 Hello everyone, welcome to the next lecture in the topic remote sensing data, data portals and processing tools. In the last lectures, we are discussing about the various remote sensing data sets and saw few examples of what we can get from the multiple remote sensing satellites that are available. And also some of the commonly used data portals from which we can download the data that also I have introduced you all. So feel free to explore those portals on your own in your free time and try to use the max to the maximum extent. So we discussed some of the commonly used data portals in the last lecture like Earth Exploder, Booven, Mosdag, they are all very widely used. There are like even other portal, simple data portals which are often not known but again provide some data access to us. So one is the Glovis portal, globevis.us.gov given here. So a browse based viewer where we can visualize the software basically which is available especially Landsat, Hyperion which is a hyperspectral data, Sentinel-2, Global Landsat, it is basically like a visualization platform primarily. Then also we can have a look at like Landsat data using what is known as a Landsatlook.usgs.gov which is that allows rapid online viewing and access to Landsat archive and Sentinel-2 data. So even before downloading the data, we may have to just take a look at how the data is. Say I need to download the data but if half of my image is covered with cloud, I may not download interested in downloading it right. So such visualization is also really important when you are searching for data. Without visualization, downloading may be a waste thing like after downloading if we realize the data is fully covered with cloud, it is like a waste of the download and all the data we used up right. So visualization actually helps us even before downloading we can check it. These two portals are primarily visualization tools but still we can use. But within the common data portals itself it is available but I just thought of telling you this. So with this again we finish our discussion about like the data portals then we will move on to data analysis tools that are available to us. So now we have discussed about data from where to download data. But before we use the data using all the principles we learned, we need some tools to use right. So those tools range from freely available open source tools to extremely expensive commercial products. Each tool varies in their capacity or capability to process certain kind of data, only certain kind of processing on algorithms can be run on software all these things. So we have like a very wide spectrum of processing tools. But also nowadays with the advent of programming languages where most of the students are interested in doing programming it is always easy to process data on our own like GOTF data, HTF data, whatever different formats I told it is very easy to use some sort of programming language like Python or Matlab to open them to visualize them to code them. But even without coding capabilities we can process the data. But some sort of processing tool is always needed as a interface when we want to use the data. Without processing tool the data will be there lying idle and in order to get maximum benefit out of the data definitely we need a tool. So that is what we are going to see. Lot of commercial vendors are there, commercially available products are there. Some of the famous commercial products that we can use for remote sensing image analysis are like ERDAs, Imagine, NV even like RGS which is like a very famous GS software we can use it for like remote sensing image analysis to like a very good extent and so on. So these are all commercial products but these products normally will be available in research institutes and academic institutes where the students and researchers will have access to it we need to purchase a license to them and do it. But as a common man say normally we as an individual cannot purchase licenses to the software and they may be expensive only for certain projects or something we can purchase license or for academic reasons we can purchase license. But if as an individual if I am interested in doing some remote sensing analysis is there any tool available means yes there are again plenty of tools available starting from just visualization to large scale processing. So we have like lot of opportunities now that is why even in the first lecture of the topic I think two lectures back I told you this is like a golden era for remote sensing earth observation because of the variety of opportunities that lies in front of us. So among all the tools that are available to us we are going to discuss only two of them one is a snap toolbox and another one is Google earth engine. So snap toolbox is we can it is kind of like a software we can download it install it in our computers locally download all the data process it in our machine it or everything happens locally in our machine we have to download everything whereas Google earth engine which is becoming famous rapidly in the last few years like within last 10 years it has gained tremendous popularity and even many global applications are using this particular cloud based platform. So Google earth engine is kind of like one of the most powerful tool available in cloud where we need not download anything it provides us a good interface where we can just see the data process it in the cloud and get the outputs. So we will get briefly introduced to two of these like these two data processing tools. The first one we are going to see is snap sentinel application platform developed by European Space Agency as like a free and open source platform for remote sensing data processing and analysis. Basically it was developed to process the data from sentinel satellites sentinel 1, 2, 3 but in addition to sentinel 1, 2, 3 missions all other commonly used satellites data also can be processed within this tool. So it is again it is a software we have to download and install it. So when you search for snap toolbox we will have different options like we can download the tool only for sentinel 1 which is a SAR mission we can download only that particular toolbox or sentinel 2 which is optical like this we can download the particular toolbox or we can combinedly download everything and download the entire snap toolbox platform and use it for processing everything. See this is kind