 Hello everyone, welcome to the next lecture of the course remote sensing principles and applications. In this lecture, we are going to discuss how an image is acquired, what will be the like the geometric properties of images and so on. That is, until last lecture, whatever we discussed effectively dealt with the contents of the image, what we call the radiometric content of the image, like what the image contained DN, what is the actual physical property recorded in the image, radiance, what do we really need for our applications, reflectance, what all the factors that may affect the radiance and so on. So, essentially we talked about the contents of the image DN, radiance, reflectance, some factors affecting them, everything. In this lecture and in the coming few lectures, we are going to see how actually the image is recorded, how sensors work in space and due to sensors property, how the geometric accuracy of the image as well as the radiometric accuracy of the image will be affected. So, geometric accuracy in a sense, say for any ground point x y, let us say the coordinate of the point is 100 comma 100. In the image, we will have a point of that particular ground point, we will be able to calculate what is the ground coordinates of each image point, that is possible. So, if we calculate that from the image also, we should retrieve back the same 100 comma 100 for the ground point. If we are able to do that, the image is geometrically accurate and whatever feature is there, it should exactly look the same, right, then only we see images geometrically accurate. Say when we take our normal photographs, let us say we are taking a photograph of a circle. If the circle appears as a circle in the photograph of similar size, it is fine. If the circle gets distorted, if it appears as an ellipse, then the image is not geometrically correct, right, there is some sort of geometric distortion. So, all these kind of properties about how image is being recorded, how sensors, the way the sensor performs, how it affects the geometric accuracy of the image, how it affects the radiometric accuracy of the image, all these things we will discuss. In addition to this, the most important concepts that we are going to discuss in this lecture and the coming few lectures are the different resolution concepts attached with a sensor and an image. Each remote sensing system has certain characteristics given by the terms spatial, spectral, temporal and radiometric resolutions. So, these are four important characteristics of any remote sensing system, spatial, spectral, temporal and radiometric resolutions. So, what are these, how these are related to image acquisition process, all these important concepts we will cover in next few lectures starting from this particular lecture. So, before we move on to actually looking at the procedure of image collection or image acquisition, we will first try to get a feel for what are the different class of remote sensing sensors are there, how remote sensing sensors can be classified. It is given in this particular slide. So, any remote sensing sensor can collect spatial information, spectral information and intensity information. Intensity information, we can also call it as radiometric information. Spatial information is data about any given ground point x, y. Say for example, if I collect the elevation of all ground point x1, y1, z1, x2, y2, z2. If I collect such data at a given ground point, ground coordinate x, y, what is the elevation of the point? If I collect this, I am actually collecting spatial information. On the other hand, at every ground point, if I collect how the incoming energy or how the reflected energy varies with respect to wavelength, say there may be like a vegetation standing there in a given ground point x, y, there may be like a tree standing. What I am interested in collecting is at the point x, y, what is the spectral reflectance curve? So, at a given point x, y for this tree, how the spectral reflectance curve looks? This will vary from 0 to 1. If I collect such information, I am collecting spectral information. On the other hand, rather than collecting this reflectance value that is between 0 to 1, if I collect the actual amount of radiance, let us say for this particular tree, the radiance recorded at green bandage, say some 10 units at NAR bandage, say some 50 units. So, if I collect the actual radiance recorded, actual energy that came in, actual energy that got reflected, if I measure it quantitatively, I call it radiometric information or intensity information. So, essentially remote sensing is a process in which we do all three to some extent. We should collect information across a space, across a x, y domain. We should collect information, spectral information at different bands, how much is the reflectance? Also for various applications, we should also measure the actual radiance itself. Like say for example, for some applications, it will be good for us to know only the reflectance values. Say for example, for this particular feature, 10% of incoming energy is in green, 20% of reflected energy is in NAR band. If I know this, that is sufficient. I may need not know what is the exact amount of energy came in, only the fraction or only the percentage composition, if I know that is good enough. For some applications, I should know the exact amount of radiation that came in different different bands. So, it depends on the various applications we use. So, based on all these things in remote sensing, we may have to collect spatial information across a spatial domain, spectral information across different wavelengths and radiometric information, measure