Transcript

00:01So, this next session is going to be about imagery…

00:03…what's happening as we move forward, and hopefully many of you saw the plenary.

00:07Lots of exciting things going on.

00:09You probably got a little bit of a glimpse of some of the things that are actually happening at 10.1.

00:14Before talking specifically about 10.1, I just want to quickly talk about some of the imagery-related things…

00:20…that are coming up between now and when 10.1 gets released.

00:25These have been mentioned before. One of them is the extending off the World Imagery Services that we have.

00:31This is like this sort of background imagery of the world.

00:35As you heard, we're adding about 50 million square kilometers of GeoEye data to that.

00:40We recently released the Landsat services.

00:42These are dynamic image services which have Landsat data going back 40 years.

00:49You know, they're not just a static backdrop; they are the actual…

00:52…what's sitting on the server is the actual original Landsat scenes…

00:55…and you can dynamically interact with those and do things like feature extraction…

01:00…and look at the different band combinations.

01:02Soon we're going to be releasing the world elevation services.

01:05And these are really a collection of publicly available elevation data that is available for…

01:12…that is available and what we're doing is putting those up in services…

01:17…that can be accessed through any web or desktop application…

01:21…and those applications can render the elevation data in different ways, but also directly do analysis on it.

01:28So it's an important way of extending the use of, of imagery, going well beyond imagery to different types of elevation datasets.

01:38So, what's actually happening in 10.1 in ArcGIS? The first thing is really making things easier to use.

01:45Many of you who might be using, for example, GeoEye or Digital Globe imagery…

01:51…probably in ArcGIS Desktop of…or have within Catalog…browsed to a folder of GeoEye imagery…

01:57…and come up with a sort of a list that you probably see in the bottom right-hand side.

02:02It's a list of different shapefiles and TIFF files and NITF files and, yeah, you could use it in 10.0…

02:09…but you have to know which files to combine in different ways.

02:13In 10.1, you'll see a new item appearing essentially with the metadata.

02:18It'll actually be a folder, and if you actually open it up, you will see a list of actual products.

02:23So these are products that we can create from the raw data.

02:27So simply, you can see a list of…let's say I want to have a multispectral image…

02:32…or I want a pan-sharpened image or a panchromatic image.

02:34All you can do is just basically pick that up and drag it and drop it into ArcMap…

02:39…and it'll automatically set up all the different functions…the author rectification pan-sharpening, pan, band extraction.

02:45All that will actually be set up for you. It makes it much easier to work with these…these datasets.

02:52So, what we're also doing as part of that is extracting much more meta information from the satellite imagery.

03:00For example, the actual frequencies of the different bands, and no longer is it just a list of band 1, band 2, band 3…

03:06…but we actually know which is the red, green, and blue band, and we have meta information about the frequencies used.

03:13Also we're standardizing meta information such as sun angle and cloud…

03:18…which unfortunately has not been standardized in the industry…

03:20…so we're making it easier to combine different data sources and work with different data sources.

03:27Another important one is the image enhancement.

03:29Many of you probably have opened imagery and you get something looking like that.

03:35It's probably the wrong band combination. It looks not particularly pleasing.

03:40What we're doing is using the meta information that we know and also some techniques that we're analyzing the imagery…

03:45…and essentially automatically…maybe that screen shows better than that screen…

03:50…but automatically determining the optimized enhancement parameters…

03:54…the lookup tables that need to be applied to the imagery…

03:57…and therefore getting much clearer, crisper imagery, and without actually losing information…

04:01…for example, in the shadows and highlights.

04:03So that's optimized color correction and we've also added, for example…

04:10…interactive stretch tools so you can very easily work with the actual lookup tables and histograms…

04:17…manipulate different components off it and directly see the output. Easier to you than it was before.

04:24Also, we're working in collections of images.

04:27Those of you who are using mosaic datasets with collections of images…

04:31…you probably have already started hopefully using the color correction tools that already exist.

04:36There're a number of improvements that we've been made to that with more experience at doing this in larger projects…

04:42…and we've identified certain tweaks to that and that's making it easier to correct these very large collections.

04:48You see on the left, the typical multitude of different colors and then after running the routines…

04:54…which essentially store in memory, or rather within the mosaic dataset…

04:59…correction masks to be applied to the imagery, so the actual processing is actually done on the fly.

