Agriculture Reference
In-Depth Information
replaced by special sensors that allow us to investigate phenomena, even using
infrared and microwave bands (note that photography only uses the visible part of
the electromagnetic spectrum).
Multispectral detection may provide new information that is not obtainable with
visible spectrum methods. For example, infrared sensors measure the thermal
emission of an object, and these temperatures can represent important parameters.
From a statistical point of view, this information represents a typical example of a
multivariate data set.
Reflectance measured by a sensor can be considered as a proxy variable of some
biophysical phenomena such as the geographical coordinates ( x , y ) of an object, the
temperature, the color, or the moisture content of the soil and vegetation. These
covariates are often called direct variables (Jensen 2004 ). However, we can derive
some hybrid variables by simultaneously analyzing several biophysical variables.
For instance, it is possible to determine the stress of a plant by considering its
absorption characteristics, temperature, and moisture content. This represents a
hybrid variable.
An RS system usually consists of a platform, a navigation device, one or more
sensors, and a module for data processing and interpretation. The platform is
typically a satellite or aircraft. The navigation device establishes the location of
the platform and the land area under investigation. The interpreter can be a human
or an automated system that supervises the whole operation and platform.
RS systems can be active or passive. Active systems such as radar and laser emit
their own electromagnetic radiation. They later analyze the characteristics of
signals reflected from illuminated objects. Therefore, images can be acquired day
and night, completely independent of solar illumination, which is particularly
important at high latitudes (polar night). The emitted and received microwaves
are at a much longer wavelength than optical or infrared waves. Microwaves can
therefore easily penetrate clouds, and surface images can be acquired irrespective
of the local weather conditions.
Conversely, passive systems are based on electromagnetic waves that come from
external sources of energy like the sun. Note that the joint analysis of radar and
optical data can provide unique information that is not visible in separate images.
When plants receive electromagnetic energy from the sun, there are three
different possibilities. Depending on the wavelength of the energy and the plant
s
features, the energy will be reflected, absorbed, or transmitted. Reflected energy
bounces off leaves, and is recognized by human eyes as the green color of plants.
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, and shapes
determine how much energy will be reflected, absorbed, or transmitted. The
relationship between these different types of energy is used to determine the
spectral signatures of individual plants. Spectral signatures are unique to plant
species.
However, as stated by Carfagna and Gallego ( 2005 ), spectral response and crop
type do not have a one-to-one correspondence. In fact, the radiometric response of
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