Exploring Earth observation data in the ODC workshop
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Adams, Caitlin
This workshop is designed to provide an introduction and demonstration of how to load data and manipulate it in the Digital Earth Africa Sandbox environment. We'll use this environment as there is no installation required and data is already available. The workshop is designed for people who are new to programming or new to ODC. Please see the accompanying documentation for this workshop to follow through here:
 Thank you so much for joining. We might give it a few minutes just to make sure everybody's online but I'm really happy to see all of you so far. I hope you were either able to attend the session already or that you're planning to attend some upcoming sessions if they're in a better time zone for you. I certainly know it's a bit earlier in the day on the other side of the world from Australia where I am. So I appreciate you all coming along. So yeah, I'll give it another like minute or two but then we'll get started. If you're keen to chat or feel like you want to introduce yourself feel free to put in the chat who you are and where you're joining us from. I'd love to see the different diversity and global representation that we've got going on. Thanks Alex for starting off the chat. Thank you. That's wonderful. We've got people from all over the world. I'm so excited. It's my absolute pleasure to be running this session with you and my hope is that at the end of the session you'll be a little bit more familiar with doing some programming with an open data cube implementation specifically for Digital Earth Africa. So we seem to be doing pretty well for people in which case I might get started. So I'm going to share my screen and just present a few slides to sort of introduce you to the workshop and a little bit of background. So thank you so much for coming along. It's really great that you're here, that you're participating in the conference and that you've taken this opportunity to get to learn a little bit more about how we can, you know, how you could use the open data cube to analyze satellite imagery. We're going to specifically be working with one of our open sandbox platforms. I did send around an email earlier if you had pre-registered for this session with some instructions for signing up but if you haven't yet don't worry at all we'll cover that as part of the 30 minute session that you have for working in a small group. So for this particular tutorial I'm just going to give you a little bit of background. I'm going to do a live demonstration of how to load. We're going to have 30 minutes to work through a tutorial again which I sent around earlier but again I will share with you when we get there. So if you're new to the open data cube I wanted to start by talking about the fact that it's a piece of open source software that's there to help you catalog and query specifically raster data. So images that come out of satellites it's really great for that. And what it really is doing is that it's providing a method for you to say here's where my data is located and here's how it's sort of sorted in time and here's where it is on my file system. And then what that means is that you can query that database to just pull out the pixels and the imagery that you actually need and want to analyze and that's what the open data cube enables you to do. So this is sort of well explained by these components so we have the open data cube as a whole but it's sort of split into you know where the data is sitting and those are the actual you know let's say geotiff files. Then there's the infrastructure which is what's interfacing between the data and also the applications which is how you're going to access the data. So when we set up open data cubes we have to build this index database that says here's where all my data lives either it lives in the cloud on s3 or it might live on your native file system. And once you've done that indexing you can then use these sort of various apps like Jupiter notebooks or web services to go and access the data that you need. But the indexing is pretty hard and so what we're going to do today is we're going to use an implementation of the open data cube that already has that index set up specifically over all of Africa. And for this implementation we're going to use Jupiter notebooks so this is an environment where you can write Python code section by section and see your results as you go. So I'm going to show you a little bit of what that looks like. Like I said doing the index is the hard part of the open data cube and the reason these sandboxes are great we not only have one for Digital Earth Africa but one for Digital Earth Australia as well is that the data is already there and you can just work straight with the open data cube like an API to work with the data. The other thing that's great about the sandboxes that you might notice in the picture is they actually come with a whole bunch of reference notebooks such as the beginner's guide that you can use to learn about how to actually achieve certain things in the open data cube such as loading data or plotting it. So the goals for this workshop you're going to find an area that looks interesting to you somewhere in Africa. Load a little bit of data for it we won't load too much just because you only have a little bit of time and sometimes the