05:06So as you pan and zoom around, the original pixels are processed…

05:09…and as part of that process, the data is color corrected and you get a much more pleasing, pleasing actual output.

05:18Here's another sample. This is a collection of imagery.

05:21Again, it actually has been color corrected.

05:24You'll see that though that you still see the seam lines…

05:27…or rather the edges of the footprints of the individual seams and those are just straight-line edges.

05:33You can see probably a couple of them on, on the sides here.

05:37To remove…to remove that, what we've done is include an automatic seam line detection…

05:43…so these are algorithms that actually look at the overlapping imagery and determine the optimum location…

05:48…at which a seam line should actually be generated…

05:51…generate those seam lines, and they'll store those as part of the mosaic datasets.

05:55That was there before, now the actual…you…having the mosaic data…seam lines there…

06:00…but the automatic generation was actually missing in version 10…

06:04…so we've added that back so you can…so it'll automatically determine those seam lines.

06:08And this is the same mosaic dataset, but using the seam-line mosaic method and you see…you get a continuous image.

06:16Typically what you want to do, if you, for example, want to cache imagery, is it basically removes the seams.

06:24Next thing is really getting more information out of imagery.

06:28I've mentioned that we're reading much more meta information about the seams…

06:31…that we are actually reading in and we can do more with that.

06:34And one of those is a strange word, mensuration.

06:38For those in the military, it means a lot; for most of the other people, it doesn't mean much.

06:42But, simply translated, it's really the measurement of height information primarily out of imagery.

06:49So we've added these tools and as long as the imagery has sufficient metadata, that could be, for example…

06:55…a sensor model, you know, for example, a QuickBird or IKONOS image…

06:58…which has got a sensor model associated with it…

07:01…or it has information, for example, the time of day and the sun angle.

07:05Now we can use that to provide ability to measure height. And there are various tools to do that.

07:11They appear in the Image Analysis window and you can, for example…

07:15…pick between the base and the top of a building and it'll automatically compute the height of that building.

07:21It'll also actually give you estimates of the accuracy at which that…of that measurement.

07:25And there are other ways of doing it, for example, base to shadow, or the top of the building to the top of the shadow.

07:32Those are all different ways of computing height information…

07:37…which can be used, for example, to take a footprint of an image…

07:41…a building, and then add an attribute to it to create a block model, things like that.

07:46These mensuration tools are also available through the REST interface.

07:49That means that even through an iPhone application or those, you know, sort of applications or a web application…

07:57…you can actually measure heights in images now. And there are actually two versions of this.

08:03There is an unclassified version, the one which is basically part of the core product…

08:07…but then there's also, for the defense customers, there is a classified version, which is based on the MSP.

08:13For those that have access to that, they can use that to actually do…to have the certified measurements as well.

08:21This works on various types of images. Here for example, I'm working on a GeoEye imagery.

08:26Quite a lot of the satellite imagery does actually…

08:28…is actually taken a bit of an angle and you can use that alternative that you can use.

08:34For example, oblique imagery. This is imagery from pictometry and the same measurements can be made.

08:40Any imagery where you're actually seeing the size of the buildings or the shadows of the buildings…

08:45…and if the meta information is there, we can actually use these tools.

08:49Next is data sources.

08:51We already support over 60 formats, but what we're doing is carrying on to extend that…

08:57…and there are, at 10.1, there are 16 additional formats being added.

09:01These include things like the MrSID Generation 4 that's been released recently, DOQ 2, TerraSAR-X.

09:08So formats that we didn't support previously have been added.

09:12We're also improving the raster types.

09:13A raster type is really something like a collection of a format and meta information…

09:18…and how we handle that, and that can include reading the sensor model.

09:23So for example, SPOT-5 was a model that we could read before, but it wasn't accurately georeferenced.

09:28We're actually using…we have to have that sensor model built in.

09:32We have better support for things like Landsat, and again…

09:37…more for the defense customers, those that use the CSM as a transform.

09:41That can actually be used within the system as well.

09:43So that provides the ability to georeference a lot of classified imagery.

09:48Next is full-motion video integration. A very growing…number of users are starting to connect or get full-motion video.

09:58Some of it can be from, say, drones, and things like that.

