MALE SPEAKER: OK, hi, everyone.
Today, I'm going to talk about the Spatial Data Access Tool,
enable visualization and access of geospatial data
using OGC services and Google Earth.
[INAUDIBLE], I'm a postdoctoral researcher
associate from Oak Ridge National Lab.
And I'm working together with [INAUDIBLE], Bob, Bruce, and
Tammy on this work.
Before I start, let me ask a couple of questions.
Do you spend quite some time on finding the data that can
be used in your research using Google or some other tools?
If you find some data, do you want to see the data, instead
of just the reading some words about it?
If the data is actually what you need, do you want to get
the data in a form that can be used quickly and directly in
your research with only minimum processing?
The Spatial Data Access Tool I'm going to introduce today
will help you to solve those problems.
It makes it easier for you to find, visualize, and access
biogeochemical and ecological data that is useful in
environmental research.
This work is funded by ORNL DAAC and the MAST-DC projects.
Let me first give a brief introduction
to those two projects.
The ORNL DAAC, the Oak Ridge National Laboratory
Distributed Active Archive Center, is a NASA-sponsored
source for biogeochemical and ecological data and models
useful in environmental research.
It is a crucial link for the validation of biogeochemical
inferences from remotely sensed data.
The data kept in the ORNL DAAC mainly fall into three
categories, the field campaign data, land validation data,
and the related regional and global data.
There are over 800 data sets and about 220,000 data files.
And the total volume is about 1.1 terabytes.
The data files are stored in various formats, including
ASCII, binary, metacdf, and the [INAUDIBLE].
The Modeling and Synthesis Thematic Data Center, the
MAST-DC, provides data management support for the
North American Carbon Program project.
Its goal is to provide data in the formats, resolutions, and
the projections based on users' requirements.
There are many carbon cycling models
involved in the NACP project.
So the data archived in MAST-DC includes model inputs
and outputs data.
It also includes some observations data like forest
and crop inventory, tower fluxes.
There's some other related data like climate and
[INAUDIBLE] data archived.
Data centers is, especially for those handling Earth
science data, are facing challenges.
The rapidly increasing archiving rate of geospatial
data is only one issue.
A bigger one is that geospatial data is
heterogeneous in many aspects, including data format and
metadata standard.
The rapidly growing user
community is another challenge.
Users are getting more requirements on
the data they need.
And they expect more customized the data than just
the raw data.
And nowadays, different data centers are using different
mechanisms to publish and deliver data to users.
And this introduces extra burdens to users if they need
to access data from multiple centers.
So this situation is getting more critical.
With the Earth science, researchers are getting more
complex and expanding across more disciplines.
Data users need to find and visualize data efficiently.
They need to access diverse data in ready-for-use formats
and also in a standard way.
So the data centers need to take new solutions to solve
those problems and certify the data users.
The ORNL DAAC and the MAST-DC have tapped into the benefits
offered by Open Geospatial Consortium standards,
Web-enabled GIS tools, and the Virtual Globe technology to
accomplish this goal.
So what is OGC?
OGC is special name for Open Geospatial Consortium.
It is nonprofit, international, voluntary
consensus standards organization that is leading
to the development of standards for geospatial and
location-based services.
The OGC standards cover almost all aspects of geospatial
information, including the representation, management,
processing, and application.
The OGC standards we are using, the WMS and WCS, fall
into the category of geospatial information
management.
The OGC Web Coverage Service, WCS, defines a standard
interface that enables customizable access to
geospatial coverage data.
A coverage means a phenomenon that covers a geographic area,
such as satellite images and the digital
elevation model data.
The OGC Web Map Service, the WMS, defines a standard
interface that enables the visualization of geospatial
data and this including both the coverage and features.
This standardization of the data visualization and access
promotes the geospatial information interoperability,
which benefits both the data centers and the data users.
Based on MapServer, we developed and deployed the OGC
WCS and WMS servers.
The ORNL WCS server is compatible with OGC WCS
standard version 1.0.0.
It provides the features for customized geospatial coverage
data access, like spatial, temporal, [? fan ?]
subsetting, reprojection, resampling, and reformatting.
Popular data formats are supported, including GeoTIF,
ARC/Infor, ASCII [INAUDIBLE], netCDF, and
ITF and IRDIS Imagine.
The ORNL WMS server is compatible with OGC WMS
standard version 1.1.1 besides those features
provided in WCS server.
It also supports both automatic and the manual color
scheme definition.
It can render images in PNG, JPEG, and GIF formats.
The ORNL WCS and WMS servers are mainly machine oriented.
In order to bring the benefits of those servers to the end
users, we developed the Spatial Data Access Tool.
And the URL is listed here.
The SDAT tool is a Web application that enable users
to find, visualize, and access geospatial data in user
specified temporal, spatial, expanded resolution, format,
and projection.
It provides a WMS-driven interactive map widget for
data visualization and WCS-based options for
customizable data access.
Within Spatial Data Access Tool, geospatial data is
organized in two levels, the data set level and the data
file level.
As of today, there are 65 data sets available through the
ORNL OGC servers and the Spatial Data Access Tool.
Those data sets fall into a couple of major categories,
including land cover, elevation, soil,
climate, and ecoregion.
The main page of the Spatial Data Access Tool, as shown on
the left image, provides a list of all the available data
sets, their preview images, a keyword search box, and the
links to metadata pages and KMZ files, which I will talk
about later.
