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- [Amanda] Hi, everyone.

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My name is Amanda Armstrong,

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and I will be your
instructor for this course,

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remote sensing foundations.

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In this first lecture, we
will be moving pretty quickly

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from particle physics
to Google Earth Engine,

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as we dive into the exciting
world of remote sensing.

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Upon completion of this module,

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my hope is that you will be
able to define remote sensing,

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define how and where remote
sensing is used in industry,

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science and commercial applications,

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name and define the components

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of the electromagnetic spectrum,

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understand how energy and matter interact

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with surface terrain,

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understand and distinguish

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between active and passive sensors

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and what they are used to measure.

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And finally, let's get
your Google Earth Engine

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account set up.

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Let's get started.

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So what is remote sensing?

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Perhaps the most simplified definition

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would be the collection of information

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about an object without making
physical contact with it.

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However, for the purposes of this course

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I'd like to add some words

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onto the front end of that definition.

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So I think of it more as
the science of identifying,

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observing, collecting,
and measuring objects

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without coming into
direct contact with them.

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Did you know that a remote
sensing is accomplished

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by humans and animals
with the aid of our eyes

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and other senses, like smell
and hearing, every day.

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And another important
point that I wanna make,

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is that satellites don't
actually take pictures

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of our planet, but what
they do is they record

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the electromagnetic
energy that's reflected

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or admitted from objects on earth.

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So which industries and
careers utilize remote sensing?

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I won't read this slide to
you, but as you can see,

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remote sensing analysis
is used in many sectors,

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and where it is used
is growing every year.

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From commercial to nonprofit, to science,

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to engineering and medicine.

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There are a whole host of
different career options

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for those that have a background
in remote sensing analysis.

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Okay, so let's delve a little bit deeper

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into some of the science

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behind what we are
measuring in remote sensing.

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I remember when I took my
first remote sensing course

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in graduate school,

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we spent the first month or so of class

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brushing up on physics,

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which might not sound

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related to the study of measuring objects

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without coming into
direct contact with them.

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But in order to understand
what we are measuring

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when a satellite measures
the surface of the earth,

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we need to go back to some of the basics

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of particle physics and our
understanding of energy.

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A quark is one of the
fundamental particles in physics.

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Fundamental means that the particle

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does not have a substructure.

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So it cannot be split.

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Quarks are the fundamental building blocks

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of all particles that we know of.

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They join to form subatomic structures

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such as protons and neutrons

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which are components
of the nuclei of atoms.

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Quarks are known to be one
of the fundamental particles

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that interact

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through all four fundamental
forces of physics.

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Gravitation, electromagnetism,

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and the strong and weak interactions.

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Though the measurement of their properties

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of mass spin and parity
is mostly theoretical,

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interactions of quarks is
believed to be the foundation

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of our knowledge of energy.

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Which as I will show you is essential

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to understanding the interpreting
of satellite imagery.

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Okay, so energy is the basis
for remote sensing, but how?

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Well we know that we
can measure the movement

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of particles in space, which
have a sinusoidal shape.

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We can measure their wavelength

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which is the distance from
one wave crust to another,

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and is usually measured in
units, like meters or nanometers.

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We can also measure their frequency

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or the number of crusts

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passing a fixed point in
a given period of time,

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which often measured in hertz units.

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And finally, we can also
measure their amplitude,

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which is the height of each peak

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and measured in energy levels.

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The greater the amplitude of a wave,

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the more energy it is carrying.

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When we look at all three together,

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we can see how wavelength
and frequency range

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from low to high energy states.

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This is called the
electromagnetic spectrum.

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The entire distribution of
electromagnetic radiation,

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according to frequency or wavelength,

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although all electromagnetic waves

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travel at the speed of light in a vacuum,

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they do so at a wide range of frequencies,

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wavelengths and photon energies.

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This figure shows some of
the most common sources

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of electromagnetic energy.

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As you can see, we come into
contact with a whole suite

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of electromagnetic energy emitters,

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that emit at varying frequencies
and wavelengths every day,

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from x-rays to cell phones.

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But the most important by far is the sun.

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All of the energy from the sun

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that reaches the earth
arrives as solar radiation,

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part of a large collection of energy

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called the electromagnetic
radiation spectrum.