10:02Some of it is just information from the side of a road or coming from a bridge, and that can now be integrated into the system.

10:09So either the live or archived feeds can be added and individualized with the georeferenced locations.

10:18Categorical data.

10:20Another thing that we've…Esri has done for many, many years…

10:23…but wasn't actually available in the mosaic datasets, has been added to the mosaic datasets.

10:29That means that if you have data which is the result of some form of a classification…

10:34…and you have associated with that some form of a database that defines what each pixel means…

10:39…now we can actually associate the two together…

10:41…and when you serve that, you will actually get not only an RGB rendering of the classification values…

10:47…but Identify and stuff will go back to the database and actually query and return actual values.

10:53So that extends the capabilities of mosaic datasets and image services into more categorical data…

10:58…which was not well supported before.

11:01Clayton already talked a bit about lidar. Just ready to reiterate some of those aspects.

11:06We see lidar as a being a very, very important dataset that we need to be able to manage…

11:12…we need to be able to disseminate, visualize, and analyze. There are really two ways of doing that, in a way.

11:18One's LAS datasets. That's really a collection of last files.

11:23Now, plus links to constraints, things like the edges of break…you know, break lines, or edges of lakes.

11:29Mainly used in project-type scenarios and you can basically create a LAS dataset…

11:35…and then access that actually within the 3D analysis tools, but you can also open it, for example, now in Spatial Analyst…

11:42…and you can actually do spatial analysis on it.

11:44It appears to the system as a virtual raster where the system rasterizes the data in the background…

11:50…and what we're actually doing is some quite advanced caching that's going on, so that if you pan and zoom around…

11:56…the rasterization is not repeated multiple times, and that improves the speed substantially.

12:01So you can directly use the LAS dataset or you can actually use the LAS files within a mosaic dataset.

12:08And that gives us the ability to catalog the potentially petabytes off LAS data that actually exists within the United States.

12:16And many organization have many terabytes of this stuff.

12:19It's all in different projections and different locations and different…yeah…many different ways.

12:25So the mosaic dataset allows us to catalog that and then when you've cataloged it…

12:30…where you've created a mosaic dataset off it, you can define additional functions.

12:34The functions do things like, oh, I want to apply a hillshade…

12:36…or I want to apply aspect or I want to do different types of filtering.

12:40You can do that in raster-type functions.

12:43It also maintains all the meta information, so if a user connects to a service and identifies a particular point…

12:49…it'll tell you the source, where it came from, things like that.

12:52So that's all really extending the mosaic dataset and the mosaic datasets can then be served as image services.

12:59When they're accessed as an image service, they can be accessed either as a virtual elevation dataset.

13:05They can be accessed as a catalog, to query. And users can actually download the data.

13:10So this can actually be used in multiple ways.

13:12Typically, an organization may have LAS data covering a small…a project.

13:17It could be a small project, like a dam or a dyke, and they may have hundreds of those within their organization.

13:22Typically what they'd do is they'd create a LAS dataset to define that project and add things like constraints to each one of those.

13:30What they can then do is to take those projects and add them to a mosaic dataset.

13:34So, they could basically create one mosaic dataset, which contains all the LAS for the whole country.

13:41They could then add to that other collections. They might have huge collections in their archives of existing LAS data.

13:47Those can be added to the mosaic dataset.

13:49They may have managed terrains, they may have datasets that they've cleaned up, and out of the billions of points…

13:55…extracted the points that are most valuable, maybe hydrographically enforced those, and created a terrain out of those.

14:02Those can be added to a mosaic dataset.

14:04And then naturally, all the other elevations data, the NED, the SRTM, the GTOPO…

14:08…the rasterized datasets that exist could be added and what you end up with is this huge virtual digital elevation model…

14:17…that can then be served to a whole range of different web, desktop applications, mobile applications.

14:23Those applications can visualize, work with the data, everything is dynamic.

14:27They can change the different rules of the data. What they can also do is analysis.

14:32So those mosaic image services can be used, for example, in Spatial Analyst.

14:36So you can create a GP tool in Spatial Analyst and do, let's say, a viewshed, or water run-off model…

14:41…or whatever you want to do, and then those tools can be served as geoprocessing tools…

14:47…and again, accessed by those applications, which no longer need to actually bring over all that elevation data.

