From global observations to local information: The Earth Observation Monitor
15 views
Formal Metadata
Title 
From global observations to local information: The Earth Observation Monitor

Title of Series  
Part Number 
62

Number of Parts 
193

Author 

Contributors 

License 
CC Attribution 3.0 Germany:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor. 
Identifiers 

Publisher 
FOSS4G, Open Source Geospatial Foundation (OSGeo)

Release Date 
2016

Language 
English

Content Metadata
Subject Area  
Abstract 
Earth Observation (EO) data are available around the globe and can be used for a range of applications. To support scientists and local stakeholders in the usage of information from space, barriers, especially in data processing, need to be reduced. To meet this need, the software framework "Earth Observation Monitor" provides access and analysis tools for global EO vegetation timeseries data based on standardcompliant geoprocessing services. Data are automatically downloaded from several data providers, processed, and timeseries analysis tools for vegetation analyses extract further information. A web portal and a mobile application have been developed to show the usage of interoperable geospatial web services and to simplify the access and analysis of global EO timeseries data. All steps from data download to analysis are automated and provided as operational geoprocessing services. Opensource software has been used to develop the services and client applications.

00:00
State observer
Trail
Trail
Information
Presentation of a group
Oval
Geometry
.NET Framework
Local ring
Units of measurement
00:35
Standard deviation
State observer
Context awareness
Mobile app
Observational study
Presentation of a group
Time series
Mathematical analysis
Client (computing)
Formal language
Mathematics
Web service
Software
Integrated development environment
Process (computing)
Conditionalaccess module
World Wide Web Consortium
Area
Focus (optics)
Electric generator
Information
Geometry
Mathematical analysis
Interface (computing)
Digital signal
Set (mathematics)
Cartesian coordinate system
Web application
Message passing
Computer animation
Personal digital assistant
Web service
Statement (computer science)
Right angle
Object (grammar)
5 (number)
Local ring
Series (mathematics)
03:52
Modul <Software>
Domain name
Greatest element
Mobile app
Statistics
Mapping
Presentation of a group
Algorithm
Multiplication sign
Mereology
Formal language
Web 2.0
Summation
Web service
Latent heat
Lecture/Conference
Process (computing)
World Wide Web Consortium
Web portal
Process (computing)
Information
Mapping
Interior (topology)
Client (computing)
Library catalog
Cartesian coordinate system
Software
Personal digital assistant
Web service
Asynchronous Transfer Mode
Library (computing)
Series (mathematics)
Wide area network
05:42
Satellite
Slide rule
Pixel
Scientific modelling
Multiplication sign
Disintegration
Source code
Time series
Point cloud
Mathematical analysis
Data analysis
Coma Berenices
Twitter
Data model
Web service
Mathematics
Feasibility study
Utility software
Subject indexing
Negative number
Process (computing)
Subtraction
Area
Link (knot theory)
Satellite
Process (computing)
Electric generator
Information
Geometry
Mathematical analysis
Electronic mailing list
Code
Point cloud
Bit
Cartesian coordinate system
Plot (narrative)
Subject indexing
Word
Kernel (computing)
Computer animation
Integrated development environment
Web service
Right angle
Data integrity
Modem
Series (mathematics)
10:03
Product (category theory)
Manufacturing execution system
Multiplication sign
Computergenerated imagery
Mathematical analysis
Amsterdam Ordnance Datum
Ext functor
Mathematical analysis
Data analysis
Euler angles
Variance
Subset
Summation
Computer animation
Web service
Computer cluster
Case modding
Queue (abstract data type)
ASCII
Series (mathematics)
World Wide Web Consortium
10:28
Point (geometry)
State observer
Manufacturing execution system
Mapping
Computergenerated imagery
Disintegration
Price index
Mathematical analysis
Complete metric space
Interface (computing)
Variance
Web 2.0
Explosion
Web service
Term (mathematics)
IntServ
Software framework
ASCII
Physical system
World Wide Web Consortium
Metropolitan area network
Process (computing)
Scaling (geometry)
Geometry
Mathematical analysis
Ext functor
Set (mathematics)
Limit (category theory)
Cartesian coordinate system
Estimator
Differential geometry
Subset
Computer animation
Web service
Case modding
Queue (abstract data type)
Series (mathematics)
12:32
Query language
Server (computing)
Open source
Multiplication sign
Mobile Web
Mathematical analysis
Icosahedron
Formal language
Web 2.0
Web service
Software
Google Maps
Process (computing)
World Wide Web Consortium
Metropolitan area network
Addition
Satellite
Process (computing)
Mapping
Software developer
Open source
Mathematical analysis
Coma Berenices
Cartesian coordinate system
Computer animation
Software
Web service
Function (mathematics)
Revision control
Software framework
Wide area network
13:10
Point (geometry)
Metropolitan area network
Electronic data processing
Computer animation
Bridging (networking)
Mathematical analysis
Decimal
Library catalog
Hand fan
Emulation
13:31
Pressure
State observer
Asynchronous Transfer Mode
Greatest element
Manufacturing execution system
INTEGRAL
Source code
Library catalog
Price index
Mathematical analysis
Data analysis
Mereology
Emulation
Workstation
Web service
Bridging (networking)
Linker (computing)
Computer network
Process (computing)
output
