To validate terrestrial ecological products of the Global Change Observation Mission-Climate (GCOM-C) satellite, a large-scale ecological observation project "JAXA Super Sites 500" was initiated. The project's purpose is to obtain the representative leaf area index (LAI), above-ground biomass (AGB), and fraction of absorbed PAR (fAPAR) in the satellite footprint scale. This study aimed to determine the appropriate observation methods in the satellite scale for the target land-cover types such as a deciduous broadleaved forest, evergreen/deciduous needle-leaved forests, and a grassland. As a result of the comparative observations, a combination method using litter-traps and LAI- 2200 was adopted as the LAI observation in a forest, a tree census method was adopted as the AGB observation in a forest, and a clipping method was adopted as the AGB and LAI observations in a grassland. LAI, AGB, and fAPAR were observed and were used to validate the GCOM-C terrestrial ecological products.

Japan Aerospace Exploration Agency (JAXA) had launched new Earth observation satellite GCOM-C in the end of 2017. The core sensor of GCOM-C, Second Generation Global Imager (SGLI) has a set of along track slant viewing Visible and Near Infrared Radiometer (VNR). These multi-angular views aim to detect the structural information from vegetation canopy, especially forest canopy, for estimating productivity of the vegetation. SGLI Land science team has been developing the algorithm for Above Ground Biomass, Vegetation Index, Shadow Index, etc. We developed the ground observation method using Unmanned Aerial Vehicle (UAV) in order to contribute the algorithm development and its validation. Mainly, multi-angular spectral observation method and simple BRF model have been developed for estimating slant view response of forest canopy. The BRDF model developed by using multi-angular measurement has been able to obtain structural information from canopy. In addition, we have conducted some observation campaigns on typical forest in Japan in collaboration with other science team experienced with vegetation phenology and carbon flux measurement. Primary result, Above-ground biomass of these observations are also be demonstrated.

The Global Change Observation Mission (GCOM) consists of two satellite missions, GCOM-W (Water) and GCOM-C (Climate), and aims to provide comprehensive information of the Essential Climate Variables (ECVs) of atmosphere, ocean, land, cryosphere and ecosystem. The GCOM-W "SHIZUKU" satellite was launched in May 2012, which carries the Advanced Microwave Scanning Radiometer 2 (AMSR2). It achieved its 5-year designed mission life in May 2017 and is currently in extended mission phase. The GCOM-W satellite is joining in the A-train orbit to provide synergies with the other A-train satellites, such as Aqua and Cloudsat. The GCOM-C "SHIKISAI" satellite was launched in December 2017, which carries the Second generation Global Imager (SGLI). SGLI data has been released to public since December 20, 2018. Both AMSR2 and SGLI data are used in operational numerical weather prediction and environmental monitoring to reduce meteorological disasters. Because of its observation capability and observation local time, both GCOM satellites have synergies with the Joint Polar Satellite System (JPSS) program and can contribute to objectives of JPSS.

Japan Aerospace Exploration Agency (JAXA) had launched new Earth observation satellite GCOM-C in the end of 2017. The core sensor of GCOM-C, Second Generation Global Imager (SGLI) has a set of along track slant viewing Visible and Near Infrared Radiometer (VNR). These multi-angular views aim to detect the structural information from vegetation canopy, especially forest canopy, for estimating productivity of the vegetation. SGLI Land science team has been developing the algorithm for Above Ground Biomass, Vegetation Index, Shadow Index, etc. We developed the ground observation method using Unmanned Aerial Vehicle (UAV) in order to contribute the algorithm development and its validation. Mainly, multiangular spectral observation method and simple BRF model have been developed for estimating slant view response of forest canopy. The BRF model developed by using multiangular measurement has been able to obtain structural information from canopy. In addition, we have conducted some observation campaigns on typical forest in Japan in collaboration with other science team experienced with vegetation phenology and carbon flux measurement. Primary results of these observations are also be demonstrated.