loading can take a while and then see if you can visualize it using the sort of standard RGB red green blue imagery plot. If you are feeling ambitious there's a scratch goal where you can take this data and calculate a satellite imagery band index so this might be something like the normalised difference vegetation index which might tell you about the health of different fields, yeah the different crops in these fields. So I'm going to jump in now to doing a live demonstration. So here's the digital Africa sandbox I've already logged in. You can see here's these existing folders that are really useful and this is how we create a new notebook. So I'm going to rename my notebook and call it ODC workshop. So the great thing is is that this sandbox is your space when you leave and log back in anything you put in here is unique to you. You have a copy of all these standard notebooks but you can copy them and edit them as you desire and just make your own notebooks. So now that we've got this I'm actually going to need to pick an area that we want to start with. So one of the easiest ways to do this is the digital earth Africa maps interface and the reason I really like this is that you get a really clear visual of the whole continent and you can sort of easily look about where look where data is available and get the information that you're going to need in order to load it in your data cube. So one of the nice features I think is that you can directly search. So this is pullback carer. I've zoomed in a little bit at the moment this is just a sort of background imagery setting but once that loads in I'm going to be able to use this as a sort of guide to find something interesting that I want to look at. So here I'm going to look at these irrigated fields. Okay so the thing I can do now that's really helpful is that by clicking somewhere on the map I can actually get some latitude and longitude coordinates and these are what I'm going to have to use to load my data. So what I'm actually going to do is I'm going to copy those and in my notebook I'm going to change this this is called a cell I'm going to change it to mark down and this means I'll plain text here that I can get back to later. If I press shift enter that actually just renders this plain text so this is really good for keeping notes of things I'm going to need. So I'm actually going to make a note that when I did that click I was sort of in the bottom left corner of where I want to look so I'm going to say bottom left are these coordinates. Perfect so I can get rid of that and now I can click up here so that's going to be the top right again I'm just going to copy those coordinates and pop them into here so that is the top right. Awesome and I do want to mention that I as part of that PDF that you'll work through for most of the session I have instructions for you to follow for all of these steps so there's no need to follow along live with me as I do this feel free to just pay attention and understand the different components that are involved in actually going and loading loading data. So now that I know whereabouts I want to load some data I'm just going to put a break in there so I can see them a bit more clearly. I can come back to my map and start exploring what data digital earth Africa has available so there's a big explore map data button here and everything's nicely cataloged so I'm going to look in satellite images I want to look at surface reflectance so that's what our earth looks like and again this is analysis ready data so it's going to be straight ready for us to work with so I want to have a look at sort of changes on the order of months so I'm going to go for the daily surface reflectance data rather than looking at the annual. I'm also going to add I'm going to look at Sentinel-2 specifically because it's got that higher resolution and sort of faster revisit time so when I click that product in the DE Africa maps interface I get this really good sort of detailed information about the product this is really worth reading if you're not familiar with these products but right at the bottom there's a piece of information I really need for the sandbox and this is this what's called the layer name so I'm going to copy that here it says s2 underscore l2a and that stands for Sentinel-2 level 2a so that's the analysis ready data so I'm going to come back to my notebook and double clicking that cell to edit it and I'm just going to make a note that says Sentinel 2 product name is this oh um you can directly add that data to the map um and there's another good feature that will let you specifically filter by location because Sentinel-2 specifically passes over different parts of Africa each day you won't always see satellite imagery in the location that you're looking at every day however if I change it to filter by location you can really see the real imagery that was captured on these days so that can be a really nice heads up of you know are you looking at the data you actually want to analyze so for me I'm pretty happy with this so now I can actually get started so now that I have this information that I'm going to need one of the best things you can do to help yourself is to go and look at the beginner's guide and look through the different notebooks we have for doing things so I'm going to open the loading data um notebook as a reference for myself just going to close this a little bit um