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Solar radiation includes visible
light, ultraviolet light,

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infrared, radio waves,
x-rays and gamma rays.

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Radiation is one way to
transfer heat and light.

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A very simplified view of remote sensing

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would be to say that remote sensing

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is measuring the reflection
of the sun's radiation

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as it comes into contact with
different surfaces on earth.

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However, it is not quite that simple,

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because some of the
energy that reaches earth

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is absorbed and some is reflected back.

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The reflected radiation is also absorbed

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or scattered on its
way back to the sensor.

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Spend a minute studying this graphic,

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which shows the percentages

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of incident and reflected energy,

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and you'll begin to understand

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why it is necessary to
have a grasp of physics

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in order to interpret satellite imagery.

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It is also important to note
that not all of the radiation

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reaches the earth surface directly.

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In addition, energy
from the sun is composed

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of many kinds of radiation.

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Both in the visible range

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and also outside the
range of human vision.

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This energy is absorbed or scattered

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through the atmosphere
before it reaches earth.

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The sun's energy can
therefore be transmitted

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which is to pass through the material

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or the atmosphere, absorbed,

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which is absorbed and converted
into other forms of energy,

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scattered or deflected in many directions,

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reflected which is returned
at a given angle or emitted,

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which usually is what occurs
over longer wavelengths.

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By understanding how
radiation from the sun

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interacts with the atmosphere,
then with the earth surfaces,

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as well as how it is
reflected from the surfaces

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back to space.

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We can begin to understand
the nature of the energy

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that is measured by satellite.

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Each surface because of its makeup

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and texture has what is
called a spectral signature.

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A spectral signature is
a unique distribution

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of reflected emitted and
absorbed radiation of an object.

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Here is a graph that shows
the percent reflectance

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of some common features
on the earth surface.

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As you can see, snow and
ice are highly reflective

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as well as clouds,

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whereas clear water and turbid water

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have a very low percent reflectance.

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You can also imagine
that different satellites

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are constructed to
measure differing ranges

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of spectral reflectance,

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with high accuracy and precision,

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depending on what the satellite
is designed to measure.

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Here are two quick
examples of how scientists

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use spectral signatures to
understand the earth surfaces.

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On the left is a graph
showing percent reflectance

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of surface features by
a Landsat satellite.

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The ranges of wavelength are
grouped into bands or channels,

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with one being visible blue light,

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two being green, three red
and four near-infrared.

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As you can see, vegetation
has a high reflection

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in the near-infrared channel, band four,

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and a low reflection

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in the visible red channel, band three.

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Water mostly reflects in
the visible light range.

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So it will look dark in the near-infrared,

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vegetation reflects more than
soil in the near-infrared

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and less than soil in red.

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On the right, a study
by As-syakur in 2012,

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compared spectral signatures

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converted to digital number
across different bands

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or channels using one satellite.

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They compared signatures
and used them to map,

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built up and bear land
in an urban area in Bali.

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So now that we are gaining
a better understanding

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of what satellites are actually measuring,

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let's talk about how they do it.

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There are two main
mechanisms for measuring,

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active and passive.

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Passive sensors rely on natural energy.

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So they record energy that
is naturally reflected

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or admitted from the Earth's surface.

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The most common source of
radiation is reflected sunlight,

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but the downside is that
they can only detect energy

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when the naturally occurring
energy is available.

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Or in other words, during the day.

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The most popular passive remote sensing

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examples of devices are various types

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of radiometers and spectrometers.

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Some of the instrument names

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clearly identify what they measure.

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So a spectrometer distinguishes
and analyzes spectral bands,

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a radiometer on the other hand determines

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the power of radiation
emitted by the object,

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in particular band ranges.

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A spectro radiometer finds
out the power of radiation

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in several band ranges.

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Hyperspectral radiometers operate

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with the most accurate
type of passive sensor

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that is used in remote sensing.

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Due to extremely high resolution,

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it differentiates hundreds

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of ultimately narrow spectral bands

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within the visible near-infrared
and microwave regions.

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There is also the imaging radiator,

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which scans the object or
surface to reproduce the image.

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And a sounder which senses

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the atmosphere conditions vertically.

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Finally, there is also an accelerometer

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which detects changes
in speed per unit time.

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These are all examples of
passive remote sensing devices.