For monitoring of global environmental change, the Japan Aerospace Exploration Agency (JAXA) has made a new plan of Global Change Observation Mission (GCOM). 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) 250m resolutions over land and area along the shore, 2) Three directional polarization observation (red and NIR), and 3) 500m resolutions temperature over land and area along shore. The final check of the sensor system has been completed in 2016. The final check of the entire satellite system will be completed in the first half of 2017. The launch of GCOM — C is scheduled for the second half of 2017. These characteristics are useful in many fields of social benefits. In addition, 51 products will be made by mainly 35 principal investigators. There are 14 land products of SGLI (standard products are 9, and research products are 5). Already the Land team completed most of the algorithm and have created a product validation plan. Currently land team are improving the performance of the algorithm and preparing for verification. These activities are reported in this paper.

The global leaf area index (LAI) and above-ground biomass (AGB) are essential parameters in ecology and hydrology. Therefore, dataseis derived from satellite remote sensing are needed. To assess data accuracy, in-situ datasets of LAI and AGB measured at a large scale (that of satellite footprints) are desired. However, such data are rarely available. Therefore, we initiated the project "JAXA Super Sites 500" to obtain in-situ LAI and AGB data at the 500 m × 500 m scale. We established four observation sites in Japan and carried out pilot studies at two sites in 2014. This study aimed to examine an observation method at this scale and to evaluate the data quality. At the Fujihokuroku site, the mean LAI was 1.89 (LAI-2000), 2.85 (fish-eye camera), and 2.14 (tree census within a partial area). The mean AGB was 117 t/ha (Bitterlich's method) and 126 t/ha (tree census within a partial area).

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.

Various remote sensing technologies are utilized to monitor tropical forest for REDD project. In developing countries, the accuracy of field measurement does not satisfy the quality required for the validation of satellite remotely sensed data. Therefore, we introduce the most portable laser sensor, SICK LMS511, to measure trees in the field of tropical forest and the semi-automatic process to derive tree parameters from the 3D point cloud is established to provide accurate forest inventory data. From the accuracy assessment of the portable laser system provided 3.61 cm of root mean square error (RMSE) of stem diameter and 0.50 m of RMSE of tree height measurement. The portable terrestrial laser sensor can be the standard technique to create forest inventory data for the field validation of satellite remote sensing.

Japan Aerospace Exploration Agency (JAXA) is going to launch new Earth observation satellite GCOM-C1 in 2016. The core sensor of GCOM-C1, Second Generation Global Imager (SGLI) has a set of along track slant viewing Visible and Near Infrared Radiometer (VNR). These multi-angular views aim to detect the structural information from vegetation canopy, especially forest canopy, for estimating productivity of the vegetation. SGLI Land science team has been developing the algorithm for above ground biomass, canopy roughness index, shadow index, etc. In this paper, we introduce the ground observation method developed by using Unmanned Aerial Vehicle (UAV) in order to contribute the algorithm development and its validation. Mainly, multi-angular spectral observation method and simple BRF model have been developed for estimating slant view response of forest canopy. The BRF model developed by using multi-angular measurement has been able to obtain structural information from canopy. In addition, we have conducted some observation campaigns on typical forest in Japan in collaboration with other science team experienced with vegetation phenology and carbon flux measurement. Primary results of these observations are also be demonstrated.

For monitoring of global environmental change, the Japan Aerospace Exploration Agency (JAXA) has made a new plan of Global Change Observation Mission (GCOM). 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) 250m resolutions over land and area along the shore, 2) Three directional polarization observation (red and NIR), and 3) 500m resolutions temperature over land and area along shore. SGLI has a set of along track slant viewing Visible and Near Infrared Radiometer (VNR). These multi-angular views aim to detect the structural information from vegetation canopy, especially forest canopy, for estimating productivity of the vegetation. SGLI Land science team has been developing the algorithm for above ground biomass, canopy roughness index, shadow index, etc. In this paper, we introduce SGLI characteristics and the ground observation method developed by using Unmanned Aerial Vehicle (UAV) in order to contribute the algorithm development and its validation. Mainly, multi-angular spectral observation method and simple BRF model have been developed for estimating slant view response of forest canopy. The BRF model developed by using multi-angular measurement has been able to obtain structural information from vegetation canopy. In addition, we have conducted some observation campaigns on typical forest in Japan in collaboration with other science team experienced with vegetation phenology and carbon flux measurement. Primary results of these observations are also be demonstrated.