I love Jupiter Lab because I can just stick this notebook over here as a reference and I can keep working in my own notebook so these notebooks have lots and lots of detail um and they're really great as a reference guide so one of the first things you can see is that when we're working with the open data cube you need to import the open data cube um Python package so that's going to give you access to all the API and you need to set up um an object that's actually your connection to the to the digital earth Africa data cube so I'm going to start by import data cube and you can see some of the color has come up because I'm actually working in a code cell so when I press shift enter that's all good um this one on the side here means that that's finished running and then in order to connect to the data cube I'm going to call my data cube object DC and the way that you call it is you write data cube dot data cube so that's the data cube object from the data cube library um we tend to give it an app name and that's just to help us understand um all the different people that are using the data cube but really we can call it anything so I'm going to call it my notebook and then that's enough to connect it this uh deprecation warning is coming up but it's um not something we need to be worried about so sometimes when things come up in red they might just be a warning it's always worth having a read of them okay so I'm now looking at how the load data using DC load specifically it will require at a minimum a product so this is actually our Sentinel to level 2a product um it requires the area I want to load um my sort of uh x dimension the area I want to load the y dimension um and the time span over which I want to load it and it tells you a little bit about how you need to provide the format there so what I'm going to do is before I actually construct that load I'm going to turn the data I collected into something that's a little bit more useful so something that's great that I can do in python is I can actually set up variables that mean something to me so what I'm doing here is I'm typing bottom and left so these are two variables and here I'm going to just copy the latitude and longitude values that I collected earlier so I know that that one is the bottom because it corresponds to degrees north and I know that this one is the left because it's degrees east and what that will do is when I evaluate that cell this will say bottom is equal to 30.2 and left is equal to 30.5 obviously with the extra Gaussian points so I can do this again for the top and the right equals and then again I'm going to use a bracket this is called a tuple in python um and I'm going to copy and paste my coordinates straight in there okay so I'm going to say that my data product is equal to s2 underscore l2a I'm using quotes here because I need to pass this in as a string so a word rather than a number and finally the thing I hadn't decided is that I need to pick a start and an end date so I'm going to call a new variable start date it's equal to I'm going to look at 2020 and January and January first again you pass this in as a string and you can see that that information is available in the loading data book. I'm just going to load two months worth of data just because I don't want us to be here too long and Sentinel 2 is data every three to five days so two months should give me a reasonable amount of data to look at. So when I press shift enter these variables are all assigned if I type one of them and hit shift enter you can see that python will print out for me the value that's actually assigned to that so that's a good way to check if things are working the way you expect I'm just going to cut that settle because I don't need it anymore. Fantastic now we can start learning how to load data so this is an example for the geomedium Sentinel 2 product I'm going to use that as a basis and I'm going to add a couple of other things that have to do with loading Sentinel 2 so I'll need to assign my loaded data to a variable so I'm going to call that ds that stands for data set you could really call this anything you could say Sentinel 2 you could say you know March data set or anything you want to call it is fine we tend to use ds and ds with underscores to kind of indicate that they're a data set so here I'm using this dc object that we did earlier that's my data cube and I'm asking it to load so from here I'm going to start inputting the information I need so there's an argument called product and I'm going to say that that's equal to my variable data product which is the Sentinel level 2a then I'm going to say that my x is equal to left comma right and my y is equal to it doesn't really matter I don't think whether you go top or bottom or bottom or top but I'm going to go top and bottom and then finally I'm going to also put in time equals start date and date you could also copy you know these numbers and these strings straight into here like they are in in this example I like using variables because you could come and edit this later if you wanted to change them another thing you'll see here is you need to specify which measurements you want these are the sort of satellite imagery bands so measurements equals and for that we provide python lists so that's with the square brackets so we use blue green right I'm also going to load near input red so that's nir finally there's a little extra