 This is the lesson three lecture with a focus on emergent earth observation sensors platforms and analytics The objectives for lesson three are an introduction to the Google earth engine platform Introduction to the following sensors Hyperspectral and thermal both of these are passive sensors They just receive the energy coming up to them Hyperspectral receives the reflected energy coming up to the sensor Whereas thermal sensors receive the emitted the thermal emissions come into the sensor and then Active remote remote sensing would be radar and we will take a look at radar and its related products Like the synthetic aperture radar also known as SAR We'll also look at some European space agency satellites Sentinel-1 and Sentinel-2 part of the Copernicus satellite program We'll look at some recent commercial small satellite startups in this lesson and also You need to start thinking about your project pre-proposal which will be due after lesson four What's the problem statement? What problem are you gonna work on and what type of data is needed? You need to start thinking about it once you get done with lesson three So you will also get an introduction to the Google earth engine cloud computing platform And this is a platform that has all the publicly available remote sensing data a Toolkit of image processing algorithms and scalable computing all available on the cloud so basically all you need is broadband to access this very powerful capability and this is a powerful capability for contemporary remote sensing and Please view the short introductory video on the Google earth engine website that is linked right over here and the coding environment in the Google earth engine is in JavaScript and it also has APIs API stand for application programming interfaces available for JavaScript, Python and Rest at this site. So so this site is hyperlinked to the developers website for developing custom Google earth engine applications and this is for all the programmers in the class who would have an interest in this We will also take a look at hyperspectral remote sensing which is a rapidly developing field with sensors deployed on satellites aircraft and unmanned aerial systems So hyperspectral bands are typically narrow Spectrally and to the order of about 10 nanometers or so. So the graphic on the right Kind of shows you what hyperspectral remote sensing is all about if you look at the diagram for Multispectral remote sensing you can see that the bandwidths of particular bands are pretty wide Whereas if you go to hyperspectral the bandwidth gets to be Substantially narrower and once again to the order of about 10 nanometers and Ultra spectral sensors in which the spectral resolution gets to be greater Which means the bandwidth gets to be even smaller are yet in a very experimental stage so the sensor captures a smooth and continuous reflective or emissive spectra as shown in the diagram to the right and this allows for the identification of vegetative species earth surface materials and environmental conditions like water quality and pixels need to image the same land cover class for a definitive Identification in other words you need to have a pure pixel of a particular type of a land cover class for their spectra to match exactly And data volumes are large and special image processing techniques are needed for image classification of hyperspectral imagery So we will also consider radar and its derivative the synthetic aperture radar in this lesson so radar is active remote sensing and So which means to say that the sensor needs to carry a power source with it So typically radar instruments are larger and heavier When they're deployed on a platform and the radar is increasingly being used for remote sensing applications and the synthetic aperture radar once again is a derivative derivative product of the radar technology and In the case of SAR Multiple looks at the same area are processed to develop a SAR raster image that highlights feature differences in the terrain and SAR is deployed on aerial platforms and on satellites and The server SAR handbook is an excellent resource for ecological mapping applications and I have listed the link over here and Please browse the five one-page reference guides for key SAR concepts that are available on this web page above so radar imaging operates on several different bands that are listed in this diagram below and They had these names like L band S band and C band X band and these names came about from the Second World War when these ideas and this technology was developed but what I want you to notice is that the wavelengths of Radar are much larger than that of visible light So typically as you can see these wavelengths are ranging from about three centimeters Up to oh up to 30 centimeters and greater to the order of a meter So this slide once again reiterates in words what was presented in the previous slide So the basic idea of radar is it sends out a pulse of electromagnetic radiation sent by the transmitter That bounces off the terrain and comes back and brings information about the terrain back to the sensor And the wavelengths are much longer than visible as mentioned and and are in centimeters as opposed to micrometers and have these Typically traditionally are represented with these letters each one of these letters represents a certain wavelength that that particular radar operates at So this is to get into the idea of a radar geometry and the fact that a radar is a side-looking Sensor such that if the platform let's say was flying into the screen Then it would be doing remote sensing with radar Looking off to the side at 90 degrees to the direction of motion You can see the green arrow that represents what is known as the slant range plane and then you can see the ground range plane and that is being imaged and Typically a slant range image is taken in the beginning as shown in this picture