[Music] hello namaste welcome back to the course on geographic information system in in the last week we were looking at how do we look at the spatial analysis part of GS so now when we are looking GS as a tool or software the first thing that comes into mind is how do we do the analysis okay having said and done with the theory we the next step is to how do you do analysis so in this aspect this particular week is basically trying to give you an flavor of what are the different types of analysis is done whether it has spatial analysis whether it is advanced and special analysis or whether it is what are the limitations of jsj at the end so this week has been broken down into three parts first part I would give you an introduction to what do you mean by remote sensing okay having said this is Justin one short introduction to do more remote sensing but it is not limited to what I speak so you you would have if you have to understand remote sensing you have to go beyond at least my very beyond what I've already taught in this particular set of sights in the next classes I would look at next two or three classes I would look at what do you mean by spatial analysis the basics Patience's which already have spoken about a few of them but I would go into emphasis with some examples next I would look at advanced spatial analysis which again some examples and finally I would end this particular week with what are the limitations of having geographical information system in place so this would be the entire course of B so in today's class we let us understand what do you mean by remote sensing okay so in in this class I would give in a just sneak peek into what do we understand by basics of remote sensing what what do you mean by a remote sensing are you really doing a remote sensing when you are actually looking at a through this particular set of video slides and when when you are looking at this remote sensing what are those principles that you have to understand when and how they actually interfere into your to form an image is what we have to understand and finally I have given a small set of introduction to what do you mean by different resolutions for example we were speaking about data when you are looking at data it means to say that the data has to be measured in certain form now if someone is trying to use a satellite data okay so satellite data has different qualities or we just called as resolutions okay there is a first and the foremost thing that you have to see in a satellite data so in order to understand that I have included what do you mean by a resolution a spatial resolution or a spectral resolution or radiometric resolution so this is what would be the flow of today's class so when we for example when you are looking at this particular video lecture so you are actually sensing it without being in a contact with the person who is teaching it yeah so when you are not in a physical contact it means you are remotely sensing this particular presentation which I am trying to do which means I am remotely present and you are trying to analyze who our grasp whatever I am trying to inform it to you that's nothing but remote sensing so if you want to define a remote sensing so let me very specific it is assigned an art of obtaining information okay information can be information as the last part of data analysis and remote sensing which becomes data for us okay so it is a science and art of obtaining information about an object it can be an object it may be you are building it may be any draw type it may be a soil type it may be water type an area entire city entire colony or it may be any of those regions or a phenomena it may be your landslides it may be your earthquake it may be your for fire or it may be of floods so these are phenomenon so it can be an object it can be area or a phenomena through the analysis of data acquired by a device that is not in physical contact so now if you have a camera here and you are trying to acquire a object area or a phenomena in your camera in your mobile phone camera then it because you are remotely sensing an object area or a phenomena which is under investigation which you are trying to capture okay for example when you take up when you take our selfie so what are you trying to do basically you are trying to capture yourself acid maybe as an object and trying to place it in your lens that your camera captures so it captures certain certain amount of light okay so that is nothing but sensing remotely so you are not in contact with that particular sensor right so you have a remote sensing object which is nothing but a camera and you are taking a picture the similarly the same concept applies with satellites which are placed somewhere around 900 800 to 900 kilometers away from the earth surface okay so these sense the Earth's surface in terms of whatever is a display whatever is the object area or a phenomena based on your application you try to see that what what kind of information that you need so that is what is remote sensing when you look at mode sensing you have two types one is called passive other one is called active so when I for example if there is a sunlight the source of energy which is not emitted from the satellite and this hits the Earth's surface and there are certain amount of reflections that is again captured by the satellite so satellite doesn't have a source of energy then it is called a passive remote sensing if satellite has its own source of energy by various means for example when you are looking at microwave remote sensing okay so you have your own source