本多 嘉明

The global leaf area index (LAI) and above-ground biomass (AGB) are essential parameters in ecology and hydrology. Therefore, datasets derived from satellite remote sensing are needed. To assess data accuracy, insitu 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 x 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 LA! 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).

レーザースキャナーが身近に利用できるようになり，3 次元レーザーデータから樹木調査ができるようになってきた。本研究では北海道大学中川研究林において，様々な樹種構成のある22 箇所のプロットで簡易型地上レーザーを用いて3 次元データを取得し，得られたデータから森林簿作成に必要な樹高，胸高直径，枝下高，毎木位置図を作成した。本研究に用いた簡易型地上レーザーは半径50 m まで照射できるSICK LMS511 であり，市販されているレーザーセンサーの中で安価な製品の一つである。安価で可搬性に富む簡易型地上レーザーを用いた毎木調査法を確立するために，樹木測定精度を明らかにした。

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.

The canopy shadow fraction (CSF) is composed of the fractional area covered by shadowed tree crowns and shadowed backgrounds for a given illumination and view geometry. Since the CSF is related to the canopy biological and structural features, an accurate estimation of the CSF is expected for better understanding of the canopy characteristics. This study explores an algorithm for an automated extraction of the CSF using near-surface remote sensing method. The high-spatial resolution true-color images over different forested canopies were acquired using an unmanned helicopter. For each site, the images of the same target canopy from multiple view zenith angles (VZA) were taken at the principal plane. The digital images were processed to extract the CSF using the color vegetation indices (CVI) combined with an image threshold algorithm. The CSF was measured based on visual interpretation of the grayscale images. For an automated extraction of the CSF, different CVI related to CSF were assessed with Otsu threshold algorithm. A new CVI called the blue deficient index (BDI) was proposed as an indicator of the CSF exploiting the canopy spectral properties. The performance of each automated extraction method was evaluated with comparison to measured CSF. Among the methods assessed under the study, the CSF estimated by the BDI with the Otsu algorithm was found to be most closely related to the measured CSF. After a successful extraction of the CSF, the effect of VZA on CSF was analyzed. The substantial variation of the CSF with respect to the VZA in the principal plane was confirmed for a given solar position. © 2012 Springer-Verlag Berlin Heidelberg.

Near-surface bi-directional reflectance and high-spatial resolution true-color imagery of several forested canopies were acquired using an unmanned helicopter. The observed reflectance from multiple view-zenith angles were simulated with a kernel-driven bidirectional reflectance model, and the BRDF parameters were retrieved. Based on the retrieved BRDF parameters, kernel-derived multi-angular vegetation indices (KMVIs) were computed. The potential of KMVI for prediction of canopy structural parameters such as canopy fraction and canopy volume was assessed. The performance of each KMVI was tested by comparison to field measured canopy fraction and canopy volume. For the prediction of canopy fraction, the KMVI that included the nadir-based NDVI performed better than other KMVI emphasizing the importance of nadir observation for remote estimation of the canopy fraction. The Nadir BRDF-adjusted NDVI was found to be superior for the prediction of canopy fraction, which could explain 77% variation of the canopy fraction. However, none of the existing KMVI predicted the canopy volume better than Nadir BRDF-adjusted NDVI and Nadir-view NDVI. The Canopy structural index (CSI) was proposed with the combination of normalized difference between dark-spot near infrared reflectance and hot-spot red reflectance. The CSI could establish an improved relationship with the canopy volume over Nadir BRDF-adjusted NDVI and Nadir-view NDVI, explaining 72% variation in canopy volume. In addition, MODIS based KMVI were evaluated for the prediction of canopy fraction and canopy volume. MODIS based KMVI also showed similar results to the helicopter based KMVI. The promising results shown by the CSI suggest that it could be an appropriate candidate for remote estimation of three-dimensional canopy structure. (C) 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved.

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.

The early stage of the water stressed forest shows the higher temperature before the spectral reflectance change. To detect the water stressed forest, the satellite detected surface temperature is utilized. The day and night surface temperature difference is the key factor of the detection, in the case of non-stressed forest the daytime surface temperature suppress the latent heat increase and the nighttime surface temperature is almost same as the air temperature at the surface, so that the water stress makes the daytime temperature increases. The day and night surface temperature difference is primary affected by the forest water stress level. To remove the another effect to the temperature difference such as the nighttime low air temperature in autumn, the modified day and night surface temperature difference is defined for the forest water stress detection index. Using the day night surface temperature product from MODIS and the latent heat flux dataset acquired at some sites of the AMERIFLUX, The water stressed forest is identified using the proposed index. Also the numerical simulation for the sensitivity analysis of the proposed index is made and the effectiveness of the index is clarified.. © 2012 SPIE.

In the Northern hemisphere, the CO2 concentration in the warm season indicated anomalously high values in 2003, and low values in 2004. To investigate the reasons of the interannual variation, a numerical simulation using a land biosphere - atmosphere full couple GCM was carried out. Relationship between interannual variations of CO2 and those of the land surface elements was investigated. In 2003, high surface temperature and low soil wetness conditions in the Eurasian Continent and in North America, and low downward short wave radiation condition in East Asia, occurred in the warm season. It is considered that these climate conditions in 2003 induced relatively low GPP and NEP values in the continental scale. Comparison of the simulation results of GCM with satellite data (MODIS and AMSR-E) was performed concerning the remarkable interannual changes from 2003 to 2004. Global distributions of the seasonal changes by the model almost agree with those by the satellite data regarding both the land surface temperature and the soil moisture. The interannual changes of land surface temperature by the model agree well with those by the MODIS data. As to the soil moisture, the regions exist where the interannual changes by the model disagree with those by the AMSR-E data especially in the warm season. The values of elements calculated by the model are physically and bioecologically consistent each other in the model. Therefore, the model results are useful as the relative information for the validation of the global scale or regional scale products of satellite data estimated separately by each algorithm.