below The diagram and then that is processed to give you the actual ground range image And it turns out that radar has certain artifacts known as layover for shortening and shadows and all of this is discussed in greater detail in your readings So the following graphic gives you an idea of how radar Interacts with the surface that it is imaging and what type of an image you end up getting So if you just have a flat surface you end up getting a radar image That is this dark rectangle below if it's a forest then Depending on the radar wavelength the signal may bounce around before it goes back up You may get a speckled image Here we have an idea of what cropland might look like with rose and so forth as it is being cultivated and Then the next graphic shows you what a mountain might look like and have a shadow Behind it because the radar signal is occluded from the region behind the mountains You can see a rough surface once again will give you a speckled image and if you had urban structures With very definite geometry that will be reflected in the image as well So this set of diagrams shows you three distinct scattering mechanisms for radar imagery and One is just reflection off of a smooth surface or a rough surface The other type is a double bounce and that comes about due to a Edge being present like a corner reflector and you would get a double bounce Reflecting off of two smooth surfaces like a freshly cut tree stump for example And then you have the third general type of scattering that you have with radar is volumetric scattering where the light comes down or or or the radar wave comes down and bounces around let's say tree canopies or forest canopy and then Goes back up to the sensor Where then you can estimate densities of canopies and so on and so forth or another example might be the reflection off of dry snow where Some of the signal gets reflected directly from the top surface and some of the signal penetrates and then gets reflected back to the sensor Where once again you can do volumetric estimations with this type of scattering So radar waves that are typically to the order of a few to several centimeters Have another property This is a property that all electromagnetic waves have and this is known as polarization It defines the plane of oscillation of the incoming electromagnetic wave so You can have a vertical vertical polarization for example what that means is that the Radar antenna is Giving out a wave that is vertically polarized It's it's the wave is oscillating up and down in the vertical direction So it's a vertical sand and then the scattered wave is also coming back with a vertical polarization And that would be known as a VV or a vertical vertical polarization image and Then you can have a radar antenna that is transmitting in horizontally polarized waves that go and hit the target and then they bounce back and they are received by a Horizontal sensor and that would be a horizontal Horizontal polarization wave or signal or H H and you can have mixed Polarizations to that gives interesting information about the surface that is being examined that is you could send off a signal polarized in the vertical direction and Then the signal gets rotated upon reflection and then you capture a horizontal signal coming back and that would be a VH image similarly you can have a HV image that you are the sensor is the the antenna is putting out a horizontally polarized image and part of it gets the polarization vector gets Rotated after it interacts with the surface and then you are receiving a vertical image And that would be a H V image and we will see examples of this soon enough so here are Radar images taken off a portion of Brazil and you can see the X band radar is this is a vertical vertical image this is a C band image different wavelength and the Radar is transmitting with a horizontal polarization and then it is receiving a Vertical polarization and this is the information that we see on the image and This third example is a L band image. That's even a larger Radar wavelength and it's being transmitted with a horizontal polarization and then the vertical polarization is being received and Just by looking at these images you can see that each one of these different polarization combinations is is Highlighting different types of features on the ground. So the radar sensor has many advantages and Active microwave energy Penetrates clouds and can be an all-weather remote sensing system, which means radar can penetrate clouds It can readily do imaging if they're imaging if there is light precipitation taking place so it's an all-weather sensor and Synoptic views of large areas for mapping at scales of one is to 25,000 to one is to 400,000 Can be done and cloud shrouded countries may be imaged very effectively and coverage can be obtained at user-specified times even at night and Since radar is a side-looking sensor It permits imaging at shallow-look angles resulting in different perspectives that cannot be obtained using aerial Photography that means to say if you image the same terrain with shallow-look angles from many different directions It will highlight features that you once again you could not see with Aerial or satellite imaging. So once again wavelengths in a radar sense Outside the visible in the infrared regions of the electromagnetic spectrum once again these wavelengths are to the order of a few too many centimeters and they provide information on surface roughness the dielectric properties, which is a physical property of the surfaces and moisture content So there are many other advantages of the radar sensor as well that makes it such a important sensor and It may penetrate vegetation Sand and surface layers of snow if the conditions are right and if you're using the proper wavelengths for that study and Since it is an active remote sensor It has its own illumination and the angle of illumination can be