澤田 義人

<title>Abstract</title>Using satellite remote-sensing is a useful approach for agriculture to monitor plant and soil conditions and provide decision-making support to farmers. Recently, several types of tools and indices by the satellite remote-sensing have been developed for monitoring drought stress, changes in land uses, and crop–soil water relations. Although these techniques are powerful tools, especially in developing countries and regions where precise data of crop evaluation and yield statistics are not accessible, it is quite difficult for beginners to select the most suitable tool or index for their objectives. Major difficulties are in the specificity of the terminology, differences among the sensors (e.g., active vs. passive sensors), interpretation of imaginary data, and multidisciplinary topics. This work offers non-expert readers basic knowledge of remote-sensing use in agriculture, presenting advancements in the field and future insights. We review different sensors that are frequently used, such as optical sensors and synthetic aperture radar, as well as the following different purposes for using remote-sensing in agriculture: drought stress detection, monitoring land use in tropical regions (e.g., deforestation), and estimating water balance evapotranspiration in emerging and developing countries. Additionally, the integrated approach of remote-sensing data into the crop simulation model, which can provide a more holistic view of the plant and field status over cropping season, is described for the field-based studies. <bold>Graphic abstract</bold>

Accurate measurements of above ground biomass are important to evaluate its contribution as a CO2 absorption source. If global canopy height model can be obtained, we can make an appropriate evaluation. This is MOLI's mission. Moreover, MOLI can improve the accuracy of digital terrain model. In this paper, we will report on the development status of MOLI for LIDAR observation from space by mounting on the Japanese Experiment Module with International Space Station.

<p>Regarding to global carbon cycle accurate measurements of forest biomass are important to evaluate its contribution as a CO₂ absorption source. Forest biomass correlates with forest canopy heights, therefore global measurements of canopy heights lead to a better understanding of the global carbon cycle. Space-borne lidar has the unique capability of measuring forest canopy height. A vegetation lidar named MOLI (Multi-footprint Observation Lidar and Imager) has been designed to observe canopy heights more accurately, and MOLI is currently being studied in the Japan Aerospace Exploration Agency. This paper introduces an overview of MOLI and its current status.</p>

Greenhouse Gases Observing SATellite-2 (GOSAT-2) will be launched in fiscal year 2018. GOSAT-2 will be equipped with two Earth-observing instruments: the Thermal and Near-infrared Sensor for carbon Observation Fourier Transform Spectrometer 2 (TANSO-FTS-2) and TANSO-Cloud and Aerosol Imager 2 (CAI-2). CAI-2 can be used to perform cloud discrimination in each band. The cloud discrimination algorithm uses minimum reflectance (Rmin) for comparisons with observed top-of-atmosphere reflectance. The creation of cloud-free Rmin requires 10 CAI or CAI-2 data. Thus, Rmin is created from CAI L1B data for a 30-day period in GOSAT, with a revisit time of 3 days. It is necessary to change the way in which 10 observations are chosen for GOSAT-2, which has a revisit time of 6 days. Additionally, Rmin processing for GOSAT CAI data was updated to version 02.00 in December 2016. Along with this change, the resolution of Rmin changed from 1/30° to 500 m. We examined the impact of changes in Rmin on cloud discrimination results using GOSAT CAI data. In particular, we performed comparisons of: (1) Rmin calculated using different methods to choose the 10 observations and (2) Rmin calculated using different generation procedures and spatial resolutions. The results were as follows: (1) The impact of using different methods to choose the 10 observations on cloud discrimination results was small, except for a few cases, e.g., snow-covered regions and sun-glint regions (2) Cloud discrimination results using Rmin in version 02.00 were better than results obtained using Rmin in the previous version, apart from some special situations. The main causes of this were as follows: (1) The change of used band from band 2 to band 1 for Rmin calculation (2) The change of spatial resolution of Rmin from 1/30° to 500-m.