Following the links provided from the main page, users can
get to another page listing all the files contained in the
specific data set along with some brief file level metadata
information.
The file-level interface provides rich file-level
metadata information on the top of the page, for example,
the projection definition in OGC, a well-known text format.
In the middle of this page is an OpenLayers-based
interactive map widget.
Within this map widget, users can pan, zoom in, or zoom out
on the map.
It also supports on the fly map reprojection.
If a user select a different projection from the list, the
map will be displayed in that particular projection as shown
on this image.
On the bottom of the page are those WCS-based options for
customizable coverage data sets.
The Spatial Data Access Tool is Web-based.
It brings data visualization and access functions from
local computers to the worldwide web.
The emerging virtual globe technology, like Google Earth,
uses a virtual WART on top of the worldwide web.
We can call that the web-wide WART.
It brings users a new and a higher level platform and many
more benefits for geospatial data
visualization and the delivery.
We sensed this great opportunity and used the ASCII
WMS to KML converter to prepare a KMZ file for each
data set for users to visualize the
data in Google Earth.
Following the visualize in Google Earth links, users can
access to those KMZ files from the Spatial Data Access Tool
all the maps and corresponding legend images displayed in
Google Earth's dynamically created at
the ORNL WMS server.
A new map will be reshaped and displayed in Google Earth
every time the user touches the globe.
In the next couple of slides, I will introduce those
benefits that users can get from using Google Earth.
Google Earth provides rich and valuable background maps, such
as high resolution satellite images, roads,
landmarks, and borders.
The value of scientific data increases the more you can
link it to information that the user is already familiar
with and can see their importance.
So we should take this opportunity to present our
geospatial data in a way that users can easily tie to other
data sources.
For example, on this screen, we overlay the national land
coverage data, which is available through the Spatial
Data Access Tool, with those rich information provide
within Google Earth around the Bay area.
The red color represents the developed urban area.
And the brown color, which is near the top right corner of
this image, represents the crop lands.
So in this manner, users can easily have a sense of those
different land types that run on the Bay area.
Google Earth also provides powerful address and
keywords-based locating capability.
Say what if the user want to see a data near Yosemite?
It is easy to locate the Yosemite National Park within
Google Earth.
And Google Earth provides excellent data visualization
capability.
It is globe-based and simulates the real Earth.
Users can visualize the data from arbitrary angle of view.
It can even virtually fly within Google Earth.
It supports three-dimensional objects and a
terrain surface elevation.
And this image shows how the Google Earth overlays the
national land cover data onto the terrain base in the
Yosemite National Park.
Within Google Earth, users can overlay any map from any data
set for inter-comparison.
Let's compare the land cover patterns in the Three Gorges
Dam area in China between 2001 and 2007.
The Three Gorges Dam, as marked by the red balloon on
this image, is the world's largest hydroelectric dam.
The first map shows the land cover map for 2001.
And the second image shows the land cover map for 2007.
By comparing those two images, we can see the increase of
water area and the reduce of crop lands.
And the [INAUDIBLE] savannas were
replaced by mixed forests.
From those changes, we can think that the Three Gorges
Dam does have impact on the environment.
And there was residency relocation activity.
One may not be able to do accurate analysis within
Google Earth.
But a good visualization tool like Google Earth is critical
for the generating of scientific hypothesis and
questions that one can go on to test.
It is part of getting an intuitive
grasp of the problem.
It is super convenient to run time-series animation within
Google Earth.
And this video shows the monthly one degree resolution
CO2 flux from 1998 to 2006 displayed within Google Earth.
And this data was simulated by the simple biosphere model
version three.
Negative values, as denoted by the blue colors, represent
carbon uptake into the ecosystem.
And the positive values, as denoted by the red colors,
represent the carbon released from the ecosystem.
You can see the blue color region moves to the north
during summer and moves to the south during winter, which is
a reflection of the seasonal cycle of the CO2 flux.
Since version 5, the information window of Google
Earth supports JavaScript and iFrame.
This means we can put rich and well-formatted descriptive
information about the data layer into Google Earth.
We can even embed the Spatial Data Access Tool inside Google
Earth so that users can visualize the data in Google
Earth and access the data through the Spatial Data
Access Tool without leaving Google Earth.
And this video shows how users can launch and use the Spatial
Data Access Tool from within Google Earth.
From the information window, users can see the rich,
file-level metadata information.
You can preview the map of the data and use some tools to
select an area and zoom into that particular area.
You can use some other tools to select a region for spatial
subsetting and then go ahead to change the spatial
resolution or manually set the region for spatial subsetting.
You can do something else, like select a particular data
format from a list of all available data formats and
then go ahead to access this customized data.
This integration of Spatial Data Access Tool and Google
Earth provides users more convenience for the data
visualization and access.
And here comes the summary and future work.
The ORNL DAAC and MAST-DC are rich sources for
biogeochemical and ecological data useful in
environmental research.
The ORNL OGC servers and the Spatial Data Access Tool
provide efficient and customizable visualization and
access to geospatial data in a standard way.
Google Earth serves as a new platform and brings many more
benefits for geospatial data visualization and delivery.
I hope the ORNL OGC servers, especially with access to
Google Earth, provides positive answers to those
questions I raised before this presentation.
In the future, we are going to incorporate more OGC
standards, such as the Web Feature Service, WFS, which
enables the customizable access to
geospatial feature data.
Thank you.
Any questions?
[APPLAUSE]