bit that's required um if I actually try and run this it will give me an error and that's because this product doesn't actually have a default coordinate reference system so it's telling me I have to specify the output CRS and the resolution as a part of my query so I'm going to come back up to my query and just add another line so here's the output CRS I'm going to use EPSG 6933 for Sentinel 2 that's going to give me something back in meters and then it also said I needed to specify the resolution so in this case what I'm going to write is negative 10 comma 10 and what's that saying is that each pixel is 10 meters and it's just providing the information that the y pixels go down in space rather than from left to right and they go top to bottom instead of bottom to top which is something it needs so there is some more information about that in this document if you want to look at it so see how this has a little asterisk that means it's loading which is good it does take a few seconds just double checking I didn't accidentally load a huge amount of data but it's done which is great so when I showed you before that you can just type in a variable and see what it looks like we can do the same thing with our loaded data set and what we actually get is something for the x array data set so what this tells you is that the data I've loaded actually has three dimensions I've got 24 times steps 656 x pixels and 414 y pixels and it tells me that my so I could just look at one of those directly if I type the s dot red and again that's showing me the actual surface reflectance values that are sitting in there so that's the introduction so far I would highly recommend that you also have a look at the plotting notebooks and the basic analysis notebooks if you are working through the pdf we supplied to you in the breakout rooms so I'm going to stop sharing for the moment and now it is your turn so what's going to happen now is for the next half an hour you're going to be assigned for a breakout room either with me or Andrew Hicks or Ife Chong or Alex Leif and we'll be there to answer your questions if you get stuck working through the tutorial so the link to the tutorial I'm going to post it in the chat here but each of your facilitators can post it to you again if you don't have it so yeah so please feel free to just open the pdf and start working through it your facilitators are there if you have questions or you want to know how to do something different and after half an hour we'll all come back in here just to wrap up I hope you enjoy the workshop and get to learn some things about loading and manipulating data so Roshni if you can open the breakout rooms that'd be great you might see your screen disappear as Roshni does this but it will come back in a moment when you're loaded into the breakout room so have a great time thanks
 Thank you so much for joining. We might give it a few minutes just to make sure everybody's  online but I'm really happy to see all of you so far. I hope you were either able to  attend the session already or that you're planning to attend some upcoming sessions  if they're in a better time zone for you. I certainly know it's a bit earlier in the  day on the other side of the world from Australia where I am. So I appreciate you all coming  along. So yeah, I'll give it another like minute or two but then we'll get started.  If you're keen to chat or feel like you want to introduce yourself feel free to put in the chat  who you are and where you're joining us from. I'd love to see the different diversity and  global representation that we've got going on. Thanks Alex for starting off the chat.  Thank you.  That's wonderful. We've got people from all over the world. I'm so excited.  It's my absolute pleasure to be running this session with you and my hope is that at the end  of the session you'll be a little bit more familiar with doing some programming with an open data  cube implementation specifically for Digital Earth Africa. So we seem to be doing pretty well  for people in which case I might get started. So I'm going to share my screen and just present a  few slides to sort of introduce you to the workshop and a little bit of background.  So thank you so much for coming along. It's really great that you're here, that you're  participating in the conference and that you've taken this opportunity to get to learn a little  bit more about how we can, you know, how you could use the open data cube to analyze satellite imagery.  We're going to specifically be working with one of our open sandbox platforms. I did send  around an email earlier if you had pre-registered for this session with some instructions for  signing up but if you haven't yet don't worry at all we'll cover that as part of the 30 minute  session that you have for working in a small group. So for this particular tutorial I'm just  going to give you a little bit of background. I'm going to do a live demonstration of how to load.  We're going to have 30 minutes to work through a tutorial again which I sent around earlier  but again I will share with you when we get there.  So if you're new to the open data cube I wanted to start by talking about the fact that it's a  piece of open source software that's there to help you catalog and query specifically raster data.  So images that come out of satellites it's really great for that.  