<p>We developed a prototype system to generate PM2.5 concentration maps using GOSAT/CAI L1B products. The AOT (Aerosol Optical Thickness) retrieving process at 380 nm was reimplemented. We developed a formula to calculate PM2.5 concentrations by comparing satellite images and ground measurement data. Estimated PM2.5 concentrations showed good correlation with ground data (r=0.713 RMSE=22.4 μg/m³). Finally, PM2.5 concentrations maps were generated. In addition, an empirical cloud-screening method using CAI band1 images (SCUV) was also developed.</p>

In the present study, we aimed to map canopy heights in the Brazilian Amazon mainly on the basis of spacebome LiDAR and cloud-free MODIS imagery with a new method (the Self-Organizing Relationships method) for spatial modeling of the LiDAR footprint. To evaluate the general versatility, we compared the created canopy height map with two different canopy height estimates on the basis of our original field study plots (799 plots located in eight study sites) and a previously developed canopy height map. The compared canopy height estimates were obtained by: (1) a stem diameter at breast height (D)- tree height (H) relationship specific to each site on the basis of our original field study, (2) a previously developed D-H model involving environmental and structural factors as explanatory variables (Feldpausch et al., 2011), and (3) a previously developed canopy height map derived from the spacebome LiDAR data with different spatial modeling method and explanatory variables (Simard et al., 2011). As a result, our canopy height map successfully detected a spatial distribution pattern in canopy height estimates based on our original field study data (r=0.845, p = 8.31 x 10(-3)) though our canopy height map showed a poor correlation (r= 0.563, p =0.146) with the canopy height estimate based on a previously developed model by Feldpausch et al. (2011). We also confirmed that the created canopy height map showed a similar pattern with the previously developed canopy height map by Simard et al. (2011). It was concluded that the use of the spaceborne LiDAR data provides a sufficient accuracy in estimating the canopy height at regional scale. (C) 2015 Elsevier B.V. All rights reserved.

The preparation for the launch of the Greenhouse gases Observing SATellite-2 (GOSAT-2) in fiscal 2017 has been progressing. Although the amount of observation data increases according to the changes, such as the increase in the number of bands in GOSAT-2 TANSO-CAI-2, it is not likely that of realization if the floor spaces to set up a ground system for the steady operational processing of the GOSAT-2 data significantly exceed that of GOSAT. To deal with this problem, we evaluated the usability of the graphics prosessing unit (GPU), which was designed for handling multiple tasks such as image processing simultaneously. Meanwhile the processing time is not usually simply inversely proportional to the processing capacity of the central processing unit (CPU) or GPU. It is necessary to compare different CPUs and GPUs in order to estimate the processing time on the basis of the processing capacity. For this reason, we compared the processing times of GOSAT TANSO-CAI L2 cloud flag processing with OpenMP (CPU), OpenACC (GPU), and CUDA (GPU) using three computers: Computer 0, Computer 1, and Computer 2. The results were as follows: 1) On Computer 2, the CPU multi-threaded code with OpenMP using an Intel Core i7-3820 was the fastest (25 msec). The primary reason that GPU multi-threaded code was slower than CPU multi-threaded code was the presence of a performance bottleneck for transferring processing data between the host and the device memory. Outside of the transfer between the host and the device memory, the GPU multi-threaded code with OpenACC or CUDA was 15.5 times faster than the CPU multi-threaded code. 2) In the case of converting double-precision floating-point variables to single-precision floating-point variables, the CPU+GPU hybrid parallel processing with OpenMP and CUDA on Computer 2 was the fastest (20 msec). The importance of CPU+GPU hybrid parallel processing will increase in the future as the data transfer speed between the host and the device memory becomes faster.

Biochar is widely recognized as an efficient tool for carbon sequestration and soil fertility. The understanding of its chemical and physical properties, which are strongly related to the type of the initial material used and pyrolysis conditions, is crucial to identify the most suitable application of biochar in soil. A selection of organic wastes with different characteristics (e.g., rice husk (RH), rice straw (RS), wood chips of apple tree (Malus pumila) (AB), and oak tree (Quercus serrata) (OB)) were pyrolyzed at different temperatures (400, 500, 600, 700, and 800 degrees C) in order to optimize the physicochemical properties of biochar as a soil amendment. Low-temperature pyrolysis produced high biochar yields; in contrast, high-temperature pyrolysis led to biochars with a high C content, large surface area, and high adsorption characteristics. Biochar obtained at 600 degrees C leads to a high recalcitrant character, whereas that obtained at 400 degrees C retains volatile and easily labile compounds. The biochar obtained from rice materials (RH and RS) showed a high yield and unique chemical properties because of the incorporation of silica elements into its chemical structure. The biochar obtained from wood materials (AB and OB) showed high carbon content and a high absorption character.