Subtraction
Zoom lens
File format
Geometry
Open source
Library catalog
Computer animation
Visualization (computer graphics)
Function (mathematics)
Internet service provider
Decimal
Right angle
Library (computing)
14:50
Pressure
State observer
Manufacturing execution system
Disintegration
Mathematical analysis
Function (mathematics)
Data analysis
Emulation
Web 2.0
Information retrieval
Medical imaging
Web service
Moving average
Physical law
Process (computing)
output
Addressing mode
Local ring
Subtraction
Form (programming)
Area
Metropolitan area network
Geometry
Forcing (mathematics)
Mathematical analysis
Electronic mailing list
Data analysis
Bit
Set (mathematics)
Directory service
Plot (narrative)
Inflection point
Ultimatum game
Computer animation
Function (mathematics)
Web service
Information retrieval
output
Normal (geometry)
Data conversion
16:36
Pixel
Identifiability
Network operating system
Source code
Data analysis
Client (computing)
Function (mathematics)
Information retrieval
Web service
Process (computing)
Rhombus
World Wide Web Consortium
Process (computing)
Geometry
Mathematical analysis
Coordinate system
Data analysis
Directory service
Set (mathematics)
Computer animation
4 (number)
Web service
Function (mathematics)
Uniform resource name
Information retrieval
output
Local ring
Resultant
17:36
Mobile app
Multiplication sign
Mobile Web
Computergenerated imagery
Price index
Computer
Field (computer science)
Web 2.0
Summation
Hypermedia
Forest
Integrated development environment
Software testing
Position operator
Form (programming)
Area
Metropolitan area network
Satellite
Process (computing)
Information
Geometry
Mathematical analysis
Volume (thermodynamics)
Cartesian coordinate system
Plot (narrative)
Mathematics
Computer animation
Case modding
File archiver
Resultant
Series (mathematics)
19:13
Laptop
Meta element
State observer
Server (computing)
Context awareness
Vapor barrier
Code
Multiplication sign
Mathematical analysis
Data analysis
Student's ttest
Interface (computing)
Semantics (computer science)
Field (computer science)
Metadata
Area
Summation
Mathematics
Goodness of fit
Web service
Forest
Process (computing)
Descriptive statistics
Task (computing)
Social class
World Wide Web Consortium
Electronic data processing
Geometry
Mathematical analysis
Code
Coma Berenices
Set (mathematics)
Binary file
Plateau's problem
Mathematics
Forest
Computer animation
Case modding
Task (computing)
Reduction of order
Series (mathematics)
21:25
Metropolitan area network
Raw image format
Multiplication
Geometry
Closed set
State observer
Data analysis
Bit
Summation
Latent heat
Web service
Decimal
Process (computing)
Form (programming)
World Wide Web Consortium
21:45
Network operating system
Geometry
Data analysis
Semantics (computer science)
Information retrieval
Summation
Computer animation
Web service
Function (mathematics)
Uniform resource name
String (computer science)
output
Process (computing)
Parametrische Erregung
Cuboid
Units of measurement
Form (programming)
World Wide Web Consortium
22:39
Area
Slide rule
State observer
Dialect
Process (computing)
Open source
Information
Mapping
State of matter
Multiplication sign
Moment (mathematics)
Projective plane
Water vapor
Parameter (computer programming)
Set (mathematics)
Multilateration
Chaining
Web service
Computer animation
Function (mathematics)
Infinite conjugacy class property
output
00:09
OK so no no we would go my you must have ability for speaking about the situation when you are and and and welcome to my presentation about the observation 1 or from the old observations to local information and this is the top with in the in the in the academic track so so what are the the
00:37
main challenges when working with us observation data and data and data in general so we have an increasing global data and data clients and then we need to think about how to to simplify it times data access and then and also analysis and we need to 2 decimal increasing need additional related to monitor environmental changes because the diocesan this is changing and we have the and the data to to monitor on the these changes and and if you there have been several years ago was so some some research going on for example about the next generation to the to to the house uh from exactly dominant to the 2008 and a stated to have been in the need to have easy to use interfaces and the problem problem oriented focus so this is not not neutral but but but still we we have um uh many issues to to phase when accessing timeseries data and and making some analysis so there are a lot of steps included uh for example for downloading data for certain searching for data but also to uh to to process the data sets um but but also in the new are initiatives like diffusion future putrescent messages they data we need to make research accessible for all kinds of parties and we need to develop useful tools for applying knowledge so the the awareness is this is and that it to have to always started to develop tools to make us observation data better accessible and this is also the and the content of in this paper and this probe presentation so
02:30