of energy which hits the Earth's surface and the certain amount of reflections are then captured by your sensor onboard those satellites then it is called an active remote sensing so when you look at this image here here the passive remote sensing is done using a Sun solar energy which is 99.99% of the time okay so here you have a satellite which is sending out its own form of energy which is hitting the Earth's surface and then it is captured for back in the sensors placed onboard the satellite this is called active remote sensing okay so when you look at remote sensing you as I said you have a passive remote sensing you have an active remote sensing but when you look at different sensing system you have satellite remote sensing you have a high altitude low altitude and a ground level when I say satellite satellite is at about 900 - 900 kilometer away from the Earth's surface high altitude systems are placed at least at our 20 30 kilometers from the Earth's surface or a bit away so that it can capture a certain amount of area low altitude remote sensing is normally done just above the ground level which may be about maybe a kilometer or another two kilometers away from the Earth's surface but ground level remote sensing is on the ground so you have a sensor that is almost closer to the ground level so that's how you do the remote sensing so now you have drones which again have the low altitude remote sensors so that all don't fall into the aspect of our UAVs fall into the aspect of locate your remote sensing now once you have sensed the data this data is either in the either then transformed into a digital data which may be the form of a raster image or it may be in the form of a numerical data if it ascends in a certain aspect or a certain phenomena or it may be in the pictorial data only the captured image that has been considered or it may be in the form of a reference data so reference data is extremely important when you want to validate remote sensing data so you need a reference data so it is in the form of a reference data so once you have acquired these sky of data products okay the next step is to interpret so what I am trying to tell you is how remote sensing progresses how remote you have captured the data and how it actually forms add information to the user okay so next thing is interpretation once you have captured this data you have to interpret either in the visual interpretation or in a digital information tur predation use various algorithms sophisticated algorithms to do all kind of analysis whether it statistically whether it has numerical so you try to use a lot of algorithms or there are methods where you do visual interpretation where visually you will say this form of this is a particular part of that surface which belongs to this cutting category so that's the third step and the fourth step is providing an output to the user it can be a map it can be majors it can be numerical reports it can be technical reports so depending on what category of users are you are trying to give the information do it it is dependent on such users for their analysis so you will give that kind of information so now when we look at these two things you have two types one has data acquisition data analysis and the user so now data acquisition means you have practive or a passive or active sensor sensing systems which are either passive or active sensor then once you have acquired the data then data products are in certain format this is then started to look at by the analysis analysis either is done by the sensing agencies for example in RAC also has a lot of other agencies like sac IRS etc which actually do a lot of a lot of work on this kind of remotely sensed data you would have probably seen a lot of work especially if I have to highlight a works a walk with when there was floods in Uttarakhand and very recent of the earthquake etc so all of these are actually captured and very nicely analyzed by the agencies itself and there are users who actually take these data and use them and also produce reports it may be technical reports it may be output it may be peer review papers it may be majors maps etc so these are the two we're two parts that we can distinguish an distinctly say that remote sensing is made of one is acquisition and the one is analysis so when you are looking at remote sensing as an a complete package the first thing is you have a source of energy for example here I have considered Sun as a source of energy the solar energy hits the Earth's surface there may be many things on the surface it may be high rise it may be low rise etc okay paved roadway of soil or wet soil grass water forests okay so a grassland so all of these they have their own reflection ability reflecting ability okay though the reflecting ability is very different for each and every surfaces on earth odd objects on the Earth's surface so this if the amount of reflectance that reaches the satellite is then captured by the sensors onboard the satellite this is what is then converted from an unlock form to the digital form and then given to you as a data it's when when the data is sensed by the sensor it is normally in the unlock form then you convert it into a digital form and when I look at the digital form for example you you would have sumed into certain earring images while if you just take a photo of yourself zoom in as much as possible so you would look at pixels so each of these pixels because it's the presenting certain amount of reflection has its own digital number okay so that's the amount of reflectivity that is there