14:53They just make a query to the system; the sever performs the processing and returns the results.

14:58Additionally, for those more advanced applications that actually want those lidar and LAS points locally…

15:03…and there are third-party applications that may need that, you can basically tell…you can through REST and SOAP…

15:11…you can actually download the LAS datasets locally and use those in those applications.

15:16So, it's really a way of managing the vast quantities of vast data.

15:19Here's a typical example. Small example, this is actually LAS data covering Oregon…I don't know...

15:27…it's about two terabytes of LAS files and you see that in a mosaic dataset…

15:32…and if you zoom in, you can change between, I want first return or last return, and you get the different renderings of the data.

15:39Next is improved tools. A lot of improvements that we've done in the general tools of how to work with imagery.

15:44One of them is georeferencing. A lot of users want, especially for things like change protection…

15:50…you need to ensure that the two images are aligned accurately.

15:54It's something that we had for a long time, but the tools hadn't been updated.

15:59In version 10.1, we've done a lot of updating the georeferencing tools, improved the user interface, so the new interface…

16:06…it's the same ribbon that you had before, but additional tools have been added to make things much simpler to use.

16:13There's a new mode, like a dual-monitor mode.

16:15Makes it easier for those with large screens to be able to see the image and the target and pick between the points.

16:21Increased accuracy. So, the old georeferencing tools did the transforms in image space, I mean ground space.

16:29In other words, they just walked what was on the ground.

16:31That was great for your traditional scanned map. It wasn't really optimum for satellite imagery.

16:37So now we can actually do those transforms in image space and that means, basically…

16:40…we transform those measurements that people have on the ground back into image space…

16:46…and then do the transforms there and that provides much higher accuracy, especially in built-up…on areas with high relief.

16:55So, there's improvement in accuracy, and additional transforms.

16:58These are things like projective, and traditionally we've had things like affine…

17:01…and if you know affine, everything was parallel, remains parallel.

17:05Well, for a lot of datasets, you don't want things to remain parallel and typically…

17:10…for example, browse imagery, you need a projective transform output added as well.

17:14Here's another couple examples.

17:16It shows some of the tools, the ability to, for example, quickly identify the location of a point approximately.

17:23In other words, if you know the approximate point of the control point…

17:25…it'll drive you to that location and you can then find that, that manhole or whatever that point is.

17:31There are things like autocomplete features, and then the residuals…

17:35…or rather if you want to actually analyze how accurate the results are…

17:38…you can…say, I want to look at my residuals and ground space or image space.

17:42So, a lot more tools to, to really ensure that the imagery is, is georeferenced quickly and accurately.

17:50Additional raster functions. So, this is becoming more and more popular.

17:55The on-the-fly processing that we talk about is really a different way of processing to traditional processing.

18:01Traditional processing is a push model.

18:04You have a raster or an image and you push it through a process, and you push it through the next process…

18:08…and you push it through the next process, to get a final output.

18:11Your on-the-fly processing really goes the opposite way around.

18:14You have defined what you want as an output, and it pulls the pixels through the functions, back out.

18:21So those are really the, the…on-the-fly processes, which we've had for on, you know, author rectification and pan sharpening…

18:28…and we've extended those so now in 10.1, you can do better things like band algebra using the same principles.

18:34And we're seeing more, more developers actually extending the system and adding their own custom functions.

18:42Function Editor is really a way to enable users to work with a mosaic dataset.

18:48Very often, a mosaic dataset may have hundreds of thousands of different images in it…

18:52…but you want to basically select maybe a hundred or a thousand of those images…

18:56…and apply a particular function to it, or edit a function.

19:01We had some tools at 10.0 and 10.1.

19:03We've realized we've had to further extend those and make it much easier to, to change parameters.

19:09I want to select a whole load of data and I want to just change the elevation model.

19:12You know, how do you do that? Well, the Raster Editor functions enable that.

19:17They also have templates, and templates enable you to make a collection of these functions to find them as a template…

19:23…and then apply that multiple times within the system.

19:26It's really extending the ability for people to create extremely large and potentially very complex mosaic datasets…

19:36…which to the end user look very, very simple. So, it's very powerful capability.

19:42Improved management.

19:43What we want to do is improve the management of, of the mosaic datasets and one other way of doing that is analyzers.

