, it can interact with the target in three ways:
1. Absorption (A) – the target absorbs the energy.
2. Transmission (T)
3. Reflection (R) is the process by which energy is reflected back to the sensor.
Specular reflection: When radiation strikes a smooth surface, such as a calm body of water or a mirror-like surface, it reflects in only one direction. According to the law of reflection, the angle of incidence of the radiation equals the angle of reflection.
Diffuse reflection: When radiation strikes a rough or irregular surface, such as a forest canopy or rocky terrain, it reflects in multiple directions, resulting in diffuse reflection. Because the radiation is scattered, the angle of incidence does not always equal the angle of reflection.
Types of Resolution
Radiometric resolution: The ability of a sensor to distinguish between minor differences in the energy of incoming radiation is referred to as radiometric resolution.
Spatial resolution: The smallest discernible ground area that a sensor can distinguish between is measured in meters or feet.
Spectral resolution: The ability of a sensor to distinguish between different wavelengths or colors of the electromagnetic spectrum is referred to as spectral resolution.
Temporal resolution: The time interval between image acquisitions of the same location by a satellite or sensor is referred to as temporal resolution.
Interpretation of Images
An image is a graphic representation of an object or scene.
Image examples include:
- Photographic sensors produce analog images on paper or transparent media.
- Variations in scene characteristics are represented as variations in brightness (grey shades)
- Objects reflecting more energy appear brighter on the image and objects reflecting less energy appear darker.
- Pixels are square or rectangular areas that make up a digital image.
- Each pixel has a pixel value known as a Digital Number (DN), Brightness value (BV), or grey level that is determined by the amount of reflected energy from the ground.
- An object that reflects more energy receives a higher digital number on the digital image, and vice versa.
Visual Elements of Remote Sensing
The visual elements of remote sensing are:
1. Tone or brightness: The relative brightness or colour of objects in an image is referred to as tone.
2. Saturation or purity: The degree of concentration of a hue or colour in an image, ranging from vivid to pale, is referred to as saturation or purity.
- A pattern is defined as an orderly repetition of similar tones and textures that results in a distinct and ultimately recognisable pattern.
- Patterns can be seen in orchards with evenly spaced trees and urban streets with regularly spaced houses.
- The arrangement and frequency of tonal variation in specific areas of an image are referred to as texture.
- Smooth textures are typically produced by uniform, even surfaces such as fields, asphalt, or grasslands.
- Rough textured structures, such as a forest canopy, are represented by rough texture.
5. Size or scale
- The size of objects in an image is a function of scale.
- If an interpreter had to distinguish zones of land use and had identified an area with a number of buildings in it.
- Large buildings such as factories or warehouses would suggest commercial property, whereas small buildings would indicate
6. Shape or form
- Shape refers to the general form, structure, or outline of individual objects.
- The shape can be a very distinctive clue for interpretation.
- Straight edge shapes typically represent urban or agricultural (field) targets, while natural features, such as forest edges, are generally more irregular in shape.
- Farm or cropland irrigated by rotating sprinkler systems would appear as circular shapes
7. Shadow or tone relief
- A target’s relative height can be determined by its shadow.
- Shadows can also reduce or eliminate interpretation in their field of influence because targets in shadows are much less (or not at all) distinguishable from their surroundings.
- Association considers the relationship between other recognisable objects or features near the target of interest.
- Proximity to major transportation routes may be associated with commercial properties.
- Schools, playgrounds, and sports fields would be associated with residential areas.
The unique pattern of reflected or emitted electromagnetic energy at different wavelengths that is characteristic of a particular material or feature on the Earth’s surface is referred to as a spectral signature. Remote sensing scientists can identify and map land cover types, geologic formations, and other features of interest by analysing spectral signatures. Typically, spectral signatures are represented graphically as a plot of reflectance or radiance values at various wavelengths.
Spectral Signature for Vegetation
- The spectral signature for vegetation typically shows high reflectance in the near-infrared portion of the electromagnetic spectrum and low reflectance in the visible blue and green portions of the spectrum.
- This is due to the strong absorption of blue and green wavelengths by chlorophyll and the high reflectance of near-infrared wavelengths by plant cell structures.
- The primary difference in leaf reflectance between species is determined by leaf thickness.
- Canopies of needle-leaf trees reflect significantly less near-infrared radiation than those of broad-leaf vegetation.
- Immature leaves have less chlorophyll than mature leaves and reflect more visible light while reflecting less infrared radiation.
- The health of the vegetation also has an impact on reflectance.
Normalized Difference Vegetation Index (NDVI)
- This index is calculated by dividing the difference between near-infrared and red reflectance by the sum of those two values.
[NDVI = (NIR-Red) / (NIR-Red)]
- It receives values from -1 (no vegetation) to +1 (abundant vegetation).