筆者らは分光反射スペクトルデータのクラスタリングと隠れマルコフモデルを組み合わせることで，多バンドデータで雲除去と時系列モデル化を行う離散的状態空間モデルを開発した．メコン川流域全体を対象としてMODISデータを用いた洪水域の自動監視を行うシステムを構築し，広く情報提供を行っている．また，2011年にはタイ国バンコク周辺で洪水発生し大きな被害があったが，MODISによる冠水地域抽出結果を，より高解像度のセンサーであるASTERやRADARSATのデータを用いて精度評価を行った．その結果，MODIS画素内冠水割合が95%以上の場合の正解率（一致率）はASTERに対しては96.7%，RADARSATでも69.8%であった．RADARSATのデータとの比較では結果のばらつきが大きく，ほぼ完全に検出できた時期もある一方で，雲や欠損画素が連続する場合や植生と冠水域の混在などの要因で検知できなかった場合もあった．

High-accuracy three-dimensional (3D) information of global area is useful in various fields, such as global observations of canopy height, elevation and ice sheet. Especially, there are pressing needs to advance understanding of how changes in the 3D structure of terrestrial vegetation are affecting the global carbon dynamics and their implications for climate change. Thus new space based observations are needed to measure global maps of the 3D structure of vegetation. Japan Aerospace Exploration Agency has started a conceptual study of the spaceborne vegetation LiDAR called MOLI (Multi- Footprint Observation LiDAR and Imager) which will enable us to obtain high-accuracy 3D information of vegetation areas from the globe. To investigate waveforms and analysis procedure, the waveform-simulator for MOLI was developed. Comparing with previous studies about the canopy height estimation from GLAS waveforms, waveform analysis procedure in which waveforms were fitted with a sum of Gaussian functions was studied. The maximum canopy height error was divided into two components the basic error (EB) which was not depending on terrain index (TI), which was the vertical difference between the highest and lowest elevation within a footprint, and the error depending on TI (ETI). The total error (ETotal) could be RMS of the two. We propose ETotal in which EB is 1 m and ETI is 1/3TI as a target observation accuracy of MOLI. According to this error estimation, the observation accuracy of MOLI is 1m at a plane area (TI &amp 0) and 3 m at slope area up to about 20 degree. © 2013 SPIE.

災害発生直後のテキストデータについて解析し,可視化を行うことを目的として,一連の解析手法の開発を行った.単語の出現頻度に基づいた分類を行い,各ノードでの単語の出現頻度(Zスコア)からSOM上でのトピックを決定する方法を開発した.山陰豪雪に関連するツイッターデータの解析では,明確なトピックを決定するのは困難であったが,ツイッターに特有なものとして「情報共有」のトピックが得られた.SOMの分類と隠れマルコフモデルによるモデル化を組み合わせることで,発言内容の短時間のゆらぎも含めた5つのトピックが自動抽出された.豪雪の状況が全国ニュースで取り上げられた時には,それ以降のツイート内容が変わったことも明らかになった.［本要旨はPDFには含まれない］［本要旨はPDFには含まれない］

災害発生直後のテキストデータについて解析し,可視化を行うことを目的として,一連の解析手法の開発を行った.単語の出現頻度に基づいた分類を行い,各ノードでの単語の出現頻度(Zスコア)からSOM上でのトピックを決定する方法を開発した.<br>東日本大震災発生直後の新聞記事の解析では,大きく6つのトピックを抽出でき,事象の推移にしたがって記事数も時間的に変化する様子を捉えることができた.特に,福島第一原発の事故のようにこれまでに類のない事象に関する記事についてもトピックの可視化が可能である結果が得られた.［本要旨はPDFには含まれない］

ブラジル・アマゾン川流域で季節変化により発生する浸水林の正確な把握は,森林バイオマスを推定するうえでも重要である.広域にわたるアマゾンの森林を解析するため,澤田らはTerra/MODISデータから雲の影響を除去する独自のプログラムを用いて土地被覆分類図を作製したが,その精度は検証されていない.本研究では,ALOS/PALSARデータにオブジェクトベース分類手法を適用して,浸水林面積を推定し,それをもとに澤田らのTerra/MODISデータから作成された土地被覆分類プロダクトの精度評価を試みた.［本要旨はPDFには含まれない］