And what it really is doing is that it's providing a method for you to say here's where my data is  located and here's how it's sort of sorted in time and here's where it is on my file system.  And then what that means is that you can query that database to just pull out the pixels and the  imagery that you actually need and want to analyze and that's what the open data cube enables you to do.  So this is sort of well explained by these components so we have the open data cube as a whole  but it's sort of split into you know where the data is sitting and those are the actual you know  let's say geotiff files. Then there's the infrastructure which is what's interfacing  between the data and also the applications which is how you're going to access the data.  So when we set up open data cubes we have to build this index database that says here's where  all my data lives either it lives in the cloud on s3 or it might live on your native file system.  And once you've done that indexing you can then use these sort of various apps like Jupiter  notebooks or web services to go and access the data that you need. But the indexing is pretty hard  and so what we're going to do today is we're going to use an implementation of the open data cube  that already has that index set up specifically over all of Africa. And for this implementation  we're going to use Jupiter notebooks so this is an environment where you can write Python code  section by section and see your results as you go. So I'm going to show you a little bit of what  that looks like. Like I said doing the index is the hard part of the open data cube and the reason  these sandboxes are great we not only have one for Digital Earth Africa but one for Digital Earth  Australia as well is that the data is already there and you can just work straight with the open  data cube like an API to work with the data. The other thing that's great about the sandboxes that  you might notice in the picture is they actually come with a whole bunch of reference notebooks  such as the beginner's guide that you can use to learn about how to actually achieve certain things  in the open data cube such as loading data or plotting it. So the goals for this workshop  you're going to find an area that looks interesting to you somewhere in Africa.  Load a little bit of data for it we won't load too much just because you only have a little bit  of time and sometimes the loading can take a while and then see if you can visualize it using the  sort of standard RGB red green blue imagery plot. If you are feeling ambitious there's a  scratch goal where you can take this data and calculate a satellite imagery band index so  this might be something like the normalised difference vegetation index which might tell  you about the health of different fields, yeah the different crops in these fields.  So I'm going to jump in now to doing a live demonstration. So here's the digital Africa  sandbox I've already logged in. You can see here's these existing folders that are really useful  and this is how we create a new notebook. So I'm going to rename my notebook and call it ODC  workshop. So the great thing is is that this sandbox is your space when you leave and log back in  anything you put in here is unique to you. You have a copy of all these standard notebooks but you  can copy them and edit them as you desire and just make your own notebooks. So now that we've got this  I'm actually going to need to pick an area that we want to start with. So one of the easiest ways  to do this is the digital earth Africa maps interface and the reason I really like this is  that you get a really clear visual of the whole continent and you can sort of easily  look about where look where data is available and get the information that you're going to need  in order to load it in your data cube. So one of the nice features I think is that you can  directly search. So this is pullback carer. I've zoomed in a little bit at the moment this is just a  sort of background imagery setting but once that loads in I'm going to be able to use this as a  sort of guide to find something interesting that I want to look at. So here I'm going to look at  these irrigated fields. Okay so the thing I can do now that's really helpful is that by clicking  somewhere on the map I can actually get some latitude and longitude coordinates and these are  what I'm going to have to use to load my data. So what I'm actually going to do is I'm going to  copy those and in my notebook I'm going to change this this is called a cell I'm going to change  it to mark down and this means I'll plain text here that I can get back to later. If I press  shift enter that actually just renders this plain text so this is really good for keeping  notes of things I'm going to need. So I'm actually going to make a note that when I did that click  I was sort of in the bottom left corner of where I want to look so I'm going to say  bottom left are these coordinates. Perfect so I can get rid of that and now I can click up here  so that's going to be the top right again I'm just going to copy those coordinates and pop them  into here so that is the top right. Awesome and I do want to mention that I as part of that PDF  that you'll work through for most of the session I have instructions for you to follow for all of  these steps so there's no need to follow along live with me as I do this feel free to just pay  attention and understand the different components that