Normalised Difference Water Index
- It employs the near-infrared band and a band in the shortwave infrared (SWIR)
- Instead of using the red band, a short-wave infrared band in the region between 1500 and 1750 nm is used where water has high absorption.
[ NDWI = (NIR – SWIR) / (NIR + SWIR) ]
Spectral Signature for Soil
The five characteristics of soil that determine its reflectance properties are, in order of importance:
- Moisture content
- Organic content
- Iron oxide content
Soil Moisture Content
- Wet soil generally appears darker.
- Increasing soil moisture content lowers reflectance.
Soil Organic Matter
- A soil containing 5% or more organic matter is typically black in colour.
- Organic materials that are less decomposed have higher reflectance and vice versa.
Soil Iron Content
- The presence of iron, particularly iron oxide, has an effect on spectral reflectance.
- Reflectance decreases in the green region as iron content increases but increases in the red region.
- (a) High organic content, moderately fine texture.
- (b) Low organic, Low iron content.
- (c) Low organic, medium iron content.
- (d) High organic content, moderately coarse texture.
- (e) High iron content, fine texture.
- Clay soil has a strong structure, which results in a rough surface when ploughed.
- Clay soils also have a high moisture content and, as a result, a low diffuse reflectance.
- Sandy soils have a low moisture content and, as a result, have fairly high and frequently specular reflectance properties.
Spectral signature for water
Reflection of Light – Wavelengths
- Water Depths – Shallow, Deep
- Suspended material
- Chlorophyll Content
- Surface Roughness
The majority of radiant flux incident upon the water is either not reflected but is either absorbed or transmitted.
In visible wavelengths of EMR, little light is absorbed, a small amount, usually below 5% is reflected and the rest is transmitted.
Water absorbs NIR and MIR strongly leaving little radiation to be either reflected or transmitted. This results in the sharp contrast between any water and land boundaries.
Spectral Reflectance of Snow
Snowpack thickness: As snow ages, its reflectance decreases.
The amount of liquid water in the snow: Even slightly melting snow reduces reflectance.
Contaminations (soot, particles, and so on) reduce snow reflectance.
Remote Sensing Applications in Agriculture
- A sufficient supply of high-quality agricultural crops is critical for feeding the world’s population. Water availability, nutrient levels, weather, and pests all have an impact on crop growth.
- Remote sensing helps to monitor crops by providing data on these factors. These data can be combined with other information in Geographical Information Systems to aid in agricultural decision-making.
- Individual farmers use remote sensing data to assess crop health and deal with problems, while national governments use it to inform agricultural policies.
- The Indian Remote Sensing Satellite (IRS) series, which includes Resourcesat, Cartosat, and Oceansat, provides critical data for a variety of agricultural projects in India.
Monitoring of Crop Status
- When a plant experiences stress, its normal growth process can be disrupted.
- When a plant is stressed, it is not functioning properly due to one or more causes.
- When a plant is stressed, it usually exhibits visible symptoms as well as some that are not visible to the naked eye.
- Depending on the cause, stress symptoms may appear in all or only some of the plants in the field.
Crop Yield Forecasting
- To make future crop yield estimates based solely on remote sensing data, we must first understand the relationship between vegetation indices at a specific crop growth stage and crop yield.
- This purpose is served by historical data from previous growing seasons, and the accuracy of crop yield prediction increases as the amount of historical data increases.
- Growing seasons, on the other hand, are never the same. To make more accurate predictions, consider the factors that influence crop growth and yield in the current year.
- Meteorological and climatic data, soil properties, and farming practices are combined with current remotely sensed data to model crop growth and make estimates on final crop yield.
- It is very important for a national government to know what crops the country is going to produce in the current growing season.
- This knowledge has financial benefits for the country, as it allows the budget planning for importing and exporting food products.
- One method is for someone to travel around the country and see what crop is grown in each field. But this takes too much time and costs a lot of money.
- Because the vegetation cover of each crop changes at different rates, it is possible to identify the different crop types by using multi-date data (data from different dates) from the same growing period.
- Furthermore, the planting and harvesting dates differ.
- We can distinguish and identify different crops by combining this information with remote sensing data.
GPS (Global Positioning System)
GPS is short for Global Positioning System which is “a network of satellites that continuously transmit coded information, which makes it possible to precisely identify locations on earth by measuring the distance from the satellites”.
Example: Global Positioning System (GPS): An agricultural producer may use a handheld GPS receiver to determine the latitude and longitude coordinates of a water source next to a field or vineyard.
GPS data gathering
GPS receivers can collect information such as: depending on the make and model of the unit, the number of satellites available, and the quality of (unobstructed) signals, GPS receivers can collect information such as:
- Coordinates of latitude and longitude (time-in-place or point location).