okay so it represents a digital number that is that is what is captured by the sensors on the satellite okay so that is amount of reflectivity of each and every that is that is what differentiate every aspect on the earth surface area it's a phenomena whether it has an object area or a phenomena what whatever it is so that amount of energy that is actually recorded on board a sensor is very different from each of them and that differentiate differentiates everything okay so and the very important aspect that you have to look at here is the first thing is electromagnetic spectrum so I hope many of you would have learned what you mean by an electromagnetic spectrum but electrical field and magnetical field are propagating at 90 degrees is nothing but an electromagnetic spectrum okay so now when you are you let's say that this is the wave that is actually propagating I have just taken either electrical or a magnetic field the distance between a successive crust or a distance between a successive Rock okay either this or this is called as a wavelength okay and number of cycles passing for example this is one cycle okay passing at a particular point of time is nothing but your frequency okay so when you look at this this is can be explained very clearly by the loss of energy the same loss of energy is applicable in terms of remote sensing when there is longer wavelength you have lower frequency when you have lower frequency you have lower energy when you have shorter wavelength you have higher frequency and higher energy let me explain it to you by the this particular equation if you have looked at energy of quantum it is easy called H nu which you can see here okay when you look at it it is he is equal to H nu okay when this particular aspect is considered okay frequency is C by lambda okay where C is nothing but your constant or the speed of light and lambda is your wavelength so which means that e is equal to HC by lambda okay or e is equal to H F right so now energy is directly proportional to the frequency so lower energy lower frequency energy is inversely proportional to the wavelength so energy high lower energy longer wavelength higher energy shorter wavelength okay and het is a Planck's constant which is 6 point 6 to 6 into 10 power minus 34 joule-seconds okay so this is the first principle that you have to understand in terms of understanding the remote sensing okay so energy of a quantum or quanta is measured as is called HF or H nu so nu is nothing or F is inversely proportional to the wavelength that is H is equal to C by lambda so F is equal to C by lambda so U is equal to HC by lambda so when you look at this equation frequency is directly proportional to your energy and when you look at your wavelength it is inversely proportional to the energy so how does it affect your remote sensing if you ask me how does it affect for example you if you look at your frequency range if you go back to your electromagnetic energy distribution so if you have the lower wavelength it will have higher energy which means your visible spectrum or even below that will have higher amount of energy whereas your the ones which have higher wavelength will have lower energy or longer wavelength will have lower energy so it is easy to capture more amount of information when it is offer in a low a longer wavelength oh sorry in a hi ina a shorter wavelength but with high energy and high frequency so this is how it is implicated in your remote sensing okay so when you look at the entire electromagnetic spectrum that's what I was trying to explain if you look at this the radio waves is in this region okay then you have certain part of the microwaves where you that our that actually worked okay then you have a certain part of energy which is actually the visible energy okay which is here Oh point for micrometer to 0.75 micrometer okay so when you look at this part of the energy you can see that this is in the lower end of the spectrum okay which means that it has it is in the shorter wavelength region okay once you have saw a shorter wavelength region it means to say that it has higher frequency once it has higher frequency it means to say it has higher energy okay so that that is what I intend to explain here then if someone asks you what is the wavelength of region of visible region you should be able to say it's 0.4 micrometer to 0.75 micrometer okay so that's that's very important when you are actually explaining the electromagnetic spectrum then you have ultraviolet then you have soft x-rays and this in this is it is also called as infrared where this is the short infrared mid infrared and far infrared and then you have thermal infrared okay until 10 ^ yeah so until 10 ^ our 15 then you will have hard x-rays and gamma rays okay so that is about the electromagnetic spectrum okay to give you more understanding about it if you look at the wavelength here this is where the visible region is there and if you see the wavelength is shorter when the wavelength is shorter it has higher energy the energy is very high as a wavelength increases the energy decreases so when you look at the Sun sun's length is somewhere here okay so energy is much lesser when you look at the Earth's surface you can see it here the same thing is very much our receive creative in terms of transmission okay so I'll speak about this in when I speak about other to loss but why I am very particular about this is to just understand how the energy and wavelength are related and when we come to the next law as the stiffens pores Boltzmann law which states that it has W equal to