19:50So those of you who've used ArcGIS Desktop and published a map, well, an analyzer pops up and tells you…

19:57…Huh, you've got the data in the wrong projection, or you know…

20:00…you're doing certain things in…gives you some suggestions of how that can be, how that can be improved.

20:06We've added two analyzers. One for mosaic datasets.

20:11Those will go through the data in the mosaic dataset and give suggestions of things that should be changed.

20:17It may be parts that are broken or formats that aren't optimized and it'll give you suggestions of how to improve that.

20:25Similarly, for the image services, you know, if you publish an image service…

20:29…it can analyze that and also come up with some potential suggestions of what might need to be changed.

20:35Automation tools to improve automation. These are mainly as additional geoprocessing tools.

20:42We realized that there were some tools missing in 10.0, for example to change parameters in the mosaic dataset.

20:48The UI is there, but the GP tool is not there.

20:52There are some workarounds, but additional geoprocessing tools have been added to change parameters.

20:58Synchronization is a capability of the system to monitor, or rather not necessarily monitor…

21:04…but to check if anything changed within the system and then update those mosaic datasets.

21:09A typical use of that is, for example, having a directory which contains data and if you just add more data to the directory…

21:17…it should automatically be added to the mosaic dataset. It simplifies automation.

21:22Those tools exist but have been substantially enhanced to provide all sorts of different workflows and synchronization workflows.

21:31Lastly, in serving, we've done a lot of work to improve how image services are served.

21:38One is to simplify the experience. If you've been to any of the other Road Ahead sessions on Server…

21:45…you'll see the new user interface being used to enable people to serve the imagery.

21:51Now that has been simplified with a number of scalability improvements.

21:54We're always looking on how to improve the scalability of the data.

21:58Image service caching. This enables you to take an image service and actually cache it so that it becomes a map…

22:05…and that map can then be displayed as a static background.

22:09Again, for scalability reasons, that is sometimes advantageous.

22:13It was available in 10.0, but it required you to actually go and create a map and then run a set of processes…

22:21…which were very generic, and now these are optimized specifically for imagery.

22:26Server-side functions.

22:28An app, even 10.0, an application can connect to a server and define a function to be applied.

22:34I want to apply a hillshade and I want to change parameters, but we only had eight functions.

22:40Now you can have as many as you want.

22:41You can define your own functions on the server and a web application can connect.

22:46Change parameters and the server will actually do the process being applied. Very, very powerful.

22:53Image service editing. Well, what happens if you have an image service and you have an image you want to add to it?

23:00In 10.1, through a web interface, you can actually add imagery to a service…

23:04…remove imagery from a service, change imagery from a service.

23:07In other words, the management capability, if you open it up, can be performed by multiple people…

23:13…working in a web environment and modifying the services running on a server.

23:17It's very powerful, especially as we move to a cloud-type environment. And then extending the REST.

23:22The REST is really…REST interface is the way that most developers connect with the image services.

23:28Those REST interfaces have been extended.

23:30The mensuration tools, yeah? Typically you may have an application, you want to measure heights.

23:35You can do that now within web applications as well.

23:38So that's it.

Copyright 2014 Esri
Auto Scroll (on)Enable or disable the automatic scrolling of the transcript text when the video is playing. You can save this option if you login

Road Ahead - Imagery

Peter Becker discusses the imagery enhancements for ArcGIS 10.1 including the ability to work with lidar data and mensuration from different sensors.

  • Recorded: Jul 14th, 2011
  • Runtime: 23:39
  • Views: 37138
  • Published: Sep 22nd, 2011
  • Night Mode (Off)Automatically dim the web site while the video is playing. A few seconds after you start watching the video and stop moving your mouse, your screen will dim. You can auto save this option if you login.
  • HTML5 Video (Off) Play videos using HTML5 Video instead of flash. A modern web browser is required to view videos using HTML5.
Download VideoDownload this video to your computer.
<Embed>Customize the colors and use the HTML code to include this video on your own website
480x270
720x405
960x540
Custom
Width:
Height:
Start From:
Player Color:

Right-click on these links to download and save this video.

Comments 

Be the first to post a comment
To post a comment, you'll need to login.
If you don't have an Esri Global Login ID, please register here.