- Position “Real Time” (calculated while farm equipment is moving).
- Elevation (if at least four satellites are used).
Basic Information Provided by GPS Receivers
1. Location: Using GPS satellite signals, the GPS receiver calculates the user’s latitude, longitude, and altitude.
2. Speed: The GPS receiver can determine the user’s speed and direction of travel by measuring changes in location over time.
3. Time: GPS receivers provide precise time information by synchronising with GPS satellite atomic clocks.
4. Distance: By measuring the distance between the user’s current location and a destination, the GPS receiver can provide information on the distance remaining to reach the destination.
5. Direction: The GPS receiver can provide information on the user’s heading or direction of travel, as well as the route to a specific destination.
6. Navigation: Many GPS receivers include mapping software, which allows users to view maps, create routes, and receive turn-by-turn directions.
GIS (Geographic Information System)
Geographic Information System is abbreviated as GIS (s). “In the strictest sense, a GIS is a computer system capable of assembling, storing, manipulating, and displaying geographically referenced information, i.e. data identified according to their locations. Practitioners also regard the total GIS as including operating personnel and the data that go into the system”.
Example: GIS system can reveal environmentally-sensitive areas that should be protected during response and recovery phases.
GPS/GIS Applications in Agriculture
- Position data (georeference data) is recorded at predetermined intervals.
- Other data is recorded manually or automatically by a monitor, computer, or data logger.
- Data is displayed by the geographic information system (GIS) in thematic map format.
- Georeferenced soil samples can be collected.
- Sampling Methods.
- Grid sampling: an intensive sampling of the entire field.
- Directed sampling: an intensive sampling of particular target areas.
- Record of spatial yield variability within a field or farm.
- GPS data coupled with yield data to produce a map.
- Mechanically harvested
- Hand harvested
- A useful tool for decision-making.
- Fields can be scouted for a variety of pests.
- Pest populations recorded on maps.
- Decision tools can be applied on a site-specific basis.
Precision Agriculture is a farming management concept that uses advanced technology and data analysis to optimize crop production. The goal of precision agriculture is to increase crop yields while reducing costs and minimizing environmental impact. This can be achieved by using high-tech tools such as GPS, sensors, drones, precision planting and harvesting equipment, and other forms of remote sensing. By using this technology, farmers can collect and analyze data on things like soil moisture, crop growth, and weather patterns, to make more informed decisions about planting, fertilizing, and harvesting their crops.
GPS and GIS Difference
- GPS (Global Positioning System) and GIS (Geographic Information System) are two technologies that are frequently used in tandem, but they serve distinct functions.
- GPS is a satellite-based navigation system that allows us to track and accurately locate objects or people in real-time.
- A geographic information system (GIS) is a computer-based system that analyses, manages, and visualises geographic data.
- It combines spatial and non-spatial data to generate maps, charts, and other visual representations for a variety of purposes such as urban planning, natural resource management, and environmental analysis.
- The primary distinction between the two is that GPS provides precise location data, whereas GIS is a data analysis and decision-making tool. Both technologies are critical in a variety of fields, including emergency services, logistics, transportation, agriculture, and surveying, among others.
Conclusion of Remote Sensing and GPS/GIS
- Remote sensing technology can be used to assess various crop stresses, whether biotic or abiotic.
- Remote sensing is a critical tool in crop management, providing high-resolution solutions even in small land areas.
- It is possible to distinguish between crops based on their reflectance characteristics, allowing for informed policymaking.
- Ground-based and satellite-based remote sensing is useful for forecasting crop yields and making informed decisions.
- Microwave remote sensing can be used to assess nutrient and moisture levels at different times and spatial scales.
1. How does remote sensing work? Remote sensing involves capturing images or data from a distance using various sensors and platforms, such as satellites, aircraft, or ground-based devices. These sensors measure energy interactions with the Earth’s surface and atmosphere to provide valuable information.
2. What is the difference between passive and active remote sensing? Passive remote sensing relies on naturally available energy sources, such as sunlight, while active remote sensing uses its own energy source, emitting and measuring radiation directed at the target.
3. How is remote sensing used in agriculture? Remote sensing aids in monitoring crop health, forecasting yields, identifying crop types, and optimizing farming practices, contributing to increased agricultural productivity.
4. What is the significance of GPS in agriculture? GPS provides precise location data, helping farmers with navigation, mapping, and efficient management of farming operations.
5. How can GIS benefit agriculture? GIS enables farmers to analyze and visualize geographic data, aiding in field mapping, soil sampling, crop scouting, and decision-making for better agricultural practices
Hello, I am Sonu Verma, M.Sc. (Horti.) Agriculture content writer, and an enthusiast who loves to share knowledge. No Culture Without Agriculture.