are involved in actually going and loading  loading data. So now that I know whereabouts I want to load some data I'm just going to put a  break in there so I can see them a bit more clearly. I can come back to my map and start exploring  what data digital earth Africa has available so there's a big explore map data button here  and everything's nicely cataloged so I'm going to look in satellite images I want to look at  surface reflectance so that's what our earth looks like and again this is analysis ready data so  it's going to be straight ready for us to work with so I want to have a look at sort of changes  on the order of months so I'm going to go for the daily surface reflectance data rather than  looking at the annual. I'm also going to add I'm going to look at Sentinel-2 specifically because  it's got that higher resolution and sort of faster revisit time so when I click that product in the  DE Africa maps interface I get this really good sort of detailed information about the product  this is really worth reading if you're not familiar with these products but right at the  bottom there's a piece of information I really need for the sandbox and this is this what's called  the layer name so I'm going to copy that here it says s2 underscore l2a and that stands for  Sentinel-2 level 2a so that's the analysis ready data so I'm going to come back to my notebook  and double clicking that cell to edit it and I'm just going to make a note that says Sentinel  2 product name is this oh um you can directly add that data to the map  um and there's another good feature that will let you specifically filter by location because  Sentinel-2 specifically passes over different parts of Africa each day you won't always see  satellite imagery in the location that you're looking at every day however if I change it to  filter by location you can really see the real imagery that was captured on these days  so that can be a really nice heads up of you know are you looking at the data you actually  want to analyze so for me I'm pretty happy with this so now I can actually get started  so now that I have this information that I'm going to need one of the best things  you can do to help yourself is to go and look at the beginner's guide and look through the  different notebooks we have for doing things so I'm going to open the loading data um  notebook as a reference for myself just going to close this a little bit um I love Jupiter Lab  because I can just stick this notebook over here as a reference and I can keep working in  my own notebook so these notebooks have lots and lots of detail um and they're really great as a  reference guide so one of the first things you can see is that when we're working with the open  data cube you need to import the open data cube um Python package so that's going to give you  access to all the API and you need to set up um an object that's actually your connection to the  to the digital earth Africa data cube so I'm going to start by import data cube and you can see some  of the color has come up because I'm actually working in a code cell so when I press shift enter  that's all good um this one on the side here means that that's finished running  and then in order to connect to the data cube I'm going to call my data cube object DC  and the way that you call it is you write data cube dot data cube so that's the data cube  object from the data cube library um we tend to give it an app name and that's just to help us  understand um all the different people that are using the data cube but really we can call it  anything so I'm going to call it my notebook and then that's enough to connect it this uh  deprecation warning is coming up but it's um not something we need to be worried about so  sometimes when things come up in red they might just be a warning it's always worth having a read  of them okay so I'm now looking at how the load data using DC load specifically it will require  at a minimum a product so this is actually our Sentinel to level 2a product um it requires  the area I want to load um my sort of uh x dimension the area I want to load the y dimension  um and the time span over which I want to load it and it tells you a little bit about how you  need to provide the format there so what I'm going to do is before I actually construct that load  I'm going to turn the data I collected into something that's a little bit more useful  so something that's great that I can do in python is I can actually set up variables  that mean something to me so what I'm doing here is I'm typing bottom and left so these are two  variables and here I'm going to just copy the latitude and longitude values that I collected  earlier so I know that that one is the bottom because it corresponds to degrees north and I  know that this one is the left because it's degrees east and what that will do is when I  evaluate that cell this will say bottom is equal to 30.2 and left is equal to 30.5 obviously with  the extra Gaussian points so I can do this again for the top and the right equals and then again  I'm going to use a bracket this is called a tuple in python um and I'm going to copy and paste my  coordinates straight in there okay so I'm going to say that my data product is equal to s2 underscore  l2a I'm using quotes here because I need to pass this in as a string so a word rather than a number  and finally the thing I hadn't decided is that I need to