controlled such that you can point your radar sensor once again To your study area and be able to discern features that would be very difficult to see otherwise It enables resolution to be Independent of the distance to the object with the size of the resolution cell being as small as one meter by one meter and As we discussed in the previous slide images can be produced from different types of polarized energy HH, HV, VV, VH and Radar sensor may Simultaneously operate in several wavelengths so that means it could be put in out several different bands at the same time and Thus has a multi frequency potential that at the same time you can discern different types of things on the ground Radar can measure ocean wave properties even from orbital Altitudes and therefore is very important for oceanography It can produce overlapping images suitable suitable for stereoscopic viewing and radar Grammetry and what that means is such that you can make very good measurements from this data and It supports Interferometric operation using two antennas for 3d mapping an analysis of incident angle signatures of objects and Interferometric SAR it turns out can make very accurate measurements of the topography and as we will come to see very useful for Where the land topography is changing like in the case of earthquake? Tsunami in the case of the ocean or a glacier So here is a graphic that gives you an idea of how synthetic aperture radar works So you have a sensor flying in a particular direction looking off to the side And it images the same portion of the ground with many different looks and then Mathematical processes are run on these different looks to create the SAR data image So here's an another example of a SAR image that is compared to a color infrared photograph taken by the space shuttle So you can see that we have at the bottom a Composite image that was acquired by radar and so you have the red gun is assigned to the C band Horizontal and then vertical polarization band the HV band the green gun is going to the L band and The HV band in particular and the blue gun is once again going to the L band With the horizontal horizontal the H H Polarization and then these three separate bands are being rendered as a False color image over here And if you look at it you can see the incredible detail that the radar is able to capture So for example for observations of forests The C band radar which has wavelengths of about three to eight centimeters Has low penetration depth of the canopy it comes in it bounces around the canopy and then goes back up to the sensor Whereas if you're imaging with larger wavelengths like L band radar or P band radar It can penetrate deeper to the canopy all the way to the ground and in fact it can penetrate the ground as well especially the drier the ground the deeper the penetration and And so therefore C band is very useful for looking at tops of canopies and volumetric estimations and L band and P band are very good for looking Underneath the pen canopy and imaging all the way to the ground so here's an example where we have a landslide image and then we have a strip of radar data from sir a That basically stands for space-borne imaging radar and you can see that it has a penetration depth of about one to four meters in the Sahara desert Because the soil is so dry you can get a penetration and Start seeing structures underneath the ground So here's another comparison between a Landsat optical image to the left of Oasis in Egypt and if you look at the same region with Cersei L band Radar image you can see a penetration up to two meters and can see features underneath the ground Another very important value added SAR product is the Interferometric SAR also known as if SAR or in SAR and Basically, you can use two SAR images with different view angles and then you can do some math in it and the basic upshot of it is that you can measure very small changes in the topography of the ground and this comes in very useful if I'm mapping earthquakes and Things like glacier movements or also looking at the surface of an ocean so here we have a Ifsar image of the of the 2004 tsunami that occurred in Asia and Now let's get into another very important area of remote sensing and that is the thermal remote sensing and All previous sensor systems discussed sensing or measuring reflected solar radiation in thermal infrared remote sensing we measure emitted terrestrial radiation so energy is first absorbed and surfaces heat up and the energy could be The Sun warming up the earth in the daytime and then it's emitting energy at night or it could be anthropogenic energy generation like a heated building and What a thermal sensor will measure is just the emitted and Thermal energy coming from the study area may to be in daytime or at night so here is an example of a Reflective multi-spectral image taken by Landsat 7 and then the Landsat 7 etm plus sensor has a thermal band as well and we can see the comparison between both of them The brighter the thermal band the warmer that surface is and Notice that in this case the spatial resolution of the thermal sensor is coarser than the optical sensors Here's another example of day and night thermal imagery taken from an airplane and you can see the regions that are warmer in the daytime and Then you can see the regions that are warmer and emitting heat at the nighttime Let's talk about a little bit about the underlying physics of thermal remote sensing So the level of thermal radiation emitted by objects is determined by their temperature So the temperature of the object that is being imaged Determines the amount of thermal emission coming from it Also, the amount of thermal emission is dependent upon the surrounding temperature of the heated object as well and The amount of energy being emitted or absorbed is also a function of the emissivity e where the emissivity of a perfect black body of a Perfectly