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Remote Sensing Applications for Agriculture and Land Use Management and Mapping | Auracle Geospatial Science, Inc. News
Remotely sensed images can be used to identify nutrient deficiencies, diseases, water deficiency or surplus, weed infestations, insect damage, hail damage, wind damage, herbicide damage, and plant populations.
QUALICUM BEACH, BC, CANADA, September 17, 2011 /Canada PR News/ -- Information from remote sensing can be used as base maps in variable rate applications of fertilizers and pesticides. Information from remotely sensed images allows farmers to treat only affected areas of a field. Problems within a field may be identified remotely before they can be visually identified.
Ranchers use remote sensing to identify prime grazing areas, overgrazed areas or areas of weed infestations. Lending institutions use remote sensing data to evaluate the relative values of land by comparing archived images with those of surrounding fields.
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Around the world, agricultural practices have developed as a function of topography, soil type, crop type, annual rainfall, and tradition. In this montage of six ASTER sub-images, the differences are graphically illustrated by the variation in field geometry and size. In Minnesota (upper left) the very regular grid pattern reflects early 19th century surveying; the size of the fields is a function of mechanization and that dictates a certain efficiency. In Kansas (upper middle), center pivot irrigation is responsible for the field pattern. In northwest Germany (upper right), the small size and random pattern of fields is a leftover from the Middle Ages. Near Santa Cruz, Bolivia (lower left), the pie or radial patterned fields are part of a settlement scheme; at the center of each unit is a small community. Outside of Bangkok, Thailand (lower middle), rice paddies fed by an extensive network of canals that is hundreds of years old, appear as small skinny rectangular fields. And in the Cerrado in southern Brazil (lower right), cheap cost of land and its flatness have resulted in enormous farms and large field sizes.
The Electromagnetic Spectrum
The basic principles of remote sensing with satellites and aircraft are similar to visual observations. Energy in the form of light waves travels from the sun to Earth. Light waves travel similarly to waves traveling across a lake. The distance from the peak of one wave to the peak of the next wave is the wavelength. Energy from sunlight is called the electromagnetic spectrum.
The wavelengths used in most agricultural remote sensing applications cover only a small region of the electromagnetic spectrum. Wavelengths are measured in micrometers (µm) or nanometers (nm). One um is about .00003937 inch and 1 µm equals 1,000 nm. The visible region of the electromagnetic spectrum is from about 400 nm to about 700 nm. The green color associated with plant vigor has a wavelength that centers near 500 nm.
Remote Sensing for Agriculture and Land Use Wavelengths longer than those in the visible region and up to about 25 µm are in the infrared region. The infrared region nearest to that of the visible region is the near infrared (NIR) region. Both the visible and infrared regions are used in agricultural remote sensing.
Electromagnetic Energy and Plants
When electromagnetic energy from the sun strikes plants, three things can happen. Depending upon the wavelength of the energy and characteristics of individual plants, the energy will be reflected, absorbed, or transmitted. Reflected energy bounces off leaves and is readily identified by human eyes as the green color of plants. A plant looks green because the chlorophyll in the leaves absorbs much of the energy in the visible wavelengths and the green color is reflected. Sunlight that is not reflected or absorbed is transmitted through the leaves to the ground.
Interactions between reflected, absorbed, and transmitted energy can be detected by remote sensing. The differences in leaf colors, textures, shapes or even how the leaves are attached to plants, determine how much energy will be reflected, absorbed or transmitted. The relationship between reflected, absorbed and transmitted energy is used to determine spectral signatures of individual plants. Spectral signatures are unique to plant species.
Remote sensing is used to identify stressed areas in fields by first establishing the spectral signatures of healthy plants. The spectral signatures of stressed plants appear altered from those of healthy plants.
