本多 嘉明

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.

For a comprehensive vegetation monitoring and/or management, a good understanding of the distribution of the solar radiation energy among components of this vegetation is needed. The energy received by the vegetation is measured by spectroradiometers either at satellite elevations or near the ground (in situ measurements). In this study, in situ, radiometric data and laser scanning techniques are combined, in order to evaluate the contribution of the vegetation structure to the variability of canopy reflectance. Advanced processing laser techniques are not only an efficient tool for the generation of physical models but also give information about the vertical structure of canopies (height, shape, density) and their horizontal extension. To conduct this study, airborne multispectral radiation data and, laser pulse returns are recorded from a low flying helicopter above the vegetation of a boreal forest. These measurements are used to derive canopy optical and structural variables. The impact of the canopy 2-dimensional structural variability on the distribution of the solar radiation reflected by plants of this area is discussed. The results obtained show that the laser technology can be used for the selection of the most appropriate configuration of radiation measurements, and optimization of canopy physical characteristics, in future airborne missions.

Land cover is classified over East Asia using 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) land surface reflectance, MODIS snow cover and Operational Linescan System (OLS) human settlement data. The classification method includes a decision tree classification scheme that considers 11 kinds of land surface features derived from the OLS product and the time series of two MODIS products in 2000. The decision tree was defined manually based on the experiment because of insufficient training data, ease of tuning by visual interpretation, and extensibility to further research. The resulting classification is compared to three kinds of reference data, i.e. MODIS land cover product, Chinese digital land cover map, and Chinese census. The land cover classification can be input into a hydrological model applied to the Yellow River in China.

A study was conducted in Chiba, Japan, to validate Moderate Resolution Imaging Spectroradiometer (MODIS) albedo products by taking the field measurements of shortwave band albedos in paddy fields. A large difference in spatial scale, from field-measured point data to 1-km resolution, complicates the validation process. To assess such effect of different spatial scales, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Enhanced Thematic Mapper Plus (ETM+) data were used. Spatial scale effects on the albedo were examined from three viewpoints: 1) comparison between point-based albedo and mean of albedo in homogeneous area; 2) comparison between point-based albedo and 1-km aggregated albedo; and 3) assessment of semivariogram of albedo in homogeneous area. In implementation of viewpoint 2), Liang's regression model was applied to convert ASTER reflectance into shortwave band albedo. The I-km ASTER albedo was estimated using the point spread function, and in the same manner, I-km ETM+ albedo was estimated. All results represent that an area around the measurement site can be assumed to be homogeneous, indicating negligible effects of spatial resolution difference during most of the periods. Comparison of ground-point-based albedos with MODIS actual albedo, estimated from MODIS black-sky albedo, white-sky albedo, and a fraction of diffuse skylight, showed that the accuracy of MODIS albedo products for paddy fields in Japan is within approximately 0.026 by absolute value (root-mean-square error) and 15.1% by relative value.

For the purpose to detect the change of agricultural area in large irrigation districts in the Yellow River basin, the method to estimate the agricultural area accurately using coarse resolution sensor i.e. AVHRR was developed on the Ningxia irrigation district. The agricultural area was calculated with higher spatial resolution sensor i.e. Landsat ETM+ by land cover classification, and it was correlated. with annual maximum NDVI derived from AVHRR in order to get the fraction of agricultural area within one AVHRR pixel. The AVHRR estimation result showed the good agreement with ETM+ calculation in the county based comparison.

全地球広域的に観測を行う衛星に搭載されるセンサーでは視野角の幅が広く, 観測された分光反射率データには二方向性反射率 (BRDF: Bi-directional Reflectance Distribution Function) 影響があることが知られている。全球植生純一次生産量 (NPP: Net Primary Production) を求め, その精度を改善するためには, BRDFモデルを利用して, NPPの推定におけるBRDFの影響を評価する必要がある。本研究ではスギ林に着目し, 無人ヘリコプターによりBRF (Bi-directional Reflectance Distribution Factors) 観測を行った。観測で得られたBRDFデータより, BRDFモデルの適用性を検証した上で, パラメータを決定し, モデルから計算した反射率より杉スギ林のNPPを推定した。その結果は0.36kgCO₂/m²/monthとなり, 森林調査の結果0.32kgCO₂/m²/monthと一致した。また, GLIセンサーの観測状況をシミュレーションした上で, スギ林に対して, NPPの推定におけるBRDFの影響を調べた。その結果は11%であった。

For the purpose to detect the change of agricultural area in large irrigation districts in the Yellow River basin, the method to estimate the agricultural area accurately using coarse resolution sensor i.e. AVHRR was developed on the Ningxia irrigation district. The agricultural area was calculated with higher spatial resolution sensor i.e. Landsat ETM+ by land cover classification, and it was correlated with annual maximum NDVI derived from AVHRR in order to get the fraction of agricultural area within one AVHRR pixel. The AVHRR estimation result showed the good agreement with ETM+ calculation in the county based comparison.

Estimating evapotranspiration (ET) is of the highest importance for understanding and eventually intervening in the water cycle of natural systems. ET is one of the major factors influencing climate change at local, regional and global levels. In this study, a surface energy balance method, which combines meteorological observations with spectral data derived from remote sensing measurements, was used to estimate the ET. The Surface Energy Balance Algorithm for Land (SEBAL) has been applied to Landsat+ETM and NOAA-AVHRR sensors for the estimation of ET in Mongolia, a large arid and semi-arid region with homogeneous surface conditions, on 10 August 1999. Actual ET was computed during satellite overpass and integrated for 24-h on pixel-by-pixel basis for daily ET distribution. As a result, a daily ET map over the arid and semi-arid region of Mongolia was analysed some observation data, such as radiations and surface temperature, was compared with estimated data. © 2005 Taylor &amp Francis.