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However, for the purposes of this course,

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and probably one of the most popular ones,

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an example of a passive sensor is Landsat.

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Landsat definitely stands out as the most

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long lasting earth absorbing mission.

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It's monitored our planet and
recorded the obtained data,

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which has enabled us to analyze

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the way the planet has changed
within a 40 year time span.

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One of the mission's great pluses

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is that the information is
accessible to the public

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and with interpretations
that are applied regularly

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in geology mapping, ecology,
forestry, and agriculture,

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also in Marine sciences, meteorology,

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and other applications as well.

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You will most likely be using
a lot of Landsat imagery

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at times during this course.

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Active sensors are the other
main category of sensor type.

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Each active sensor in remote sensing

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directs its signal to the object

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and then checks the response
or the received quantity.

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Active sensors are known

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for using artificial forms of energy.

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Active remote sensing techniques

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differ by what they transmit.

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They either transmit lighter waves

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and by what they determine,

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which can be distance, height
or atmospheric conditions.

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A few examples include radar.

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Radar is a sensor assisting
with radio signals.

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Its specific feature is the
antenna emitting impulses.

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When the energy flow and
radar active remote sensing

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meets an obstacle,

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it scatters back to the
sensor to some degree.

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Based on its amount and traveling time,

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it is possible to estimate
how far away the target is.

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Lidar is another example
of an active remote sensor.

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Lidar stands for light
detection and ranging.

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Lidar determines distance with light.

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Lidar active remote sensing

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implies transmitting light impulses

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and checking the quantity retrieved.

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The target location and distance

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are understood by multiplying the time

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by the speed of light.

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There is also the laser
altimeters, which measure elevation

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with lidar and ranging instruments,

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which estimate the range

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either with one or two identical devices

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on different platforms,
sending signals to each other.

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Apart from a wide variety
of implementation,

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active remote sensors

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basically have no restrictions
as to research conditions.

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Active types of remote sensing systems,

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fully function at any time of day

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as they don't require sunlight,

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and they're relatively independent

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of atmospheric conditions.

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Various types of remote sensing technology

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find implementations both
in scientific branches

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and far more practical industries as well.

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Some other examples

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include the Shuttle
Radar Topography Mission,

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which is also known as SRTM,

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which collected all the
Earth's elevation data.

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Also lidar active remote
sensing in the sky

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assisted in the elaboration

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of digital models of our planet surfaces.

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Data acquired with remote
sensing instruments

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serve agriculturists and
foresters alike as well.

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They are critical and
hard to reach places,

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and in Marine sciences
and rescue missions.

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Finally sounders,

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which is another type of active sensor,

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assist in developing weather forecasts

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with vertical profiles of humidity,

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precipitation temperature and the absence

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or presence of clouds.

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Okay, now we have defined remote sensing

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and talked about what it measures and how.

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The last thing we're going
to do in this first week

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is talk a little bit about
how we will be working

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with satellite imagery this semester.

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In this course we will use
Google Earth Engine platform.

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Google Earth Engine is an
online environment platform

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updated with data daily.

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It's towards petabytes
of satellite imagery.

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It's a great platform for image analysis,

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because it puts many millions
of gigabytes of information

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right at your fingertips.

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It's used as an environment

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to collaboratively share
data and algorithms

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and visualizations and you can
share them using simple URLs.

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Google Earth Engine
also offers the ability

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to perform analysis on
large scale data sets,

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including to detect measure,
identify, characterize,

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and interpret geospatial data sets.

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The majority of the dataset analysis

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is roster format oriented,

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which we'll go over more next week.

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And finally, one thing to note
is that Google Earth Engine

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has a very vast data catalog.

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We'll learn how to work

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and search within this data catalog

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and how to utilize the different data sets

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that are found within it.

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The data catalog includes
the complete archive

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of pre-processed georeferenced scenes,

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which include all of the
Landsat missions, MODIS,

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terrain, land cover, atmospheric,
climate and weather data,

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as well as demographic and
epidemiological data as well.

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Lastly, here are the instructions

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to activate your Google
Earth Engine account.

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Please follow them carefully to join

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our University of Vermont

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Geospatial Technologies
and Spatial Analysis Group.

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And also please reach out
if you have any questions.

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Take care until next week.