- [Amanda] Hi, everyone.
My name is Amanda Armstrong,
and I will be your instructor for this course,
remote sensing foundations.
In this first lecture, we will be moving pretty quickly
from particle physics to Google Earth Engine,
as we dive into the exciting world of remote sensing.
Upon completion of this module,
my hope is that you will be able to define remote sensing,
define how and where remote sensing is used in industry,
science and commercial applications,
name and define the components
of the electromagnetic spectrum,
understand how energy and matter interact
with surface terrain,
understand and distinguish
between active and passive sensors
and what they are used to measure.
And finally, let's get your Google Earth Engine
account set up.
Let's get started.
So what is remote sensing?
Perhaps the most simplified definition
would be the collection of information
about an object without making physical contact with it.
However, for the purposes of this course
I'd like to add some words
onto the front end of that definition.
So I think of it more as the science of identifying,
observing, collecting, and measuring objects
without coming into direct contact with them.
Did you know that a remote sensing is accomplished
by humans and animals with the aid of our eyes
and other senses, like smell and hearing, every day.
And another important point that I wanna make,
is that satellites don't actually take pictures
of our planet, but what they do is they record
the electromagnetic energy that's reflected
or admitted from objects on earth.
So which industries and careers utilize remote sensing?
I won't read this slide to you, but as you can see,
remote sensing analysis is used in many sectors,
and where it is used is growing every year.
From commercial to nonprofit, to science,
to engineering and medicine.
There are a whole host of different career options
for those that have a background in remote sensing analysis.
Okay, so let's delve a little bit deeper
into some of the science
behind what we are measuring in remote sensing.
I remember when I took my first remote sensing course
in graduate school,
we spent the first month or so of class
brushing up on physics,
which might not sound
related to the study of measuring objects
without coming into direct contact with them.
But in order to understand what we are measuring
when a satellite measures the surface of the earth,
we need to go back to some of the basics
of particle physics and our understanding of energy.
A quark is one of the fundamental particles in physics.
Fundamental means that the particle
does not have a substructure.
So it cannot be split.
Quarks are the fundamental building blocks
of all particles that we know of.
They join to form subatomic structures
such as protons and neutrons
which are components of the nuclei of atoms.
Quarks are known to be one of the fundamental particles
that interact
through all four fundamental forces of physics.
Gravitation, electromagnetism,
and the strong and weak interactions.
Though the measurement of their properties
of mass spin and parity is mostly theoretical,
interactions of quarks is believed to be the foundation
of our knowledge of energy.
Which as I will show you is essential
to understanding the interpreting of satellite imagery.
Okay, so energy is the basis for remote sensing, but how?
Well we know that we can measure the movement
of particles in space, which have a sinusoidal shape.
We can measure their wavelength
which is the distance from one wave crust to another,
and is usually measured in units, like meters or nanometers.
We can also measure their frequency
or the number of crusts
passing a fixed point in a given period of time,
which often measured in hertz units.
And finally, we can also measure their amplitude,
which is the height of each peak
and measured in energy levels.
The greater the amplitude of a wave,
the more energy it is carrying.
When we look at all three together,
we can see how wavelength and frequency range
from low to high energy states.
This is called the electromagnetic spectrum.
The entire distribution of electromagnetic radiation,
according to frequency or wavelength,
although all electromagnetic waves
travel at the speed of light in a vacuum,
they do so at a wide range of frequencies,
wavelengths and photon energies.
This figure shows some of the most common sources
of electromagnetic energy.
As you can see, we come into contact with a whole suite
of electromagnetic energy emitters,
that emit at varying frequencies and wavelengths every day,
from x-rays to cell phones.
But the most important by far is the sun.
All of the energy from the sun
that reaches the earth arrives as solar radiation,
part of a large collection of energy
called the electromagnetic radiation spectrum.
Solar radiation includes visible light, ultraviolet light,
infrared, radio waves, x-rays and gamma rays.
Radiation is one way to transfer heat and light.
A very simplified view of remote sensing
would be to say that remote sensing
is measuring the reflection of the sun's radiation
as it comes into contact with different surfaces on earth.
However, it is not quite that simple,
because some of the energy that reaches earth
is absorbed and some is reflected back.
The reflected radiation is also absorbed
or scattered on its way back to the sensor.
Spend a minute studying this graphic,
which shows the percentages
of incident and reflected energy,
and you'll begin to understand
why it is necessary to have a grasp of physics
in order to interpret satellite imagery.
It is also important to note that not all of the radiation
reaches the earth surface directly.
In addition, energy from the sun is composed
of many kinds of radiation.
Both in the visible range
and also outside the range of human vision.
This energy is absorbed or scattered
through the atmosphere before it reaches earth.
The sun's energy can therefore be transmitted
which is to pass through the material
or the atmosphere, absorbed,
which is absorbed and converted into other forms of energy,
scattered or deflected in many directions,
reflected which is returned at a given angle or emitted,
which usually is what occurs over longer wavelengths.
By understanding how radiation from the sun
interacts with the atmosphere, then with the earth surfaces,
as well as how it is reflected from the surfaces
back to space.
We can begin to understand the nature of the energy
that is measured by satellite.
Each surface because of its makeup
and texture has what is called a spectral signature.
A spectral signature is a unique distribution
of reflected emitted and absorbed radiation of an object.
Here is a graph that shows the percent reflectance
of some common features on the earth surface.
As you can see, snow and ice are highly reflective
as well as clouds,
whereas clear water and turbid water
have a very low percent reflectance.
You can also imagine that different satellites
are constructed to measure differing ranges
of spectral reflectance,
with high accuracy and precision,
depending on what the satellite is designed to measure.
Here are two quick examples of how scientists
use spectral signatures to understand the earth surfaces.