the object of some general to simplify the talent data access and analysis without having the user to to process any data by themselves to make suffered tools available as as web services because then we can use or to integrate the induced services in any kind of applications such as mobile application for them as a webbased tool use these mn scripting languages for example but but also to to provide easytouse applications for all of us they called us and and sciences and in general to to come to my statements from global observations to local information so we have global datasets but in general the the users interested in some local area so and in this case we have our users here we have our local area of interest and we have about our global last observation at Dayton Dayton data kind and on and on the right we have some analysis also puts on the and the information extracted from the DOS observation data because and the and the technical background behind this is of course a service based infrastructure providing web services so at that at the that we have our client
03:52
applications as a set before a web portal
03:55
of the mob mobile application or any other software tools and they are in general connected to the to the Internet and at the bottom we have our geospatial services infrastructure providing web services and and in the best case and the geospatial domain now what it is that services are all mode is the compliance so providing the time information using the catalog service providing the of his Asian services for ideas and well with the web map service providing access services for example was the web coverage services and the special status especially processing services using the OGC Web Processing Service specifications that better benyamin has also introduced in this last uh in in the last part of presentation and will that means in this step processing services we can have different those services can for example when we're using a Python and based on Web processing Service empire WPS and uh you can use any more Our anything where would you can use will impact and you can also exposed as a Web Processing Service you can also have a library named our to so as to have a connected direct connection from prior to to the statistical language R you can also use the command line tools and and have any other software package that is is available and these can be expressed as a weapon processing services so that this process is it is available to you to draw kind of users so let's
05:43
take a little bit about the processing services and and I have a list of research topics that is as this it is still on the ongoing we distribute the problem processing we have semantic processing we have process orchestration and processing in the Cloud Moving carrot and then modeling and generation and and this shouldn't just just our own only 1 1 paper referred to each of the topics but see the yes and they and they are still up to date so so there's uh as still the research going on but this is not that are what needs to be become and consider some so we need also to think about uh the society in general providing a process all but we can also use provided with processing services like um providing processing services for data access our data and discovery because we can benefit from different processing steps linked data integration and data analysis tools because at this time to to provide an analysis tools as as a webservice but at 1st did the user needs to have their and the data available so we need the it looking good to link to link these 2 steps to the data integration of our data and data access and the analysis tools can of course also the feasibility or the applicability of processing services uh need also be a little bit more investigated what kind of 2 could we provide was down WPS so services so I'm 190 problem we're working a lot with vegetation time series analysis of them this is a plot uh of of a single pixel showing that clearly had sent a negative trend from the year 2000 to the year 2 thousand and 15 and that showed the to produce the enhanced vegetation index as shown in the mutation and g and the utility and the is a clear change of so uh was in 2000 11 around so we have a clear and low value of of patient and this directly comes from the from the satellite but this is just the data what you want this this is information so there are a lot of analysis tools available to to extract information out of the in there the data and then these our plots from 2 words that have been developed were moving the research community like the start on on the top left is that's about the breakpoint the detection so analyzing the time series and looking for and fall
08:45
prey and to come and this is sort of from the same times as as so she shows him in the previous slide and there was a change detected in the environment 2010 around and change for the seasonality of 2 vegetation so these are useful information so now we we don't have the the data we have the information about the date when the change has been accused and there are also other now analysis to it's like this . com on the right we have the um this baby spatial trend analysis tools uh maybe it's not too good to discover from from the back but you have bound pixels our my pixels and the kernels bound with negative trend and pixels with the color of green will positivestrand so that you can clearly identify the the area where we have a negative then the iterations and and the positive the contagion and there are from tools but these tools are also available as individuals suffer package they open source and then then they can only be used but they are not connected to to any data set so you have to to a the the data and the data yourself and then we
10:05
can have a look what what kind of
10:07