emitting an absorbing surface Is one and the emissivity of a perfectly silvered surface is zero so a shiny surface is not gonna absorb thermal radiation or emit it efficiently at all Whereas if you had a surface that was closer to a perfect black body Would be very good for absorbing all the radiation fallen on it and emitting it very effectively as well so thermal power emission from a heated object or conversely of Thermal power absorption by a cooler object same idea is governed by the Stefan Boltzmann law and in this law the in this formula the temperatures are in degrees Kelvin Such that we can calculate the radiant power Emitted the thermal power emitted and power is energy divided by time The rate at which energy is being given off from a heated object is dependent on the emissivity of it Sigma is a constant known as Boltzmann's constant and has a constant value a is the surface area of the object that is emitting or absorbing the heat and then we have the difference between the fourth power of the temperature of the object minus the Surrounding or the ambient temperature So the basic point that I want to make over here is that the power the thermal power emitted or absorbed By a surface is going to be a function of the temperature difference that surface has with its Surroundings and if there is no temperature difference no power will be emitted And we will see that this leads to the phenomenon of thermal crossover in the next slide Also, want you to be aware that as thermal energy is moving through the atmosphere at Absorption and not scattering is the dominant atmospheric effect. That is the Atmosphere tends to absorb the thermal energy moving through it So here is a diagram that highlights the idea of a thermal crossover So remember that the thermal sensor will measure the thermal emissions most effectively When there is a large temperature difference between the surface and the surroundings and if that Temperature difference goes to zero then the thermal exchange basically stops at that time And so if you look at dawn or sunset is where you have the crossover periods So, you know at nighttime if you may have a heated building and the outside is very cool So you have a large temperature difference, but when the sun rises there comes to be a point where the surface temperature of the buildings Will be becomes the same as the temperature of the surroundings as the sun rises and heats up the surfaces And you are at a crossover period and that is not a good time to do thermal imaging So basically the best time for thermal imaging is where you have the largest temperature difference between the surface that is being imaged and its Surroundings that would happen somewhere around early afternoon to afternoon Where you have the largest temperature difference and hence you will have the largest Contrast in your thermal image So once again, this is to remind you of what temperature is Basically temperature is a measure of the internal thermal energy of an object and inside the object a Solid or a gas or a liquid You have the atoms and molecules are moving and zigging and zagging and If they have a larger kinetic energy if on the average they are moving faster Then the object is said to be warmer and if the object it gives off thermal emission and cools off Then the net random motion taking place in the molecules of the heated Object that is cooling down the net random motion will decrease as the temperature decreases as it emits thermal radiation There are two ways that you can measure the thermal energy of an object One is the kinetic temperature This is the one measured by a thermometer if you were to put a thermometer on the surface of the object It is also called the internal real Contact or thermodynamic temperature of the object So it's the actual temperature of the object you would measure if you had actual contact with the object on the other hand Via remote sensing you measure what is known as the radiant temperature So the radiant temperature is measured by a radiometer which is basically a sensor And the radiant temperature is also called external apparent or non-contact temperature And we will come to see that the radiant temperature can be converted to the actual or kinetic temperature If a property of the object surface known as emissivity is known So this leads to a point that is very important for remote sensing So and this is to get into the idea of the relation between the kinetic temperature and the radiant temperature so Let's say if you have a perfect black body the emissivity of an object is one Its kinetic temperature will be the same as its radiant temperature Now kinetic temperature is the temperature that you sense by putting a thermometer on the surface Or by touching the surface and feeling the warmth of it And you can assess the kinetic temperature in that manner Radiant temperature is measured by remote sensing if you have a thermal sensor sitting Somewhere and measuring the thermal emissions coming to it Then that is known as radiant temperature and the radiant temperature measured Will be the same as the kinetic or the actual contact Temperature if the emissivity of the object is one So what i'm trying to say is that it is very important to know what type of a surface You are imaging in thermal remote sensing You need to know the emissivities of these surfaces such that you can infer The temperature of the object from a distance And that is by measuring the radiant temperature So for natural or gray bodies the kinetic and the radiant temperatures differ according to the emissivity of that body So if you know the radiant temperature of an object Then as a consequence of the Stefan Boltzmann law You can calculate the kinetic temperature the actual surface temperature as well But you will need to know the emissivity of the surface that you are imaging So what that means is then is the emissivity therefore ends up