Vegetation over land plays an important role to the carbon cycle, which influences global warming. It is necessary to measure vegetation amount accurately on global scale to understand the carbon cycle mechanism. The Japan Aerospace Exploration Agency (JAXA; former NASDA) has successfully launched a new Advanced Earth Orbiting Satellite (ADEOS-II) aboard an H-2A booster on December 14, 2002. The ADEOS-II satellite is focused on monitoring of global climate change on the Earth. Unfortunately, the operation of ADEOS-II satellite has stopped on October 24 of 2003, but very important VNIR/SWIR/MTIR data have been obtained in northern hemisphere for vegetation dynamics by GLI sensor. These data have enough capability to monitor the density and vigor of green vegetation. GLI data has high potential for vegetation monitoring, and it will contribute to the future satellite sensor. 23 channels are dedicated for land observations in the two spatial resolutions (1km/250m). MODIS sensor has also 1km/250m resolution and various land products, which include VIs. This paper shows the preliminary evaluation of GLI land products for vegetation monitoring using MODIS VIs product.

The effect of the bidirectional reflectance distribution function (BRDF) is one of the most important factors in correcting and validating the reflectance obtained from remotely sensed data. While the importance of BRDF has become widely recognized, bidirectional reflectance factor (BRF) data measured for correction and validation are insufficient because of the technical difficulty of the measurement. The primary objective of the present research is to estimate BRDF effects from Moderate Resolution Imaging Spectroradiometer (MODIS) data. Temporal ground-based BRDFs of rice paddy fields were estimated from ground measurements conducted in June and August 2002. MODIS-derived BRDFs obtained from MODIS reflectance data and ground-based BRDFs were estimated using the reciprocal form of the RossThick and LiSparse (RossThick-LiSparse-R) kernels, a semiempirical BRDF model adopted for the operational MODIS BRDF product. The MODIS-derived band 1 (620-680 nm) and band 2 (841-876 nm) BRDFs were compared with the ground-based BRDFs corresponding to the same waveband, respectively. The comparison results demonstrate that BRDFs of paddy fields change in accordance with paddy growth and that MODIS-derived BRDFs are closely related to ground-based BRDFs in most of the cases. It was also revealed that MODIS-derived BRDFs can be estimated to a high degree of accuracy when MODIS data necessary for the estimation are available.

The influence of soil condition in remote sensing data have not been clearly explained. Therefore, it is important to study the relationship between ground survey data and remote sensing data. Ground survey on soil condition such as topography, soil moisture, soil color and soil particle size were carried out in Mandal-GOBI, Mongolia on every August 1998 to 2002. The test area was covered by thin grass, the coverage ranges from 12% to 28%.<BR>Topographic survey was used kinematic GPS. Soil moisture was measured in 3cm depth by four-pin prove sensor. The measurement on ground surface was very difficult. Measured soil moisture ratio indicated 0.05 to 0.20 and topography was no related to the soil moisture. Soil color was measured by HSI value in digital camera images. The result showed soil color was almost same condition. Therefore, soil moisture and soil color was disregard in this study. Soil particle size was also measured by the digital camera images. Visual interpretation of the images was carried out to classify five categories of soil particle size.<BR>In this study, TERRA ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) image was compared with soil particle size. Firstly, ASTER image was geometrically rectified with topographic data by image matching. And topographic influence of the ASTER image was removed by logarithmic residuals method. The digital number in band 7 and band 8 had tendency to drop with large soil particle size. The digital number in Band 9 had tendency to rise with large soil particle size. Those tendencies were noticeable results in vegetated area. Therefore, vegetation condition should be discussed to understand the results.

Land cover classification over Yellow River basin, China, by means of simple decision tree classification method using multitemporal metrics derived from MODIS data is shown in this paper. Since the land cover is one of the input parameters for the hydrological model, the critical feature of classification method is to control the classification result using threshold values. The tentative result shows good correlations with existing digital land use map, though the small overestimation or underestimation are recognized in several categories and the improvement is necessary in discriminating the single cropped agricultural field from natural grassland. The adjustments of the threshold values established in the decision tree would be done by the aid of higher resolution satellite data.

The concept study of new multi spectral imager has been showed. Multi spectral imager is the basic sensor for Earth remote sensing. The result of Global Imager (GLI) of Advanced Earth Observation Satellite -2 (ADEOS-2) showed us the various change of climate system. However, according to the progress of climate system change study, the reconsideration of observation channels is necessary. First, we studied the requirements of the next generation imager on the basis of GLI design considering the less observed parameters of the climate change. Then we found the necessity of the parameters related the human activities. Several parameters of each area, i.e., atmosphere, ocean, land, cryosphere, are selected. For the atmosphere, aerosol over land is emphasized. For the ocean, coastal change observation is proposed. For the land, advanced vegetation index is proposed. For the cryosphere, impurity of snow is emphasized. For the observation purposes, the proposed imager requirements are including the multi-angle polarization observation. And the resolution requirements of most channels are changed from 1 km to 250m. As the result of preliminary engineering study, the imager consists of a push broom imager for Visible and Near Infrared (VNIR) region, and a whisk broom imager for Shortwave Infrared (SWIR) and Thermal Infrared (TIR) region. Among the all channels, two channels, center wavelength 678 nm and 865 nm, are defined as multi-angle polarization observation channels. Each channel has fore, nadir, aft angles, also three polarization angles. The satellite orbit is about 800 km height sun-synchronous polar orbit to cover global area. The new sensor was named Second generation of Global Imager (SGLI). We are proposing to launch SGLI around 2010 on a satellite of Global Change Observation Mission (GCOM).