pick a start and an end date so I'm going  to call a new variable start date it's equal to I'm going to look at 2020 and January and January  first again you pass this in as a string and you can see that that information is available in the  loading data book. I'm just going to load two months worth of data just because I don't want  us to be here too long and Sentinel 2 is data every three to five days so two months should give me  a reasonable amount of data to look at. So when I press shift enter these variables are all assigned  if I type one of them and hit shift enter you can see that python will print out for me the value  that's actually assigned to that so that's a good way to check if things are working the way you  expect I'm just going to cut that settle because I don't need it anymore. Fantastic now we can start  learning how to load data so this is an example for the geomedium Sentinel 2 product  I'm going to use that as a basis and I'm going to add a couple of other things  that have to do with loading Sentinel 2 so I'll need to assign my loaded data to a variable so I'm  going to call that ds that stands for data set you could really call this anything you could say  Sentinel 2 you could say you know March data set or anything you want to call it is fine we tend to  use ds and ds with underscores to kind of indicate that they're a data set so here I'm using this  dc object that we did earlier that's my data cube and I'm asking it to load so from here I'm going  to start inputting the information I need so there's an argument called product and I'm going to say  that that's equal to my variable data product which is the Sentinel level 2a then I'm going to say  that my x is equal to left comma right and my y is equal to it doesn't really matter I don't think  whether you go top or bottom or bottom or top but I'm going to go top and bottom  and then finally I'm going to also put in time equals start date and date you could also copy  you know these numbers and these strings straight into here like they are in in this example I like  using variables because you could come and edit this later if you wanted to change them  another thing you'll see here is you need to specify which measurements you want these are the  sort of satellite imagery bands so measurements equals and for that we provide python lists so  that's with the square brackets so we use blue green right I'm also going to load near input  red so that's nir finally there's a little extra bit that's required um if I actually try and run this  it will give me an error and that's because this product doesn't actually have a default  coordinate reference system so it's telling me I have to specify the output CRS and the  resolution as a part of my query so I'm going to come back up to my query and just add another line  so here's the output CRS I'm going to use EPSG 6933 for Sentinel 2 that's going to give me something  back in meters and then it also said I needed to specify the resolution so in this case what I'm  going to write is negative 10 comma 10 and what's that saying is that each pixel is 10 meters and  it's just providing the information that the y pixels go down in space rather than from left to  right and they go top to bottom instead of bottom to top which is something it needs so there is  some more information about that in this document if you want to look at it so see how this has a  little asterisk that means it's loading which is good it does take a few seconds  just double checking I didn't accidentally load a huge amount of data but it's done which is great  so when I showed you before that you can just type in a variable and see what it looks like  we can do the same thing with our loaded data set and what we actually get is something for the x  array data set so what this tells you is that the data I've loaded actually has three dimensions  I've got 24 times steps 656 x pixels and 414 y pixels and it tells me that my  so I could just look at one of those directly if I type the s dot red  and again that's showing me the actual surface reflectance values that are sitting in there  so that's the introduction so far I would highly recommend that you  also have a look at the plotting notebooks and the basic analysis notebooks if you are working through  the pdf we supplied to you in the breakout rooms so I'm going to stop sharing for the moment  and now it is your turn so what's going to happen now is for the next half an hour  you're going to be assigned for a breakout room either with me or Andrew Hicks or Ife Chong or  Alex Leif and we'll be there to answer your questions if you get stuck working through the  tutorial so the link to the tutorial I'm going to post it in the chat here but each of your  facilitators can post it to you again if you don't have it so yeah so please feel free to  just open the pdf and start working through it your facilitators are there if you have questions  or you want to know how to do something different and after half an hour we'll all come back in  here just to wrap up I hope you enjoy the workshop and get to learn some things about  loading and manipulating data so Roshni if you can open the breakout rooms that'd be great  you might see your screen disappear as Roshni does this but it will come back in a moment  when you're loaded into the breakout room so have a great time thanks
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