Masao Moriyama

The sea surface temperature product algorithm of the Ocean Color and Temperature Scanner (OCTS) and its accuracy

The Ocean Color and Temperature Scanner (OCTS) aboard the Advanced Earth Observing Satellite (ADEOS) can observe ocean color and sea surface temperature (SST) simultaneously. This paper explains the algorithm for the OCTS SST product in the NASDA OCTS mission. In the development of the latest, third version (V3) algorithm, the OCTS match-up dataset plays an important role, especially when the coefficients required in the MCSST equation are derived and the equation form is adjusted. As a result of the validation using the OCTS match-up dataset, the algorithm has improved the root mean square (rms) error of the OCTS SST up to 0.698°C although some problems remain in the match-up dataset used in the present study.

Early evaluation of ASTER emissivity products and its application to environmental and geologic studies

Land Surface Emissivity product is one of standard products generated from Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) on NASAs Terra satellite launched in December 1999. This product is important for detailed lithologic mapping and precise land surface temperature determination. The accuracy of ASTER-derived emissivity is a function of various factors such as radiometric calibration of the instrument, assumptions used in a temperature-emissivity separation algorithm, and spatial temperature/material mixture in a pixel. In this study, the effects of spatial material mixture on ASTER-derived emissivity are investigated as one of the validation activities of this product. First, the mixture effects on ASTER-derived emissivity are evaluated through numerical simulations under various land surface material and temperature conditions. Also, at several sites including Cuprite, Nevada, ASTER-derived emissivity and airborne sensor-derived emissivity are compared. Applications of ASTER emissivity products to environmental and geologic studies will be also presented.

Adaptive least squares method for estimation of partial cloud coverage within a pixel

Abstract A study of the estimation of partial cloud cover within a pixel has been conducted in order to be able to use pixels partially contaminated with cloud in sea surface temperature determination. The existing estimation methods based on the least squares method with constraints of minimizing the mixing ratio and observation vector, are theoretically compared and then an adaptive least squares method is proposed. In a comparative study the estimation accuracies for the proposed and other existing methods, including the maximum likelihood method, are compared with simulated and real satellite image data of NOAA AVHRR and MOS-1 VTIR. The results with the simulation data show that the maximum likelihood method is best followed by the adaptive least squares method, the least squares method and the observation vector, while the results with the real VTIR data show that the proposed adaptive least squares method is best followed by the least squares method, the maximum likelihood method and the observation...

Iterative estimation of the earth surface temperature and emissivity

Abstract To estimate the earth surface temperature and emissivity from the satellite detected non-atmospherically corrected thermal IR data, an iterative estimation method is proposed. At first, the radiative transfer equation which describes the transfer process of the radiation from the surface to the satellite is simplified into the non-linear equation. Next, the inter-variable relationship is investigated and the unknown variables are reduced. And the constrainted non-linear optimization technique is adopted to solve the approximated radiative transfer equation. To verify this method, the numerically simulated data are used and the results show the effectiveness of this method and the potential for the multispectral TIR remote sensing data.

Comparison of the sea surface temperature estimation methods

Abstract The comparison between two kinds of sea surface temperature estimation methods for multispectral (over 2 channels) TIR data are made. The first one is the conventional split window method and the second one is the newly proposed physical based method. The comparison is based on the simulated spaceborne TIMS data, three kinds of the channel selections are used in each method. From the results, it is not efficient for the split window to increase the spectral channel because of high correlation between channels, but for the physical based method, use of multiple channels is efficient especially in the case of relatively large noise.