Sigma T to the power of four okay where this is a constant which is T at a Stefan Boltzmann constant which is five point six seven approximate it is five point six six nine two so it is approximate trudeau 5.67 multiplied by 10 power minus 8 watt per meter square per degree Kelvin sorry per Kelvin to the power of four okay so if you look at this okay this particular thing this has Stephens holmen's law then you have total radiant immittance which is watt per meter square and T is absolute temperature okay of the emitting material okay what are the material that is emitting that is nothing but T so now when you look at this if the immittance from the material okay the total radiant it means radiative the one that is coming out after absorption immittance is proportional to the fourth power of the temperature so higher the temperature okay higher the immittance lower the temperature lower is the immittance okay this is one the next law that we can we have to understand this means displacement law which states that lambda is inversely proportional to the temperature which means that wavelength is inversely proportional to the temperature now if the wavelength is higher temperature is lower if wavelength is lower then the temperature is higher so which means to say that lower wavelengths here have high temperatures and higher radiant immittance lower wavelength will have higher temperature and higher immittance whereas lower higher wavelength will have lower temperature and higher radiant immittance so this both of this law has to be understood in interference so that you understand how this is related to your earth surface okay so I hope you guys have understood this let me go to this example to explain you much more so what did we say W is proportional to the fourth power of the temperature and lambda is a by T correct which means higher the wavelength lower is the temperature if the temperature is lower then your ma immittance of the radiant immittance is lower now I have plotted a curve which is all spectral radiant immittance okay versus the wavelength and when you see it this is where is your exactly the visible wavelength okay and where you look at the visible wavelength that temperature is of a blackbody when I say blackbody it is a hypothetical body where which has complete absorption and complete immittance so when you look at the temperature of the blackbody is the highest and that is where is exactly your visible region located which means that the it is easy for anyone to capture in the visible region that is why human is able to look at visible region mean by his own eyes so that is why you can easily connect with RGB any of your colors are with the primary colors we just red green and blue okay so when you look at this this is blue green and somewhere here is red okay in the electromagnetic spectrum if you look at the blue can be some around 0.4 to 0.5 where Green is 0.53 2.63 okay and you are read somewhere Oh point six four to 0.75 okay so if you see it is a maximum the blackbody radiation is at the Sun temperature is maximum that is 6000 degree Kelvin and that is exactly where is following a falling on the visible region and when you look at this earth's temperature if you look at adds temperature back body radiation is about 300 degree Kelvin where if you see the wavelength is much lower and hence that amount of immittance is much lower so if you look at it anything sensing here may have a lot of loss because most of the energy would have been absorbed and the very less amount of energy is emitted back okay so that is the example that I am trying to tell you that how it is different from each other okay to explain it to you more about how this works first you have the solar radiation okay let's say this is solar radiation that is coming into the Earth's surface so let's say this is Sun okay now once you have the solar radiation you have a thick layer of atmosphere here all right there you have a phenomena called as scattering and absorption due to either scattering or absorption or due to both there will be a certain loss of energy okay now with this loss certain amount of energy reaches the Earth's surface now in that let's say there is certain amount X loss okay now with this some amount of energy is reflected some amount of energy is absorbed by the Earth's surface surface or object etc some amount of energy is reflected right so this mo energy that is reflected this again transmitted in that Monsieur again you have atmospheric interference and you have certain loss this after this the amount so you have three kinds of losses where certain amount of energy is absorbed here certain amount of energy aside the scattered or absorbed in the atmosphere then again while going back you have certain amount of energy that scattered out Monsieur the amount of energy that is reflected energy that is left after the atmospheric transmittance then that is the energy that reaches the satellite that is recorded into the satellite that is what you would get as an image once it is converted from analog to digital signal okay so this is this is exactly the process of how remote sensing is done using a satellite okay so this just to give you a flavor there are more you know things that you have to understand if you have to understand this specific object aspect in much better way okay so this is just our view of how it actually works the other thing that we look at when we are understanding remote sensing is nothing but a spectral reflectance curve when I say a spectral reflectance curve it is the curve where Y axis is the