For monitoring of global environmental change, the Japan Aerospace Exploration Agency (JAXA) has made a new plan of Global Change Observation Mission (GCOM). 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) 250m resolutions over land and area along the shore, 2) Three directional polarization observation (red and NIR), and 3) 500m resolutions temperature over land and area along shore. These characteristics are useful in many fields of social benefits. In addition, 51 products will be made by mainly 35 principal investigators. We introduce the overview of GCOM-C1/SGLI science.

The Japan Aerospace Exploration Agency (JAXA) is pursuing the Global Change Observation Mission (GCOM) that will inherit the Advanced Earth Observing Satellite-II (ADEOS-II) mission and develop into long-term monitoring. GCOM is not the name of a single satellite, but of a mission that consists of two series of medium-size satellites, GCOM-W (Water) and GCOM-C (Climate), and three generations of each satellite series to continue the observations for 10 to 15 years. The Advanced Microwave Scanning Radiometer-2 (AMSR2) will be the single instrument on the GCOM-W1 satellite, which is the first satellite of the GCOM series. The second satellite will be GCOM-C1, which will carry the Second-generation Global Imager (SGLI). GCOM-W will mainly contribute to the observations related to global water and energy circulation, while GCOM-C will contribute to the measurements related to the carbon cycle and radiation budget. Current target launch years are calendar year 2011 for GCOM-W1 and 2014 for C1.

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 1-km ASTER albedo was estimated using the point spread function, and in the same manner, 1-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 NDVT 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.

In the present paper, the validation results of Mod- erate Resolution Imaging Spectroradiometer (MODIS) albedo products are reported. Measurements of shortwave band albedos have been conducted for paddy fields in Chiba, Japan from April to December of 2004. The accuracy of MODIS 1-km albedo products for paddy fields in Japan was found to be within approximately 0.03. In addition, the results indicate that the degradation of the accuracy may be caused by an insufficient number of observations, which is deeply related to the quality of the estimated BRDF model parameters. Considering the robustness of the BRDF estimation strongly affects the robustness of the albedo estimation, a robust method that can estimate BRDF even if the number of observations is limited should be developed.

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.

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 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 bidirectional reflectance distribution function (BRDF) effect has been one of the most important factors in correcting the reflectance obtained from remotely sensed data, especially the data having wide swath, e.g. Moderate Resolution Imaging Spectroradiometer (MODIS) data. For the BRDF effect correction, it is one of the most effective approaches to estimate the reflectance at nadir based on the estimated BRDF. While the estimation of BRDF model parameter requires a set of several data, such data are not always available in fact. In the present research, temporal MODIS reflectance data were corrected to the reflectance at nadir by the following procedure. If sufficient data are available, parameters of kernel-driven BRDF model, a semi-empirical BRDF model, were estimated to calculate the reflectance at nadir. If not, BRDF model parameters were interpolated using the estimated parameters. In the present paper, the preliminary experimental results are reported.

In order to develop and/or improve algorithms of extracting various sea ice parameters, such as sea ice concentration, sea ice thickness, and sea ice types from ALOS data, it is necessary to prepare certain data set for verification. This paper describes about the preparation of multi-stage remote sensing for obtaining a series of remotely sensed data of sea ice in the Okhotsk Sea.

A new vegetation index is proposed. Ordinal vegetation index can show intensity of vegetation on the ground. It can not show structure of vegetation surface or texture. The proposed vegetation index utilizes BRF property. It is generated from data from 2 satellite orbits and it is able to show the structure of the vegetation surface or texture. Principles of this index is coming from field observation using RC helicopter. Each vegetation canopy has different texture and roughness. The new index, named BSI (Bi-directional reflectance Structure Index) shows difference of vegetation canopy. It is calculated by using the data of NOAA/AVHRR, ADEOS OCTS. ADEOS-II GLI can derive BSI.

The effect of Bidirectional Reflectance Distribution Function (BRDF) is one of the most important factors to calibrate reflectance obtained from remotely sensed data. Because the measured BRDF data involve noise caused by various factors, BRDF model parameter estimation tends to become unstable. We examined parameter estimation robustness by using BRDF data measured at paddy fields in Japan, and experimental result of the estimation is described in this paper.