the actual amount of energy that came in. So, based on these three properties, the sensors may be classified into different, different classes. First thing is any given remote sensing sensor can be imaging or non-imaging sensor. So, what is imaging or non-imaging sensor? As the name suggests, an imaging sensor produces a two-dimensional image of any given area. That is, whatever it records, it records in a two-dimensional space and gives an images output. Non-imaging sensors essentially do not create images, they just collect data at various discrete points. For our own understanding, later on we may create image out of it. What are such sensors? Let us take one class of sensor known as altimeters. Altimeters have the purpose of collecting the elevation information. Say, whenever it is flying, it will send some electromagnetic radiation either in micro wave or in light energy, LiDAR sensors. They will send in some pulses, they will collect the signals back. Using this, they will calculate the height of the ground feature. So, they will give us x, y, z points. It is a series of points x, y, z, x, y, z and so on. If you display it in like a image display system, you will get what is known as like a point cloud maybe, a different x, y, what is the z? That is the only thing that will come up. So, this sensor essentially do not provide us a two-dimensional image. It provides us a series of points with x, y, z coordinate. Such sensors are altimeters or like radar altimeters, LiDAR altimeters and so on. Similarly, atmospheric sounders. Atmospheric sounders are some instruments which will look down the atmosphere. It will try to estimate the temperature, humidity, pressure, etc., at different, different elevations of atmosphere. So, they will also essentially provide point information. At this x, y, at this height of atmosphere, the temperature pressure was this. At this x, y, at this height of atmosphere, the temperature and pressure and other variables are like this. They will provide such information. So, these kind of sensors, atmospheric sounders, altimeters, etc., they provide spatial information, non-imaging sensors. Some, let us take an example of a Landsat satellite. Landsat satellite is essentially like provides, is a imaging sensor. It provides a two-dimensional image. It collects data in multiple bands. So, it provides spatial information, spectral information and using Landsat data, we will also be able to calculate the quantity of the energy that came in. So, it collects all spatial, spectral and radiometric resolution. One more example sensor I will say is MODIS, a very widely used sensor, MODIS. MODIS full form is moderate resolution imaging spectroradiometer. Just look at the name, moderate resolution. It just deals with the resolution of the feature, we will learn about it later. Imaging, the sensor will provide a two-dimensional image that is known. Spectroradiometer, the sensor collects data in different spectral bands. Also, it collects the exact amount of energy that is coming out of a sensor. So, it is both a spectrometer as well as a radiometer. So, it is an imaging spectroradiometer. It does all the jobs, spatial information, spectral information, radiometric information. Like some instruments, like spectrometers, some instruments which we will use in our hand for collecting ground data, they may not collect the exact amount of energy that came in. They may collect only the relative variation of spectral reflectance. In this band, this is 10 percent, in this band, this is 20 percent. Only the relative variation, it will measure. Such instruments are called spectrometers. Some instruments, like say for example, during time of covid and all, people used to point, handle thermometer remotely, they will keep it towards our eyes. What the thermometer will do? It will collect the radiation from us, using that it will calculate the temperature of our body. That is essentially a pure radiometer. It is not doing any sort of spatial data collection or any sort of spectral data collection. Purely it is measuring the incoming energy. What is the quantity of incoming energy? Using the quantity of energy, it is calculating temperature of our body. That is a pure radiometer. From radiometric information, it is doing something. So, the sensors can be collecting spectral, spatial and radiometric information. Most of the remote sensing sensors, especially what we deal in our class, like Landsat, Modus, Indian remote sensing satellites. Some of the examples, what and all we will see. Essentially, they collect all the information. They collect spatial, spectral, radiometric information. They all fall in the category of imaging spectroradiometers. They collect image. They collect spectral information. They collect radiometric information. Next, we are going to start with remote sensing data acquisition. Like now, we learned to a good amount of good extent that once the image is collected, how are different, different processing we can do. Especially in the visible NIR and SWR wavelengths, it is lambda less than 3 micrometers. We have a good knowledge at this point. How that image is collected? How it is being carried out? That is what we are going to see in the coming slides. First, we will take an example of like earlier days. There is not much of like sophisticated sensors available, but a normal photographic camera was there like I am talking about like 18th century and all. So, a photographic camera was there. So, essentially people, they put a photographic camera in balloon or they tied it under like huge kites under PGNs and all. They flew it in sky, took photographs of the ground