of like a screenshot taken from the snap toolbox with the option of processing optical data sets. So this is like we have installed like the entire toolbox and here we are displaying what all the different optical data sets that we can use. You can see how many data sets we can use and process within this sentinel toolbox. It is basically sentinel 2 toolbox where we can process optical data. So in addition to sentinel 2 mode is we can process, VR is we can process and spot world view. World view is like a commercial software Landsat which is like freely available one of the most widely used platform OCM 2 which is like Indian remote sensing satellite that is available. So many different data products from different satellites if they are in optical domain it can be processed within this particular toolbox. But processing means what? Generally there is like a separate course digital image processing or which is offered to the students which talks about the various processing that one can do. You can just open the data visualizer. It is kind of like a processing. You can visualize the data you can what to say removing the data of atmospheric effect. We have seen certain steps right how to atmospherically correct the data that is again a data processing. If we have certain tools it will do processing for us or we learnt about different spectral vegetation indices NDVI, EVI and all. So starting from DN, DN to radiance, radiance to reflectance, reflectance to vegetation indices. It is kind of like a processing chain right everything can be done within the tool. You can open the data and do all the processing. So step by step the sequential processing can happen within this particular software. So it is kind of like a platform where we can do this processing. So this is possible within this SNAP tool. So here this is an example for optical datasets. Similarly this slide tells us the different SAR sensors like synthetic aperture radiometer sensors sorry not synthetic aperture radar. I am sorry it is not a radiometer synthetic aperture radar active remote sensing sensors which we can use. Sentinel-1 which is like freely available apart from it. RadarSAT, TerasRX, TandemX, AllosPulsar, ERS, NVSAT there are like many different synthetic aperture radar data that are available. Some of them are commercial, some of them are freely available which we can download and use. Again processing can be done within this tool like I told you right we can download the data convert the data from slant range to ground range converting the amplitude information into backscattering coefficient like in radar imagery we will be interested in calculating sigma or not backscattering coefficient that is possible. So all these processing steps we can do. We can like do speckle filtering like speckle effect we have seen what it does noisy grainy pattern in the image like pepper and salt pattern that can be removed using some sort of filters all these kinds of processing can be done within the snap toolbox. So snap toolbox offers us powerful option to do most of the commonly done analysis with respect to remote sensing images and this is like available completely for free which we can install in our computers and use it. But remember everything happens locally. So our machine should be machine means computer should be good enough to install the software and run. If we have like a old generation computer the software may not run or when you try to open a Sentinel-2 data in like a normal laptop like normally what we use it for online classes it may not be enough. So some good quality laptop or a computer may be needed when we want to process the data or it is good to have like a normal desktop computer with moderate capacity to run this particular thing. Anyway the if you like search about like the snap toolbox you will get information about like the basic system requirements and what are other things we need. But installation is extremely simple just with the click we can install and even processing is simple with lot of manuals available. Help files are there, manuals are there which we can read on our own understand and do it. So the final thing we are going to see in this topic is the Google Earth Engine. So Google Earth Engine is a cloud based geospatial processing platform which is designed for global scale environment data analysis. So it is kind of like revolutionizing the way we are doing remote sensing data processing. Now most of the large scale projects working in global level have moved to this Earth Engine platform because normally say I want to analyze data for the entire globe means I should have a powerful computer which can store all the data and should be capable of processing all the data. So it needs some capital investment. But if everything happens through cloud means I can just have a normal computer as the cloud to work for me that is possible right because the cloud it means like the server and the computing power rests somewhere and just kind of like using a client I am just initializing it and analyzing the results sitting in the comfort of our home or offices without the need to do large scale capital investment and developing the infrastructure. That is the advantage of having Google Earth Engine. It has see like many different scientific papers are coming out global forest mapping using Google Earth Engine, Google Earth Engine for agricultural applications, Google Earth Engine for flood mapping, many different things are coming up which is kind of slowly changing the way how we do remote sensing data analysis. But it is not the one-stop solution I will say, but it has a very huge capability to do it. So it allows us to visualize, manipulate, edit or create spatial data in easy and fast way. It has access to more than 30 years of historical imagery and other scientific data sets. If you want Landsat data it is available, mode is data available. If you want data from some re-analysis product say some modeled atmospheric outputs available. So everything is available within this portal we need not download them actually we cannot download the data sets we can just open them in the cloud whatever processing we have to do we can do it get the outputs maybe the final maps and all we can store and use it for further analysis. So we can it is not only a data portal like data portal means visualizing and accessing the data, but it also acts as a processing