study are represented as smooth 3D cloud objects even if we
looked at Asian dust clouds transversely in the Google Earth.
Fi
Fig.6 Asian dust cloud at 08:00 o
E
March 20, 2010 >
Image & 2017 DigitalGioba
Fig. 7 Asian dust cloud at 03:00 on March 20, 2010 when we
looked at the Google Earth in the transverse direction.
m 210
Fig.8 Asian dust cloud at 10:00 on March 20, 2010 when we
looked at the Google Earth in the transverse direction.
"BEI PEE
Fig. 9 Asian dust cloud covering the sky in the case that we are
in the dust cloud
REFERENCES
AEROS, Atmospheric Environmental Regional Observation
System, Ministry of the Environment, Japan
http://soramame.taiki.go.jp/index.html
Aria Technologies, 2007. Manual of Aria-regional software:
ARIA/2007.101, Aria Technologies, France
Kusaka, T, Y. Goto and T. Yobuko, 2003. Estimation of the
spatial distribution of Asian Dust using the long-range inverse
transport model and MODIS images, Proceedings of
ISPRS2003, CD-ROM
Kusaka, T, T. Kono, W. Okuda and Y. Nakano, 2009.
Visualization of the concentration distribution of Asian dust In
the Google Earth, Proceedings of SPIE 7840 (Sixth Intl. Symp.
On Digital Earth), 78401D
Kusaka, T, T. Kono and W. Okuda, 2011. The transport
animation of Asian dust clouds in the Google Earth, Proceeding
of IGARSS2011, CD-ROM
ORTHC
KEY WORI
ABSTRACT
HJ satellite 1
China, whick
rectification
database is
information.
imaging moc
utilized for o:
high efficienc
With the inci
disasters, the
satellite imag
In order to fo
natural disas
Constellation
Forecasting ii
which can pre
with the 30m
obtaining sat.
disaster moni
It is clear that
application of
Only based o
information c;
made more sc
environment
rectification i
few researche
fact is clear |
attitude and
Which can nc
rigorous sens
points[3].
GCP Image D
attribute info;
processing of
sufficient Gro
matching.
In this paper,
DOM image (
with HJ-1A/1
——
: Guoyuan L
and LIDAR