The examination of land products from GCOM-C1/SGLI

The Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) concluded that many collective observations gave a aspect of a global warming and other changes in the climate system. It is very important to understand this process accurately, and to construct the model by whom an environmental change is accurately forecast. Future earth observation using satellite data should monitor global climate change, and should contribute to social benefits. Especially, human activities has given the big impacts to earth environment. This is a very complex affair, and nature itself also impacts the clouds, namely the seasonal variations. JAXA (former NASDA) has the plan of the Global Change Observation Mission (GCOM) formonitoring of global environmental change. SGLI (Second Generation GLI) onboard GCOM-C 1 (Climate) satellite, which is one of this mission, is an optical sensor from Near-UV to TIR. SGLI can provide the various high accuracy products of aerosol, cloud information, various biophysical parameters (Biomass, Land Cover, Albedo, NPP, Water Stressed Vegetation, LST, etc.), coastal information (CDOM, SS, PAR, CHL, SST, etc.), and cryospheric information (Albedo, Snow/Ice Cover, NDII, Sea ice type, Snow Grain Size, NDSI, Snow Surface Temperature, etc.). This paper shows the introduction of the unique aspects and characteristics of the next generation satellite sensor, SGLI/GCOM-C, and shows the preliminary research for this sensor.

The relationship between land-surface temperature and rice quality in Tottori prefecture, Japan

Numerous studies have suggested that rice quality in Japan is affected by high temperatures during the ripening period, especially in summer. On the assumption that land-surface temperature (LST) can be substituted for air temperature, we examined rice quality using LST satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) during the ripening stage (August) in Tottori prefecture. Rice quality in Tottori was very low compared with Japan as a whole and to neighbouring prefectures. LST was correlated with minimum and average air temperatures in August at six meteorological stations in Tottori. Rice quality decreased with increasing LST, and the threshold LST value when the quality of rice was less than 50% was 307 K (33.9 °C). The spatial distribution of LST in August indicated that LST values over 307 K were widespread, especially in coastal and lowland areas, and areas with the highest rice quality corresponded with intermountain regions that had LSTs less than 307 K.

An assessment of ASTER surface reflectance products generated by GEO Grid

The GEO Grid is an e-infrastructure, which is capable in archiving large amount of satellite data and conducting higher level processing using the advanced grid technologies.1 The Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) Level 0 data are stored in a cluster system on GEO Grid, and ASTER ortho-rectified radiance and Digital Elevation Model (DEM) products are able to be generated on this system globally since 2000. This research shows validation of new ASTER surface reflectance products generated by the GEO Grid system, which can apply the radiometric and atmospheric correction to ASTER ortho-rectified radiance data of Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR).

A study on the possibility of land vegetation observation with SGLI/GCOM-C

The Fourth Assessment Report of IPCC predicted that global warming is already happening and it should be caused from the increase of greenhouse gases by the extension of human activities. These global changes will give a serious influence for human society. Global environment can be monitored by the earth observation using satellite. For the observation of global climate change and resolving the global warming process, satellite should be useful equipment and its detecting data contribute to social benefits effectively. JAXA (former NASDA) has made a new plan of the Global Change Observation Mission (GCOM) for monitoring of global environmental change. SGLI (Second Generation GLI) onboard GCOM-C (Climate) satellite, which is one of this mission, provides an optical sensor from Near-UV to TIR. Characteristic specifications of SGLI are as follows; 1) 250 m resolutions over land and area along the shore, 2) Three directional polarization observation (red and NIR), and 3) 500 m resolutions temperature over land and area along shore. These characteristics are useful in many fields of social benefits. For example, multi-angular observation and 250 m high frequency observation give new knowledge in monitoring of land vegetation. It is expected that land products with land aerosol information by polarization observation are improved remarkably. We are studying these possibilities by ground data and satellite data.

Vicarious and cross calibration methods for satellite thermal infrared sensors using hot ground targets

For radiometric calibration of ASTER TIR and Landsat-7 ETM+ thermal infrared band, vicarious calibration (VC) and cross calibration (CC) experiments were carried out in Lake Tahoe (Nevada), Salton Sea (California), and Railroad Valley (Nevada) in 2000. For Salton Sea and Railroad Valley, ground temperature measurements were conducted in large playas during overpasses of these satellites. For Lake Tahoe, airborne MASTER data were acquired. Atmospheric profile data were obtained by radiosonde during the experiments. These calibration results show that the radiant temperature of ASTER TIR, based on the on-board blackbody, is lower than those of VC/CC at high temperature, the ETM+ band 6 is 3/spl deg/C (except in Railroad Valley) higher than those of VC/CC. VC/CC accuracy is better than 1/spl deg/C (radiometric calibration requirement of ASTER TIR).