PE&RS February 2016 - page 82

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February 2016
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
25km radius from the Chile-Ar-
gentina Copahue Region. Other
alerts were observed in October
and December 2014. The data
included in the IDE-SNIT cat-
alog came from a local seismic
network managed by Serna-
Geomin. On March 20, 2014,
SernaGeomin raised the alert
level of the volcano after observ-
ing an increase in the level of
the seismic activity.
Most of the image data came
from the EO-1 ALI multispec-
tral sensor, usually used to val-
idate Landsat 8 imagery and
the Hyperion hyperspectral
instrument through a pilot web
sensor enablement interface.
Both sensors collected data for
Copahue at a 30m spatial res-
olution (Table 2) under a sat-
ellite tasking service managed
by NASA (2015) Goddard Space
Flight Center for EO-1.
On April 1, 2014, the Iquique
Region in northern Chile was
struck by a 8.2-magnitude earth-
quake. However, the 8.2 quake
does not seem to have completely
ruptured the seismogenic active
fault that ruptured completely in 1877 (Hayes et al., 2014). The
data and metadata came from CSN and from the Incorporated
Research Institution for Seismology (IRIS, 2015).
M
ethods
A simple view of the
Chilean Architecture
Implementation Pi-
lot (AIP) project de-
veloped by the Chile
Capacity Building
Working Group is
shown in Figure 5.
Chilean resources
were integrated by
IDE-SNIT.
Later,
they were registered
to the GCI and make
available to any
GEOSS user through the geoportal
Presently, any GEOSS user can search, discover, and ac-
cess the Chilean IDE-SNIT Catalog through the geoportal.
Typical web services architecture was adopted, where data
and metadata are converted through geospatial standards
and integrated into web services. When metadata services
related to different sensors are available or built, they are
indexed through the Catalog Service for the Web (CSW) by
IDE-SNIT and then registered to the GCI through the GEO
DAB brokering service. Once the connection is in place, all
metadata and catalog services are searchable and discover-
able. When the triggered criteria or policies are established,
the Chilean emergency agency, ONEMI, may broadcast alert
warnings on natural disasters to different types of users and
web clients.
Figures 5 also considers the data from multiple sensors,
such as through terrestrial stations, space, sea, and air sen-
sors, as well as data made available through the GCI by the
communities of experts, researchers, specialized NGOs, and
social networks. Any authorized GEOSS user can access and
discover the national and international GEOSS resources
during a disaster. GEOSS users can also perform other oper-
ations, such as a pre- and post-seismic analysis of the imag-
eries supplied by both SAF and NASA.
The National Catalog of the Chilean Spatial Data Infra-
structure (SDI) by IDE-SNIT is shown in Figure 6. The web
site allows for the search and discovery of geospatial products
generated by State agencies, such as digital maps published
on websites and other formats that contain geospatial informa-
tion, including studies, reports, statistical tables, and charts.
The work of the IDE-SNIT focuses on ensuring the enrichment
of the contents of the National Catalog tool in close collabo-
ration with regional, national, international stakeholders and
users. It is possible to access the National Catalog and all its
search capabilities from the Chilean SDI website. Thanks to
the OGC standard named “Catalog Service for theWeb (CSW),”
the National Catalog of Geospatial Information from Chile is
interoperable with other metadata catalogues. The IDE-SNIT
catalog is, for example, interoperable with the metadata cat-
Figure 4. Testing Areas of AIP
(Architecture Implementation
Pilot) project in Chile.
Table 2. Characteristics of sensors ALI and Hyperion on EO-1 Satellite.
The 7.7-km Hyperion swath falls on the western edge of the 37-km wide
ALI swath. ALI data were used both at level L1T and L1G, respectively
with and without geometrically corrected terrain, and where possible, the
same level of accuracy was also adopted for Hyperion data.
Bands
ALI (µm)
HYPERION (µm)
Pan
0.480-0.690
Continuous spectra 0.4-2.4
B
0.433-0.453
with 242 Bands.
B
0.450-0.515
G
0.525-0.605
R
0.633-0.690
NIR
0.775-0.805
NIR
0.845-0.890
SWIR (8)
1.2-1.3
SWIR (9)
1.55-1.75
SWIR (10)
2.08-2.35
Spatial resolution Pan: 10m; MS: 30m 30m
Swath width
37km
7.7km
Figure 5. Architecture Implementation Pilot
(AIP) Project Agencies – Chile Capacity
Building Working Group, as of 2014.
71...,72,73,74,75,76,77,78,79,80,81 83,84,85,86,87,88,89,90,91,92,...171
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