Hyperspectral Imager Suite (HISUI) is a Japanese future space-borne hyperspectral instrument being developed by
Ministry of Economy, Trade, and Industry (METI). HISUI will be launched in 2019 or later onboard International
Space Station (ISS) as platform. HISUI has 185 spectral band from 0.4 to 2.5 μm with 20 by 30 m spatial resolution
with swath of 20 km. Swath is limited as such, however observations in continental scale area are requested in HISUI
mission lifetime of three years.
Therefore we are developing a scheduling algorithm to generate effective observation plans. HISUI scheduling
algorithm is to generate observation plans automatically based on platform orbit, observation area maps (we say DAR;
“Data Acquisition Request” in HISUI project), their priorities, and available resources and limitation of HISUI system
such as instrument operation time per orbit and data transfer capability.
Then next we need to set adequate DAR before start of HISUI observation, because years of observations are needed to
cover continental scale wide area that is difficult to change after the mission started. To address these issues, we have
developed observation simulator. The simulator’s critical inputs are DAR and the ISS’s orbit, HISUI limitations in
observation minutes per orbit, data storage and past cloud coverage data for term of HISUI observations (3 years). Then
the outputs of simulator are coverage map of each day. Areas with cloud free image are accumulated for the term of
observation up to three years. We have successfully tested the simulator and tentative DAR and found that it is possible
to estimate coverage for each of requests for the mission lifetime.
Hyperspectral Imager Suite (HISUI)[1] is a Japanese future spaceborne hyperspectral instrument being developed by Ministry of Economy, Trade, and Industry (METI) and will be delivered to ISS in 2018. In HISUI project, observation strategy is important especially for hyperspectral sensor, and relationship between the limitations of sensor operation and the planned observation scenarios have to be studied. We have developed concept of multiple algorithms approach. The concept is to use two (or more) algorithm models (Long Strip Model and Score Downfall Model) for selecting observing scenes from complex data acquisition requests with satisfactory of sensor constrains. We have tested the algorithm, and found that the performance of two models depends on remaining data acquisition requests, i.e. distribution score along with orbits. We conclude that the multiple algorithms approach will be make better collection plans for HISUI comparing with single fixed approach.
Hyperspectral Imager Suite (HISUI) is a Japanese future spaceborne hyperspectral instrument being developed by Ministry of Economy, Trade, and Industry (METI) and will be launched in 2016 or later. HISUI’s operation strategic study is described in this paper. In HISUI project, Operation Mission Planning (OMP) team will make long- and short-term observation strategy of the sensor. OMP is important for HISUI especially for hyperspectral sensor with narrow swath of 30 km.
There are two major limitations on the operation of HISUI Hyperspectral Imager. The first one is the maximum observation time per orbit. This is due to the cooling systems of the instrument to keep the instruments temperature within the design requirements. The maximum observation time per orbit is set to 15 minutes as the current baseline. The second one is maximum data downlink amount per day. This is a limitation given by communication link of the satellite bus and heavily depends on the operation of the platform satellite. The current baseline is 150 GB per day for hyperspectral sensor and 550 GB for multispectral sensor.
We have developed observation coverage simulation program and studied the relationship between the limitations of sensor operation and the planned observation scenarios.
The achievements of global mapping or regional monitoring need to be simulated precisely before launch. We have prepared daily global high resolution (30 second in latitude and longitude) cloud coverage data.
The results of the simulations shows that HISUI will be able to acquire cloud free image of about 70 % of the terrestrial surface in three years (at the condition of 150 GB/day downlink rate).
Hyperspectral Imager Suite (HISUI) is a Japanese future spaceborne hyperspectral instrument being
developed by Ministry of Economy, Trade, and Industry (METI) and will be launched in 2015 or later. HISUI’s
operation strategic study is described in this paper. In HISUI project, Operation Mission Planning (OMP) team will
make long- and short-term observation strategy of the sensor. OMP is important for HISUI especially for hyperspectral
sensor, and relationship between the limitations of sensor operation and the planned observation scenarios have to be
studied. Major factors of the limitations are the combinations of downlink rate, observation time (15 minutes per orbit)
and the swath of the sensor (30 km). The achievements of global mapping or regional monitoring need to be simulated
precisely before launch. We have prepared daily global high resolution (30 second in latitude and longitude) climate
data for the simulation.
HISUI, a Japanese future spaceborne hyperspectral and multispectral imaging system, is currently being developed by
Japanese Ministry of Economy, Trade, and Industry. Because of the narrow swath of the imager as well as the limits on
the operation time and data downlink resource allocation, the operation strategy of HISUI should be examined
thoroughly to fully utilize HISUI's earth observation capability. A software which simulates HISUI's operation is being
developed for the detailed analysis of HISUI's long term operation plans. The simulation results indicate that 1) one-time
priority area mapping will be completed within eight months with moderate data downlink allocation, 2) one-time global
observation in a year will be possible if the allocated downlink capability is more than 250 GByte per day, 3) the
nighttime volcano monitoring will not significantly affect the daytime observation if the cross track pointing only for
nighttime observation is not allowed.
