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A possibility of land vegetation
observation with SGLI/GCOM-C
Y. Honda, Center for Environmental Remote Sensing (CEReS), Chiba University;
M. Moriyama, Nagasaki University; K. Kajiwara, CEReS;
A. Ono, Earth Observation Research Center (EORC), Japan Aerospace Exploration Agency
C
ontinuous global observation is necessary for effective
environment analysis. Satellite remote sensing is very
useful for this purpose, and can provide spatial and
temporal monitoring of the global environment. The Japan
Aerospace Exploration Agency (JAXA, formerly known as
NASDA) has developed a new plan, the Global Change
Observation Mission (GCOM), for monitoring global environ-
mental change and understanding its mechanisms, including
global warming. Data obtained from GCOM are necessary for
the monitoring of global climate change and the improvement
of climate models, and this should result in a useful contribu-
tion to social benefits.
GCOM is a follow-on satellite observation mission incorporating the
technology and results of the Global Imager (GLI) and Advanced
Microwave Scanning Radiometer (AMSER) on ADEOS-II. The
GCOM mission will consist of two series of medium-sized satellites:
GCOM-C (Climate) and GCOM-W (Water). The GCOM-C satellite
will carry the Second Generation GLI instrument (SGLI), which is
the advanced version of GLI. In addition, the GCOM-W satellite will
carry the AMSR follow-on instruments, for example a scatterometer
like SeaWinds on board ADEOS-II. Three consecutive generations
of satellite, each with a one-year overlap, will have been operated in
an observing period of more than 13 years. GCOM is designed to
establish long-term observation for monitoring global environment
changes, improving knowledge of climate systems, developing
climate forecast models and distributing environmental data.
GCOM-C and SGLI
SGLI optical sensors observe reflected solar radiation and/or infrared
radiation from the surface of the earth including land, ocean and
cloud using multiple channels for measuring biological contents
(chlorophyll, photosynthetically active radiation and vegetation
index), temperature, snow and ice cover, and cloud distribution.
These data are useful for understanding the global circulation of
carbon, estimating radiation budget, monitoring environmental
changes, and they also help develop our comprehension of primary
marine production.
SGLI has 19 spectral channels from near ultraviolet to thermal
infrared. In particular, SGLI has some unique channels, which have
been used rarely in previous years: a 380 nm channel for aerosol
detection over land, 763 nm for oxygen absorption, and 1,380 nm
for cirrus cloud detection. Eleven channels from near-UV to short-
wavelength infrared (SWIR) have a resolution of 250 m
at the nadir, and two channels in the MTIR have a reso-
lution of 500 m, covering a large portion of the Earth’s
surface with various spatial scales. Various geophysical
parameters consisting of atmospheric, oceanic, land and
cryospheric parameters are retrieved from radiance data
from SGLI. These parameters are used for tasks such as
evaluating ocean and land biomass and primary produc-
tion on a global scale; generating global fields of clouds,
water vapour and aerosol parameters; or monitoring
snow/ice properties around bipolar regions.
Simulation results of SGLI
land products from existing data
Some original SGLI land products are estimated by using
new and unique channels of the GCOM-C/SGLI sensor.
These are expected to be of great use in understanding
and improving climate change.
SGLI can observe surfaces of the earth on a slant in the
red and near-infrared (NIR) region. This function
improves the detection efficiency of vegetation biomass.
Conventional biomass estimation methods using existing
vegetation were unable to reflect the three-dimensional
structure of the vegetation canopy.
Shadow index
It is inevitable that satellite data will be influenced by
shadow. In areas of vegetation, the ratio of visible
shadow space varies widely with types of tree, plant
growth, season, and so on, because the structures and
textures of vegetation differ from each other. Thus, a
new vegetation index, the shadow index (SI) has been
developed to take into account the influence of shadow
effect. SI expresses the difference between vegetation
coverage and type, such as closed and open, or ever-
green and deciduous broadleaf. It is therefore expected
that SI will be useful for analysing vegetation in land-
cover classification, vegetation-type classification,
vegetation biomass estimation, and so on.
Water Stress Trend
Water is indispensable for animals and plants. Water
shortages have serious consequences for many forms of
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