reflectance that is the amount of energy that is reflected back from that particular object after all this loss is there the amount of energy is captured versus the wavelength okay for example if we consider vegetation so if we look at vegetation vegetation in M above in this let's say this is let this is a blue band this is a green band and this is the red band okay that band is somewhere till here okay not till here so if this is the red band now you have green and red so now when you look at this blue it has a very less reflectivity in the green band it has a little amount of reflectivity in the red band it comes down the reflection is reflectance is only 10 / 10 percent or even less okay then in the near infrared zone it has very high reflectance okay which means to say that vegetation has the characteristically reflects in the near-infrared band now if you use your eyes to measure the reflectance of vegetation okay it your naked eyes will not be able to distinguish between two vegetation because you you would not be able to sense in the near-infrared band whereas when you sense in a sensor which actually captures the reflectance so you could easily I dis distinguish between two different plants or two different characteristics of a plant which where the reflectance in the near-infrared band so that is high very high in vegetation and when you go ahead it has three dips here and in or under dip in 2.7 so this is called water absorption bands okay this is exactly for studies of vegetation the water content etc and its relationship okay so this is the characteristics of your vegetation for example if someone wants to understand what is the amount of vegetation versus non vegetation he or she would actually compare two things one is you have very high reflectance in near-infrared band and have a very low reflectance in red band so that is how people calculate our index called NDVI which is ni r - r by ni r + r okay so which gives you the normalized values of vegetative index the positive values are indicating the vegetation higher the positive value is attica the vegetation lower the values as the sparse vegetation and if you look at the value of closer to 0 is actually representing water and there the reflections that are much in the negative value is actually representing soil okay or non vegetate of characteristics so that is how people that is how you can understand the difference in the characteristics on that surface one example is what I gave it as nd VM and when is similarly if you add the aspects of water water has higher highest reflectance in the green band and lower reflectance in the red band and complete absorption in all other bands so if me it means to say that if you use an near-infrared band water is completely absorbing and hence it should be looking black okay so if someone wants to just extract water he or she would just take a near-infrared man and wherever it is zero or a certain values it may be it may not be exactly zero because there may be certain are characteristics of that particular water body which may be emitting certain amount of energy it may be that they may be plants they may accept so you look at exactly and just see that if you can with that amount of digital numbers it can be easily separated as water and non water okay that's that is called as thresholding okay so this is one aspect of water and you have this is the reflectance curve of soil so based on the same reflectance curve you can look at the various properties of the soil it too has water absorption bands here which is actually representing at one point four by one point nine and two point seven so amount of water so what present in the soil can be easily measured at this particular point and there are huge number of studies in understanding this particular reflectance curves so having understood all of these these are very basics of remote sensing the very important aspect that you have to understand is the spectral reflectance curve if you have understood that most part the very basics of the remote sensing is actually understood by you okay I if someone has an access to a spectral radiometer please look at how you can measure different plants different soil so you will understand how this particular spectral reflectance curve was as well as wavelength is actually computed once we have understood that let's go to the satellite now as I said satellites what we are trying to understand here is the polar satellites basically I I would be very much concerned about the passive remote sensing and when you are looking at any of the satellite data the first thing that you have to see is the metadata the second thing that you have to always look at is the different kinds of resolution be if you have the data already with you if you are if you do not have a data already with you then the first thing that before even considering any data you should understand what kind of what kind of resolutions that you need okay for example if if someone is looking at how the growth of a city is happening or city pattern you are trying to understand there is no need to actually buy a very highly a very costly high spatial resolution data okay but if someone wants to really see the building wise or the road wise information of a particular city then you need to have a very high spatial resolution data so first understand what is the application of your data okay without understanding the application of your data it is impossible for us to understand why that particular data has been considered or it will be it will be really and not an real aspect