It is very important to watch the spatial distribution of vegetation biomass and changes in biomass over time, representing invaluable information to improve present assessments and future projections of the terrestrial carbon cycle. A space lidar is well known as a powerful remote sensing technology for measuring the canopy height accurately. This paper describes the ISS(International Space Station)-JEM(Japanese Experimental Module)-EF(Exposed Facility) borne vegetation lidar using a two dimensional array detector in order to reduce the root mean square error (RMSE) of tree height due to sloped surface.

Japan Aerospace Exploration Agency (JAXA) is going to launch new Earth observation satellite GCOM-C1 in near future. 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 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.

The results of aeromagnetic observations at Izu-Oshima, Japan using an unmanned autonomous helicopter are reported. A practical observation system was assembled, adopting a bird-type magnetometer installation, and dense observations of the northern half of the caldera area including the central cone were made from a very low altitude. In the detailed magnetization intensity mapping deduced from the collected data, low magnetization intensity at the vent and three rows of high magnetization intensity on the caldera floor were found. The former is interpreted as the presence of high-temperature materials, such as magma or hot rock, or vacant space in the conduit. The latter is considered to be due to solidified dykes. Low magnetization intensity suggesting a magma body (or subsidiary magma chamber) was not detected below the caldera floor. The observation results confirmed that aeromagnetic observation using an unmanned autonomous helicopter had sufficient performance for volcanic observations, and could also be utilized as a low-altitude platform for other sensors. © 2011 Taylor &amp Francis.

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.

From the preliminary experiment, we received suggestion that temperature information is useful for diagnosis of water stress of the vegetation. Then, we continued the measurement of water potential, reflectance and temperature change for two sets of sample trees of Viburnum lantana by giving water to one set and cutting the supply of water to the other set. After the water shortage, water potential of the leaf was on the decrease from 12th day. On the other hand, temperature change of leaf was on the increase from 18th day, and NDWI obtained from reflectance was on the decrease from 30th day when the leaf is dying. Therefore, temperature information is more suitable and available for the early diagnosis of the water stress than NDWI.

Bidirectional reflectances obtained from optical satellite sensor is effective for the estimation of vegetation quantity (e.g., above ground biomass) because biomass is related to canopy shape and the information of that canopy shape can be obtained by bidirectional reflectance. The relationships between bidirectional reflectance and canopy shape have been modeled in several studies. However, it is extremely difficult to measure the input parameters (e.g., leaf area index, leaf inclination angle) of those models in the field. Therefore, the bidirectional reflectance predicted by those models does not match with the bidirectional reflectance observed over the canopy. On the other hand, the bidirectional reflectance obtained at top of canopy by airborne or spaceborne platform is affected by limited observation geometry. In this study, we developed bidirectional reflectance simulator (BiRS) which can simulate bidirectional reflectance in any arbitrary observation geometry. BiRS can estimate bidirectional reflectance using digital surface model (DSM) and top of canopy bidirectional reflectance obtained by radio controlled helicopter.

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.

The Third Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) concluded that many collectiveobservations gave a aspect of a global warming and other changes in the climate system. It is very important to understand thisprocess accurately, and to construct the model by whom an environmental change is accurately forecast. Future earthobservation 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.

A judicious combination of spectral and spatial surface information can improve the understanding of the vegetation optical variability and typological differentiation. The objective of this study is to evaluate the potential of airborne spectral radiation and digital imagery data for vegetation canopy classification and the impact of canopy texture on the vegetation-solar radiation interaction. To conduct the study, two multispectral radiometers with wavelengths ranging from 350 to 1050nm and a fine pixel digital camera are used. One of the radiometers is positioned close to the digital camera, and, both instruments are carried by a radio-controlled helicopter flying above the canopy of a boreal forest of the northern Japanese island of Hokkaido. Analyses of the canopy reflectance signature show a clear species differentiation in the vegetation of the area and give an evaluation of the canopy radiation capacities. The bamboo grass species have the highest reflectance and the needle-leaf species the lowest. To understand the physical factors associated with the reflectance-species typological relationship, textural features are extracted from digital images, by using colour discrimination techniques. The features estimated are the brightness intensity of the canopy, the amounts of gaps and shadows, the degree of heterogeneity of light scattering, and the green vegetation fraction. Then, the relationship between these individual properties and reflectance is examined. The results obtained show that reflectance decreases with increasing amount of gaps and shadows and, increases with the brightness intensity and more importantly with light scattering heterogeneity of the canopy. This heterogeneity effect, derived from the vegetation luminance distribution is examined through three methods. The most elaborate among these methods is the semivariogram analysis. Results of this analysis show that the range of the semivarioragram reflects well enough the average size of the plants (short range for the bamboo grass and large range for the needle-leaf species). The needle-leaf species have the highest variability, i.e. are the most heterogeneous light scatterers, while the bamboo grass species are the least variable. The scale of variability of the distribution of luminance differs according to the species: it is dominated by macrovariability in the needle-leaf, and microvariability in the bamboo grass and the broadleaf. The needle-leaf species' high spatial heterogeneity of light scattering would reduce the measured canopy bi-directional reflected radiation and enhance the transmission of this radiation towards lower vegetation levels through a multiscattering radiation process.