tool. It provides powerful APIs, application programming interfaces using either JavaScript language or Python programming language. If we are familiar in any one of the language even like a basic introduction to those languages will help us we will be able to do whatever programming we want to do data analysis. So the basic framework to do all the thing is there. So Google earth engine provides us with a code editor. So the code editor is kind of like an online IDE integrated development environment. So IDE is nothing but a place where many different things can be combined and done in one go. Okay you can like code you can like analyze everything. So this provides like an integrated environment where you can open the data visualize it run your codes see the output everything can be done in one particular place. Also it has capability to upload our own data sets. So I have collected some data from ground. I want to merge it with other satellite data sets which is possible. I can upload the data to my own portal within this cloud platform analyze on my own get the results that is possible. And for most of the academic and research purposes they provide free access. We have to first register for this. Once we register like you can always search for like a Google earth engine code editor. Once we have a Google account we can just go register for it and request an access. If we are from any academic or research organization they will immediately grant access within a few days. Once we have it we can access the code editor and do our analysis. Say this is how a basically a Google earth engine screen may look. So this portion is actually the map where we can see the map. If you want to open a satellite image say I am opening a satellite image over Mumbai it will be displayed like this here. So all these things is possible or if I have some output I can see my output being displayed here. So that is possible. This is a script manager. So the script manager tells us what are all the different codes that we have written or what are all the different codes that are available to us. There are like plenty of different pre-written codes available. We need not write everything from scratch. Say to calculate NDVI we can just call a function to do land use, land cover classification. We can just call a function. Everything is possible within this. It provides us with lot of documentation, API documentation which are kind of like help files we can read and understand the algorithms. Asset manager basically whatever we create we call it as asset we can store it see them. Like I am creating one particular code to what to say analyze all the satellite data set to capture drought prone areas. So that is one asset. So now next I am creating another asset to map land use, land cover that is possible all the thing it is done. It has a search bar which we can use to search data sets or places. This get link button. So the get link is say whatever we write code here we have to write here. This is the code editor basically all the codes we will write here. If we want to share the code with someone else this is this won't be publicly available whatever we write will be available only within our Google account login. If I want to share this with someone else like we are working as a team I am writing a small code snippet means I can get the link and share they will have access to this. So that get link is kind of like a sharing tool and then save button to save the script run to run the script and all. This shows us the console output tells us whatever output we are asking say print something it will print and all. We can inspect all the values or objects that are displayed on the map and everything. So this is what I have told us like IDE. So it provides us like a complete environment. You can do your coding here, you can do your visualization here, you can observe your or check your variables in this console whatever you need some sort of codes it is available here. So it is kind of like a huge collection of data as well as data processing tools. So the map geometry tools are available like you can pan the map, you can move, you can zoom in, you can pinpoint a location that things are available here label number 12. So this is like very basic introduction to Google earth engine. In addition to this we can there is a open source GIS software called QGIS which is again like freely available open source which is also we can use it for some sort of like data processing we can use it. It is also like a GIS software where which we can use it for analysis purposes. So there are like plenty of options available. We need not as an individual user we need not go for a commercial vendor but commercial software provides us lot of flexibilities many different capabilities that are not there here I accepted. But as I told you some of it may be expensive and as an individual we may not have access to them. So under such circumstances these openly available tools will come to our aid. So as a summary in this class we discussed about two of the commonly used data processing tools snap engine and Google earth engine. So altogether in the last two to three lectures we discussed about different data sets, data portals and data processing tools. So it is kind of like a providing you an introduction to this is like a big field okay this itself is like a very big field like if I want to talk about like data different data processing and how to do it that itself will require separate course. So the aim of this particular course remote sensing course is to provide you introduction. We have dealt with the theoretical concepts all the physical fundamentals that are required by a remote sensing student has been given to you the basics at least. Now we also got introduced to different data sets the portals from which you can download the data and some processing tools. So now we will move on to the applications part. So where we combine these data sets using downloaded using this data portals processed using these tools along with our physical concepts that we have learned using those principles what we have already learned how to use this data for various applications. So that is what we are going to see in the last part of this course. So the application part will be the last part and we will be starting it from the next lecture. With this we end this particular lecture. Thank you very much.