of working on the data so when you want to buy a data first thing or download a data the first they are four things that you have to understand this spectral spatial radiometric and temporal no temporal is completely with fixed when the satellite the sensors are actually placed on the satellite but the three things that other three things are extremely important for your analysis the first thing is spectral resolution the second one is the spatial resolution and third one is the radiometric resolution so these three have to be looked at even before you buy a satellite or download by a satellite data or download any satellite data okay without understanding these spatial as these aspects of any satellite it would be really a problematic issue if you are trying to download any data okay so let's let's go by each one of them the first thing is spectral resolution when I say spectral how far when we have looked at the EMR spectrum okay if if we try to draw this okay let us say these have the wavelength point this is the wavelength okay point five 0.6 0.7 okay then you have 1.2 1.4 1.6 then 1.8 and so on okay now if I try to use okay let's say our satellite sensors are able to categorize these each of this electromagnetic spectrum into different bands for example there is one satellite which can capture this spectral band this spectral band this spectral band and this spectral band and the spectral Bank this is the spectral resolution of that particular satellite which means it has one band two three four five which means say that a satellite has sensors which can capture in these different bands so this is nothing but a spectral resolutions okay it is extremely important in terms of what kind of resolution for example if you are trying to understand vegetation you need to as I said you have some very high reflections are near infrared band and then have a low infraction refraction reflections in the red band so you will obviously consider satellite which has all of these bands if you are using it for a variety of applications you would probably look at those applications and look at what kind of how many number of pants you need if a satellite is then capturing this as entire entire electromagnetic spectrum in single sensor okay then it is called a pan chromatic bad okay ara pan ban okay this means to say that this entire spectrum is then captured it may be this entire spectrum it may be this whatever the spectrum it captures so it when it captures then it is actually said as panchromatic image okay specifically normally it is done until here so it once it captures this then it's called a panchromatic band and this panchromatic band is has only one band or one specific image but these when i said there are different sensors which is capturing a different regions it means to say that these are different images okay so different multi images so it is multi spectral it is called MSS image okay are multi spectral sensors so you have multi spectral sensing okay so when you look at this you have collection of image if you are actually collecting everything in a single strip then it is called a panchromatic this only one particular sensor or set of sensors capture the entire region okay now the very interesting part is that if instead of this if I capture like this very narrow spectrum then it is called as hyper spectral sensing okay so if the entire spectra is captured by a single sensor and single band then it's called panchromatic if the entire spectrum is captured by multiple sensor it's called multi spectral sensors and our multispectral images and if it is captured by yeah if you narrow spectrum of a band and you have a huge amount of bands at it has been captured then it's called hyper spectral senses okay this about the spectral resolution to just give you an example of what do you mean by spectral resolution if this entire I have just taken a visible wavelength so if if the visible wavelength from from 0.4 to 0.7 micrometer this is one of the examples from Canadian Space Research Center which explains how the spectral resolution is there so when you if you look at the entire from point four to 0.7 is sensed by a single sensor and you have an output as a image as a single image then it's called a single image or it's a spectral resolution is one if the same energy spectrum this is 1 this is 2 this is 3 is broken into 3 different there are sensors and each sensor is capturing at 3 different wavelengths then it has its spectral resolution is 3 now it is sensing at different 6 different it has broken the same thing into 6 different parts so 6 different sensors are capturing it so which means to say that this is this spectral resolution is 6 okay next concept is the spatial resolution and when you look at spatial resolution it is the finest area that you can look at in that particular image okay or it can be defined as how much a pixel can capture in in its own place for example if I say it's a 30 meter pixel the spatial resolution is 30 30 meter so it says that as pixel carries 30 meter by 30 meter information in that particular pixel if I say 1 meter then it says it pixel can carry one meter by one meter information okay so just to give you an example of how what what are different so the first this is our original image which is one meter resolution so you can see very fine details of that power of a set of buildings and this is called a very high resolution image okay you have submitter also now you get images at 25 centimeter 60 centimeter 90 centimeter etcetera so this is one of those a very high resolution data Indian