controlling The radiant temperature the temperature that you measure By remote sensing of an object and therefore two objects with the same kinetic temperatures But different emissivities will have different radiant temperatures your remote sensing Instrument will measure different radiant temperatures for two objects That have the same temperature by contact but have different types of surfaces with different emissivities So here's a summary of these basic thermal properties that we have just learned And temperature of an object measured remotely is known as its radiant or apparent temperature Radiant temperature is the black body or kinetic temperature reduced by its emissivity Okay, so in other words, if you had a perfect black body then the radiant temperature is the same as kinetic temperature But the if the emissivity of that surface is lesser than the radiant temperature that is measured will be lesser And remotely sensed thermal infrared radiances the signal that the thermal sensor is receiving therefore are a combination of the emitted energy The emissivity of the surface and the atmospheric effects that happen as the infrared travels through the atmosphere and the sensor characteristics themselves So here's another example of of thermal remote sensing so in the Upper image you can see a 3d model that has been generated by using the reflective the optical bands And then you can see the thermal infrared bands Below where you can discern the differences in temperature on the terrain So here's another example of a thermal infrared image of Lake Tahoe That's draped over a landsat image of the same region and you can see that We can discern the different regions the different temperature distributions of the On the surface of Lake Tahoe Here's another example of a comparison between thermal and visible images of Glen Canyon and the surrounding sandstone And as you can see you can discern more detail from this thermal image Another important application of thermal imaging Is mapping urban heat island effects It turns out that cities have micro climate effects Due to the urban heat island that they form And this is a very good visual Rendition of a thermal imagery of the Minneapolis St. Paul area The european space agency or ESA Copernicus Sentinel program Is worth mentioning and is an important satellite program that has free access to its data So the ESA Copernicus Sentinel satellite program has six focus areas Atmosphere marine land climate change security and emergency And of this constellation of satellites, there are two satellites Sentinel one which has a SAR sensor and Sentinel two that has multispectral bands That are landsat like yet with a higher spatial resolution And Sentinel one and Sentinel two are dedicated to land remote sensing Please watch this brief video at this hyperlink To get acquainted with the ESA Copernicus Sentinel program And also look through this comparison of the Sentinel two bands and the landsat eight bands And you will see the similarity between the spectral wavelengths of these bands But Sentinel two has data that has higher spatial resolution than landsat eight In the past five years there has been a proliferation of commercial small satellite startups And this is still a very volatile area in the sense that there are Some new startups sustaining themselves and have grown and others have closed down Or have consolidated and have been brought over by other companies So for example Planet Labs was one of the initial small satellite startups that is now launching flocks of doves, which means constellations of dove small satellites small satellites the size of a shoebox But there are tens or hundreds of them such that you can have very rapid repeat Capabilities above the earth But typically these small satellites do not deliver Radiometrically and atmospherically and geometrically corrected data like government programs like landsat and sentinel do Landsat and sentinel are very exquisitely calibrated instruments And most commercial satellites at this point will give you a multispectral image But it will not have the atmospheric correction or the radiometric correction And you will be exploring some of these new remote sensing satellite companies in your readings And as remote sensing professionals you need to keep an eye on this rapidly developing area of commercial remote sensing satellites And that will continue to develop And the data deluge is just going to keep on getting to be bigger with time It is also getting to be time for you to start thinking about your project pre-proposal So by the end of lesson three you will have gained familiarity with several types of remotely sensed data and their sources And this is the time to begin to develop a vision for your course project And this involves posing a question commensurate with your professional or personal interests And then investigating the type of data available to answer A part of or the entire question that you are posing So that just depends on The type of data that is available on whether you can explore something in detail or if you can just make a first cut on it Some of you have more mature Interests than others And if you're not sure about a project theme Work on a land cover mapping project for the region where you live in Or a region that you have an interest in in the us And i'm saying the us because we have lots of data Remotely sensed data from many sensors Available publicly and free in the united states and see if you can find nape Foreband imagery and lidar For two separate time periods for a obi a project if you do if you're not sure about what you would like to work on And bear in mind that your project pre proposal is due at the end of lesson four So that you still have Oh 10 days or so to start crystallizing an idea So if you have any questions or comments, please post them in the lesson three General questions and comments forum