Hyperspectral Imager Suite (HISUI) is a Japanese future spaceborne hyperspectral
instrument being developed by Ministry of Economy, Trade, and Industry (METI) and will be launched in
2015 or later. HISUI's operation strategic study is described in this paper. In HISUI project, Operation
Mission Planning (OMP) team has responsibility to make long term and short term strategy of the
observation and sensor operation plan. The OMP is important for HISUI to archive both global mapping
and monitoring of specific sites. Major factors of the HISUI operation limitations are downlink rate,
observation time (15 minutes per orbit) and the swath of the sensor (30 km). The OMP plans to use
detailed climate data generated from MODIS data for observation simulation. The workflow to deal
cloud climate data is described in this paper.
Surface emissivity in the thermal infrared region is an important parameter for the studies of energy budget and surface energy balance. This paper focuses on estimating broadband emissivity using two sensors on NASA's Earth Observing System (EOS) Terra satellite, Advanced Spaceborne Thermal Emission and reflection Radiometer (ASTER) and MODerate resolution Imaging Spectrometer (MODIS). We developed a regression approach to generate infrared broadband emissivity maps from ASTER or MODIS data. The regressions are to relate the broadband emissivity to the emissivities for the ASTER or MODIS channels. The both regressions were calibrated using libraries of spectral emissivities.
We applied this approach for ASTER and MODIS data acquired over the North Africa and Australia. The range of the broadband emissivity was found to be between 0.86 and 0.96 for the desert area. The root mean difference between the emissivities from these two sensors is smaller than 0.015. Such emissivity map could be used as an input of climate model and could contribute for improving the simulated surface and air temperature up to 1.1 and 0.8 °C respectively. The method can be applied to any arid regions of the world.
Accurate, spatially distributed surface temperatures are required for modeling evapotranspiration (ET) over agricultural fields under wide ranging conditions, including stressed and unstressed vegetation. Modeling approaches that use surface temperature observations, however, have the burden of estimating surface emissivities. Emissivity estimation, the subject of much recent research, is facilitated by observations in multiple thermal infrared bands. But it is nevertheless a difficult task. Using observations from multiband thermal sensors, ASTER and MASTER, estimated surface emissivities and temperatures are retrieved in two different ways: the temperature emissivity separation approach (TES), and the normalized emissivity approach (NEM). Both rely upon empirical relationships, but the assumed relationships are different. TES relies upon a relationship between the minimum spectral emissivity and the range of observed emissivities. NEM relies upon an assumption that at least one thermal band has a predetermined emissivity (close to 1.0). Experiments comparing TES and NEM were performed using simulated observations from spectral library data, and with actual data from two different landscapes-- one in central Oklahoma, USA, and another in southern New Mexico, USA. The simulation results suggest that TES's empirical relationship is more realistic than NEM's assumed maximum emissivity, and therefore TES temperature estimates are more accurate than NEM estimates. But when using remote sensing data, TES estimates of maximum emissivities are lower than expected, thus causing overestimated temperatures. Work in progress will determine the significance of this overestimation by comparing ground level measurements against the remote sensing observations.
The Advanced Spaceborne Thermal Emission Reflectance Radiometer (ASTER) has acquired more than a dozen clear sky scenes over the Jornada Experimental Range in New Mexico since the launch of NASA's Terra satellite in December, 1999. To support the ASTER overpasses there were simultaneous field campaigns for the 5/09/00, 5/12/01, 9/17/01 and 5/15/02 scenes. Also, data from an airborne simulator, MASTER, were obtained for the 5/12/01 and 5/15/02 scenes to provide high resolution (3 m) data roughly coincident with ASTER. The Jornada Experimental Range is a long term ecological reserve (LTER) site located at the northern end of the Chihuahuan desert. The site is typical of a desert grassland where the main vegetation components are grass and shrubs. The White Sands National Monument is also within several of the scenes. ASTER has 5 channels in the 8 to 12 micrometer wave band with 90 meter resolution and thus is able to provide information on both the surface temperature and emissivity. The Temperature Emissivity Separation (TES) algorithm was used to extract emissivity values from the ASTER data for 5 sites on the Jornada and for the gypsum sand at White Sands. The results are in good agreement with values calculated from the lab spectra for gypsum and with each other. The results for sites in the Jornada show reasonable agreement with the lab results when the mixed pixel problem is taken into account. These results indicate ASTER and TES are working very well. The surface brightness temperatures from ASTER were in reasonable agreement with measurements made on the ground during the field campaigns.
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