On the left is a graph showing percent reflectance
of surface features by a Landsat satellite.
The ranges of wavelength are grouped into bands or channels,
with one being visible blue light,
two being green, three red and four near-infrared.
As you can see, vegetation has a high reflection
in the near-infrared channel, band four,
and a low reflection
in the visible red channel, band three.
Water mostly reflects in the visible light range.
So it will look dark in the near-infrared,
vegetation reflects more than soil in the near-infrared
and less than soil in red.
On the right, a study by As-syakur in 2012,
compared spectral signatures
converted to digital number across different bands
or channels using one satellite.
They compared signatures and used them to map,
built up and bear land in an urban area in Bali.
So now that we are gaining a better understanding
of what satellites are actually measuring,
let's talk about how they do it.
There are two main mechanisms for measuring,
active and passive.
Passive sensors rely on natural energy.
So they record energy that is naturally reflected
or admitted from the Earth's surface.
The most common source of radiation is reflected sunlight,
but the downside is that they can only detect energy
when the naturally occurring energy is available.
Or in other words, during the day.
The most popular passive remote sensing
examples of devices are various types
of radiometers and spectrometers.
Some of the instrument names
clearly identify what they measure.
So a spectrometer distinguishes and analyzes spectral bands,
a radiometer on the other hand determines
the power of radiation emitted by the object,
in particular band ranges.
A spectro radiometer finds out the power of radiation
in several band ranges.
Hyperspectral radiometers operate
with the most accurate type of passive sensor
that is used in remote sensing.
Due to extremely high resolution,
it differentiates hundreds
of ultimately narrow spectral bands
within the visible near-infrared and microwave regions.
There is also the imaging radiator,
which scans the object or surface to reproduce the image.
And a sounder which senses
the atmosphere conditions vertically.
Finally, there is also an accelerometer
which detects changes in speed per unit time.
These are all examples of passive remote sensing devices.
However, for the purposes of this course,
and probably one of the most popular ones,
an example of a passive sensor is Landsat.
Landsat definitely stands out as the most
long lasting earth absorbing mission.
It's monitored our planet and recorded the obtained data,
which has enabled us to analyze
the way the planet has changed within a 40 year time span.
One of the mission's great pluses
is that the information is accessible to the public
and with interpretations that are applied regularly
in geology mapping, ecology, forestry, and agriculture,
also in Marine sciences, meteorology,
and other applications as well.
You will most likely be using a lot of Landsat imagery
at times during this course.
Active sensors are the other main category of sensor type.
Each active sensor in remote sensing
directs its signal to the object
and then checks the response or the received quantity.
Active sensors are known
for using artificial forms of energy.
Active remote sensing techniques
differ by what they transmit.
They either transmit lighter waves
and by what they determine,
which can be distance, height or atmospheric conditions.
A few examples include radar.
Radar is a sensor assisting with radio signals.
Its specific feature is the antenna emitting impulses.
When the energy flow and radar active remote sensing
meets an obstacle,
it scatters back to the sensor to some degree.
Based on its amount and traveling time,
it is possible to estimate how far away the target is.
Lidar is another example of an active remote sensor.
Lidar stands for light detection and ranging.
Lidar determines distance with light.
Lidar active remote sensing
implies transmitting light impulses
and checking the quantity retrieved.
The target location and distance
are understood by multiplying the time
by the speed of light.
There is also the laser altimeters, which measure elevation
with lidar and ranging instruments,
which estimate the range
either with one or two identical devices
on different platforms, sending signals to each other.
Apart from a wide variety of implementation,
active remote sensors
basically have no restrictions as to research conditions.
Active types of remote sensing systems,
fully function at any time of day
as they don't require sunlight,
and they're relatively independent
of atmospheric conditions.
Various types of remote sensing technology
find implementations both in scientific branches
and far more practical industries as well.
Some other examples
include the Shuttle Radar Topography Mission,
which is also known as SRTM,
which collected all the Earth's elevation data.
Also lidar active remote sensing in the sky
assisted in the elaboration
of digital models of our planet surfaces.
Data acquired with remote sensing instruments
serve agriculturists and foresters alike as well.
They are critical and hard to reach places,
and in Marine sciences and rescue missions.
Finally sounders,
which is another type of active sensor,
assist in developing weather forecasts
with vertical profiles of humidity,
precipitation temperature and the absence
or presence of clouds.
Okay, now we have defined remote sensing
and talked about what it measures and how.
The last thing we're going to do in this first week
is talk a little bit about how we will be working
with satellite imagery this semester.
In this course we will use Google Earth Engine platform.
Google Earth Engine is an online environment platform
updated with data daily.
It's towards petabytes of satellite imagery.
It's a great platform for image analysis,
because it puts many millions of gigabytes of information
right at your fingertips.
It's used as an environment
to collaboratively share data and algorithms
and visualizations and you can share them using simple URLs.
Google Earth Engine also offers the ability
to perform analysis on large scale data sets,
including to detect measure, identify, characterize,
and interpret geospatial data sets.
The majority of the dataset analysis
is roster format oriented,
which we'll go over more next week.
And finally, one thing to note is that Google Earth Engine
has a very vast data catalog.
We'll learn how to work
and search within this data catalog
and how to utilize the different data sets
that are found within it.
The data catalog includes the complete archive
of pre-processed georeferenced scenes,
which include all of the Landsat missions, MODIS,
terrain, land cover, atmospheric, climate and weather data,
as well as demographic and epidemiological data as well.
Lastly, here are the instructions
to activate your Google Earth Engine account.
Please follow them carefully to join
our University of Vermont
Geospatial Technologies and Spatial Analysis Group.
And also please reach out if you have any questions.
Take care until next week.