Stressed sugarbeets have a higher reflectance value in the visible region of the spectrum from 400-700 nm. This pattern is reversed for stressed sugarbeets in the nonvisible range from about 750-1200 nm. The visible pattern is repeated in the higher reflectance range from about 1300-2400 nm. Interpreting the reflectance values at various wavelengths of energy can be used to assess crop health.
The comparison of the reflectance values at different wavelengths, called a vegetative index, is commonly used to determine plant vigor. The most common vegetative index is the normalized difference vegetative index (NDVI). NDVI compares the reflectance values of the red and NIR regions of the electromagnetic spectrum. The NDVI value of each area on an image helps identify areas of varying levels of plant vigor within fields.
APPLICATIONS OF REMOTE SENSING/GIS:
Inventory and mapping of Agricultural lands.
Assessment of changes in Agricultural land.
Assessment of irrigated agricultural land.
Crop inventory, crop hectarage assessment, crop yield estimate.
Soil categorization and mapping.
Assessment of degraded lands.
Land capability/suitability assessment.
Early detection of crop diseases.
Food security arrangement.
Monitoring of crop conditions including weed, herbicide and fertilizer misapplication.
Estimation of Agrometeorology parameters (rainfall amount and period, temporal).
Farm planning and plot layout.
There are several types of remote sensing systems used in agriculture but the most common is a passive system that senses the electromagnetic energy reflected from plants. The sun is the most common source of energy for passive systems. Passive system sensors can be mounted on satellites, manned or unmanned aircraft, or directly on farm equipment.
There are several factors to consider when choosing a remote sensing system for a particular application, including spatial resolution, spectral resolution, radiometric resolution, and temporal resolution.
Spatial resolution refers to the size of the smallest object that can be detected in an image. The basic unit in an image is called a pixel. One-meter spatial resolution means each pixel image represents an area of one square meter. The smaller an area represented by one pixel, the higher the resolution of the image.
Spectral resolution refers to the number of bands and the wavelength width of each band. A band is a narrow portion of the electromagnetic spectrum. Shorter wavelength widths can be distinguished in higher spectral resolution images. Multi-spectral imagery can measure several wavelength bands such as visible green or NIR. Landsat, Quickbird and Spot satellites use multi-spectral sensors. Hyperspectral imagery measures energy in narrower and more numerous bands than multi-spectral imagery. The narrow bands of hyperspectral imagery are more sensitive to variations in energy wavelengths and therefore have a greater potential to detect crop stress than multi-spectral imagery. Multi-spectral and hyperspectral imagery are used together to provide a more complete picture of crop conditions.
Radiometric resolution refers to the sensitivity of a remote sensor to variations in the reflectance levels. The higher the radiometric resolution of a remote sensor, the more sensitive it is to detecting small differences in reflectance values. Higher radiometric resolution allows a remote sensor to provide a more precise picture of a specific portion of the electromagnetic spectrum.
Temporal resolution refers to how often a remote sensing platform can provide coverage of an area. Geo-stationary satellites can provide continuous sensing while normal orbiting satellites can only provide data each time they pass over an area. Remote sensing taken from cameras mounted on airplanes is often used to provide data for applications requiring more frequent sensing. Cloud cover can interfere with the data from a scheduled remotely sensed data system. Remote sensors located in fields or attached to agricultural equipment can provide the most frequent temporal resolution.
Auracle Geospatial Science Inc (AGS), is a geospatial company and offers a comprehensive range of geospatial information services that include Geographic Information Systems GIS, satellite image processing, geospatial analysis and geospatial modeling. Our global clients from mineral exploration, oil exploration, forestry management, and the agricultural industry have come to rely on our expertise to acquire, analyze, and visualize their geographic information.
We have years of experience in remote sensing technologies including image interpretation and analysis, data integration, data fusion and data visualization.
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Press Release Contact Information:
Julie McLelland
Auracle Geospatial Science, Inc.
Remote Sensing Consultant
325 Dorset Rd.
Qualicum Beach, British Columbia
Canada V9K 1H5
Voice: 250 738 0459
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