tools are available was already available available as online time data access and data analysis tools and there are a few and this is just an excerpt uh does for example now zadnje of irony of providing now uh analysis to its annexes to do more this datasets and there's
10:29
also a based Web and Web service from those Oakridge National Laboratory in many years providing access to data sets have been there are added to it but in general they are all have so there are limiting to that are just a few it's not all day and my datasets so they they all have have limits and unfortunately there and they're not probable the most of them are not providing a standardcompliant service system does only the last 1 the the also work and then there providing Web coverage Service and the back covers processing services but and they are not having the and the complete data sets from from what the segmentation and available for example and so on so I would say that that is using this estimate compliant processing services like entity dubbed WPS as it is a very good technical solutions to integrate services associated external applications so making processing tools available to others that they can use them in their in their applications
11:40
and this is during there the mainland uh . within our concept of of the US observation monitoring and there are the main points are entering the easy access and analysis of spatial terms is they they have found that monitoring on a local scale so you cannot do any global analysis within our framework because where we're focusing on on on the local scarce and we provide web web services based on geoprocessing services so everything what what is done within the the US observation monitoring is being exposed as web services and the if this has anything to do with processing of existing data datasets integrating the there's there's Indian these are explosives geoprocessing services so we're we're
12:33
losing a lot of open source software um for the web and then the mobile did their application development uh like Jake very open
12:44
layouts Jake very mobile above but also imply the geospatial Web services we're using map server and the pi that WPS and for for the geospatial processing and there is the the our statistical language but those a Python tools for our times analysis and then the times of tool for the addition phonology and the need to
13:12
1st point of the US and
13:14
was observation money toward the 1st step within this the automated data access because of course is we wanted to make some analysis we we need the data 1st so we we have developed a data processing middleware uh and then you and so it's a
13:31
Python library that that budgets is bridges the gap between users and data providers so I'm at the bottom we have our different data providers like modus uh also from all this data about but also for climate station data from have for example and then we we have built up some some connect this to draw on the these external data sources and then integrate the data right in our a common data format and then provides the data at 1st will vote is a compliance services but also provides not only the the data for visualization but also and and some some retired from our mission was the catalog service for that and then in the 2nd step is that some of
14:21
just have all of your of foster datasets we have most mothers vegetation and a data we have some more and more this land surface temperature data available and we have some some clans station data available within the US observation 1 and 2 and those in the 2nd step is then the in the in the and data analysis and the link to the data and integration so it in the 1st part here is as stated the automated
14:50
data access so the data retrieval of on the 2 input from the user so the user only has to there has to stay the the area of interest of course and the name of the dataset he can also provide some some further problem apparently and depending on the data set like quality mom masking and so on and D and the status and I'll start in local problem told processing down directory and this is also a WPS so we have 1 WBS for the data received retrieval and another WPS for the data analysis and their and therefore we we also used in local processing them directly to directly access to data sets and make the analysis and all the steps for data preparation and running the analysis and to the the preparation of the the output size has been been ultimatum and also a little bit optimized for of force of a performance and all the outputs are then also provide pool where is he complained services so as
16:00
a said before the end the data are also provided with artistic complain services here we have a list of of different outputs for for each of the analysis tools so we have the uh uh C is the founder and that been transformed to to and the observation service we have just normal plot in images but uh we we have also all want to see that service or quarterpixel shapefile provided as uh as a web feature service that can be directly used them in the port of form for example so here I have
16:39
2 to 3 examples for uh about processing
16:43
service for the data retrieval for example and this is just and just made http we request with the data set as an input and then the day the pixel column coordinate and then the the process is being executed and you can more that the client can can't wait for the results and the 2nd was for the diamond data analysis of this is nearly the same source 1 output of the data retrieval is a unique identifier and will list unique identifier I can reference to the datasets in the analysis and is a space for for this local processing directory so that we can use this integrated data datasets diamond directly within the and the data analysis tools the so for this we