surface. So, essentially the first modes of image collection that happened is like pure analog photography that is given in this particular slide. So, in olden days that will look something like this as given in the slide. Say it will be like a photographic camera put in space, it will have like a lens. So, this is like earth surface. It will take multiple different photographs. So, as the balloon or something moves, it will take multiple photographs. So, this was like the earlier most ways in which earth observation was carried out. Similarly, later people started putting such cameras in aircraft in order to collect aerial photography, what we call photograph aerial photography and using this people did remote sensing based observations like they did what is known as interpretation. Like by just by looking at the photograph, they will tell us, okay, here there is like a small urban settlement, here there is like a water body and so on. So, this is known as photo interpretation. This was very widely developed and used in days of world war. Like the people will fly aircraft fitted with photographs or photo cameras, they will collect photographs and start interpreting it for collecting strategic defense information. And also it give us a field, what is known as photogrammetry. Photogrammetry essentially means making measurements from this photographs and mapping the features on earth surface. So, based on certain principles, if we take photographs, we will be in a position to calculate x, y, z at all points that has imaged in that particular photograph. So, mapping the terrain, what is the x, y, z coordinates, what is that particular feature there. So, mapping everything, measuring distances, all these things developed, the technology developed and that particular subject is known as photogrammetry, it is a different subject altogether. Related field, but they are the much of the interest is in making physical measurements in photographs and mapping the terrain. So, olden days that is how aerial photographs were collected and measurements were made and also photo interpretation was done. Later came the age of space based satellite remote sensing. So, when something has to be sent to space, essentially that particular sensor once sent, it cannot come back right. People were still doing it, they will send something to space, it will fly in between like aircraft and spacecraft distances, it will come back. People will retrieve the tapes from it, develop it, it was possible. But still when pure satellites was to be developed and sent to space, essentially whatever data was is being collected by the satellite, should be transmitted through some non-contact form, that is you cannot bring the satellite down, retrieve this film photography back and develop it as we do like a normal photograph. Everything has to occur digitally and also the data has to be collected in a two dimensional space. We cannot send our normal photographic camera there. Then came the development of different different sensors or different ways in which image was being collected. So, when the satellites was sent to space, there can be like two different orbits or maybe like the first till the example of like a normal still photography. Let us assume we need to take a photograph of a small surface or something that is happening in front of us. What we will do? That particular object of phenomenon will be there in front of us. We will take our camera, take a picture. So, our camera is in motion, sorry our camera is actually stationary. We are standing still. Whomever or whatever object is there in front of us, most likely will be standing still. We will take a photograph. We will get a two dimensional image. If we think about like a satellite, satellite will be in continuous motion. It is imaging earth. Earth is also rotating continuously in some axis. So, these are some of the things which are in motion. This complicates things to some extent. So, in such circumstances how the image was collected? First thing we should know is based on the orbit of the sensor, the way in which the image will be collected will differ. Orbit of the sensor means or like orbit in which the satellite is put. Two common orbits in which satellite is put is geostationary orbit and near polar orbit. Let us say this is earth, satellite is revolving around it. So, if this is the earth, it will revolve in like from west to east, it will rotate like this. So, if the satellite moves around the earth in this direction like from north to south, we call it as a near polar orbit. There is another orbit called geostationary orbit in which earth is here. Satellite will be placed along the equator at a further distance. As the earth rotates, satellite also will rotate with earth. That is known as geostationary orbit. So, when satellite is put up in two different orbits, the image collection principle may vary little bit slightly. So, under these two circumstances, we will see how the image is collected. We will see all these things from next class. So, in this class as a summary what we have seen is we have seen the broad classification of remote sensing sensors which collects spectral information, spatial information and radiometric information. Then we just got introduced to the concept of how old-in-day photography was collected, how it was used for concepts of photo interpretation and also for photo measurements, photogrammetry and so on. Next, we saw two different, we just got introduced to two different orbits, geostationary orbit and near polar orbit. And from next class, we will see how images are actually collected from these two orbits. Thank you very much.