satellites have very good capability of capturing at now at even the submitter levels so you can find out you can contact national image sensing center for any of these data products which you can always acquire then the same image is then resampled to 2 meter and the same images is sample to 30 meter okay so which means this particular pixel here and the pixel here okay this pixel is representing one meter by one meter this pixel is representing the 30 meter by 30 meter which means it's more this is a coarse resolution data 30 meter a pixel is of course a solution data whereas this is a one meter is a very fine resolution data or a very high resolution data okay so this about resolutions and if you want to look at it pictorially this is 30 meter by 30 meter if a house is picture this is the house okay if this is picture is 30 meter by 30 meter in one pixel let us say the same house if it has taken into 5 meter by 5 meter you can see the number of pixels that is it is being denoted into so maybe one part of the house your dining room or your kitchen maybe in a sir in a pixel okay the same house if it's if it is captured in a one meter resolution sensors then maybe even a very small part of a kitchen okay maybe your kitchen sink is actually coming in a single pixel okay so that is what is the difference okay just to give you an Representative features of how the resolution is is important so spatial resolution is about how much area it actually covers in a pixel spectral resolution is how the sensors can actually capture the electromagnetic spectrum into number of bands and the third one is the radiometric resolution so when you look at radiometric resolutions it is about how how many radio meters that this has for example if you if your picture can or your sensor can picture eyes at that particular part of the Earth's surface in only 0 and 1 okay then it's called a 1 bit resolution or radiometric resolution is 1 if it can capture between black and white say this is black and white always your image that is captured in different sensors in this in the gray levels so if the gray levels range from black to white so if number of gray levels is 0 to 3 that is 0 1 2 3 then it's called a two-bit radiometric resolution is a is 2 if your gray levels is represented by 0 1 2 3 4 until 255 which means it has 256 levels then it's called an a radiometric resolution is 8 okay and if you have 10 bit then 5 the ranges will be from 1 to 2023 I was speaking about digital number so when I say radiometric resolution number of gray levels that can be represented it is same as your it is equivalent to your digital number higher the higher the digital number will have higher radiometric resolution lower digital number will have lower radiometric resolution details for example if if your image if you have water if you have actually acquired a Landsat data Landsat data is a 8-bit data which means it's radiometric resolution is 8 and its values lies between 0 to 255 0 is completely black if you take an infrared image 0 is representing a water body so it is completely black and whereas 255 would be representing the highest reflected object from the Earth's surface so just to give you an example of 8-bit and 2 bit if you look at it here 8 you can it is easier for you to understand different aspects on the Earth's surface whereas in your tube it is very difficult for you to understand different objects on the Earth's surface because it can distinguish only four different colors from in great kirok combinations whereas an 8-bit it can actually look at eight different great combinations at different instant of time that is why I hire the radiometric resolution better is the quality of your data okay now the last thing is the temporal resolution when you look at temporal resolution it is often how often that a particular satellite can capture or a sensor can capture the same part of the Earth's surface for example Landsat has 16 days Eichner has 1.5 days for a multispectral sensor and up 2.5 days for a panchromatic sensor mode is on an average has a 16 day repeat but one to two days coverage okay these are different sensors very interesting sensors or satellites and sensors you can look at all of these and Aviator is one one of them were nine day repeat cycle and you have jaws which is about 30 minutes so this this is about temporal resolution it's the last kind of resolution that s actually to be understood so to summarize this particular class we have looked at what you mean by and what do you what do you understand by electromagnetic spectrum first we looked at what is remote sensing then different parts of electromagnetic spectrum and loss we started with energy of a quanta is equal to H nu then we looked at Wiens displacement law so once they asked events Boltzmann law and Wiens displacement law so once we have understood this when we looked at a spectrum the flatlands curve okay so it is a reflectance versus a wavelength so whenever you are looking at any aspect of the Earth's surface or when you are trying to capture it first thing is look at the reflectance curve then is the resolution so we ended the this particular class by resolutions of satellites where we are looking at what are different resolutions that you have to consider when you are considering the satellite data products so this is just about a small part of remote sensing in next class we would go back to GIS we would look at what are the basic spatial says very advanced special analysis in the rest of four classes of this particular week thank you very much see you in the next class