17:37
we have a web based tool that developed their work and users directly through create some some future compliance compiling on it and directly integrated in the dataset and also makes some analysis uh without any processing steps the picture that this is all done by the by the server and that the user has always the possibility to to Donald at their own all the data as it is about archive and to to process the data further offline on his own computer form for for example and we we have a mobile applications so directly in the field with the GPS position for example you can access to the WPS that the application accesses the WPS and extracted the 15 years of of time data and provide some some plots and uh analysis and results I have some some example areas where where we have a test in this uh where we can see some some now changes for example in the Bavarian Forest in unique where we have
18:53
uh and uh the growth of the volume vegetation beginning and 2004 up after the bark beetle attack some so here you you can use this in the data but also the the information from the analysis results to detect exactly the media and the date of to change and there are some further
19:15
uh possibilities for example here you can have an of uh this freelance at seeing from 1998 from 2001 and 2014 and unfortunately that there were no good lands of things between 2002 1 and 2 thousand and partying and and that was clearly change of a forest you can can cannot discover this was the land of the and but with small this data with the daily more this data set and we can clearly had a identify when the change has happened and the best I come to my conclusion
19:54
so some of notice the WPS need she it definitely to become so that establishing easytouse data access and the and and analysis tools and especially to reducing barriers uh for as observation times data because still others this and there are some some ongoing ongoing declivities class but for of for most datasets it is still very complex for use of self are kind of users uh but also for for for scientists for students and so on so it must be be easier and we we need also to link the data X is listed data analysis because you cannot do analysis of art uh accessing and then the data and we need to hide it the context data and data processing tasks that some future work we will uh doing this kind of field so providing metadata for processing services with semantic descriptions to integrate real moving code approach so that you can upload some some analysis for example by using the Jupiter notebooks to directly process data on the server and to extend their their ideas observation and talk to the sentence data and with this and like to thank you for your attention since it is with those anybody have any questions this yeah
21:29
I can many of them but 2 will slide 15 distinct and efficient multi year in the form of self close
21:36
to the Lucas because that's a bit of a flaw in this specification and you can you can have everything a single and this 1 little was it's so
21:46
small is like the 1st 1 data input on knowledge also uh it's just the enormous adjusted to be not get carried k the T because keyvalue pair but it didn't put linear what's that what's the form of of the input the data they're just the form of and unions and what I mean it's it's a string of is the string or is the area into
22:19
yeah and the and the and these are strings so so the and these are the parametres dataset named behind the online and then the and these are the the literary data inputs could and was just thinking about it doing this some semantics about these inputs or and you know book about regarded them
22:41
more living with these services and he has this is so far as a set on and on the last slide in the future work we would like to to to describe uh every input parameter will this the time information nation but this is not included at the moment but can you could also sing about profile and maybe here so 6 Phineas official where she's going from a lot of questions the what are the targeted users here is it mainly for research and all of that's in the beginning basically is a research topic and then later on was the use of you target yeah uh as you said at the beginning of from for research of course so so we have uh we have requested to to to to use these users as observation it also from from other departments around the world because they they have the same users when when existing data sets and unrelated later stage so we we plan to to make there are also with the south Serbian beauty behind is available as as open source so we're we're we're um developing this as an open per project with the possibility to um to set it up for all 4 regional problem projects so so uh I had request from 1 guy from the the water county Department in the US and they they were very interested to have regional maps from all this data from from Landsat data from with an automated post processing chain so the DEA is to to provide tools to to automate the extraction of a given area of in his interest like state for have for example and to provide 2 other automated tools services or what to expect that they can become have access to the data that is clipped to the area of interest thank you very much so you can move to another city and if you need it you have a