林業の生産性を向上させるための一つの解決策として，効率的に森林の現状を管理することがあげられる．具体的には，単木ごと材として質を調査・管理することで原木コストの削減が見込まれる．そこで，本研究では，新たな森林調査手法として地上 LiDARを利用して森林を面的かつ短時間に計測することで原木コストを削減する方法を提案する．具体的には，地上 LiDARで計測された点群から単木の質に関する任意の高さの樹幹太さを取得する手法を開発するとともに，誰でも結果を理解できるようにDEMと樹幹形状とを可視化して出力する仕組みを構築した．まず，地上 LiDARで計測した点群からDEMを作成した．次に，地上１３. mから１ mごとの樹幹太さを真円を用いて推定した．そして，近似結果を３ Dデータとして可視化した．形状に関する結果は，樹冠下までの樹幹太さに関してほほ点群の形状通りに推定でき，形状の再現は成功した．ただし，樹冠下から樹冠内の樹幹太さの推定は，枝葉の点群の影響により誤差が大きくなっていたことが分かった．しかしながら，樹冠内の樹幹太さの推定誤差を低減する解決策に関する知見は得られた．本研究の結論として，樹冠下から樹冠内の樹幹太さの推定する手法を改良する必要があるが，提案した樹幹太さの推定手法は有効であることが示された．さらに，原木コストを削減するためには，DEMを広範囲に作成できる場所に地上 LiDARを設置することが重要であることが示された．［本要旨はPDFには含まれない］

This paper describes the method and process of developing a forest echo signal simulator to be applied in "iLOVE" : Issjem LiDAR Observation of Vegetation Environment. The goal of this study was to develop an echo signal simulation model and to visualize the generation process of echo signals. The simulator consists of four components: 1) terrain and features 2) sensor configuration 3) echo signal generation and 4) visualization. Terrain and feature data were defined to be full polygon object in 3D space. A laser beam refers to numerous sub laser beams with each sub laser beam featuring specific intensity based on TEM00. The time-series intensity change of sub laser beams was based on Gaussian distribution. At the start of the echo signal generating process, intersections between sub laser beams and target objects were calculated. Then, echo signal of sub laser beams was calculated from the position of intersections, pulse width and specific reflectance of target objects. Finally, an echo signal suitable for footprint size was calculated by synthesizing echo signals of sub laser beams. Meanwhile, intersections were drawn in 3D on the surface of target objects. The results indicated that the simulator was highly useful for understanding the relationship between the echo signal and the structure of target objects, and also for developing algorism for forest applications. ©2012 SPIE.

Background: Evolutionary relations of similar segments shared by different protein folds remain controversial, even though many examples of such segments have been found. To date, several methods such as those based on the results of structure comparisons, sequence-based classifications, and sequence-based profile-profile comparisons have been applied to identify such protein segments that possess local similarities in both sequence and structure across protein folds. However, to capture more precise sequence-structure relations, no method reported to date combines structure-based profiles, and sequence-based profiles based on evolutionary information. The former are generally regarded as representing the amino acid preferences at each position of a specific conformation of protein segment. They might reflect the nature of ancient short peptide ancestors, using the results of structural classifications of protein segments. Results: This report describes the development and use of "Cross Profile Analysis" to compare sequence-based profiles and structure-based profiles based on amino acid occurrences at each position within a protein segment cluster. Using systematic cross profile analysis, we found structural clusters of 9-residue and 15-residue segments showing remarkably strong correlation with particular sequence profiles. These correlations reflect structural similarities among constituent segments of both sequence-based and structure-based profiles. We also report previously undetectable sequence-structure patterns that transcend protein family and fold boundaries, and present results of the conformational analysis of the deduced peptide of a segment cluster. These results suggest the existence of ancient short-peptide ancestors. Conclusions: Cross profile analysis reveals the polyphyletic and convergent evolution of beta-hairpin-like structures, which were verified both experimentally and computationally. The results presented here give us new insights into the evolution of short protein segments.

&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; We developed technologies to collect site environment parameters (ex. surface temperature, period of flooding, and terrain condition) and to create a site environment map that shows the diversity of site environment conditions of Amazon River basin. The filtering method &ldquo;kalmfit&rdquo; and a discrete time-series modeling method were applied to the 8-days composite of MODIS dataset for removing the influences of clouds and other noises on the data set. Data sets consists of NDVI, NDII, day/night brightness temperature and spectral clusters dataset in 2001 to 2009 every 8day intervals. A methodology for classification of a site environment conditions were developed. The terrain data derived from digital terrain model were also introduced and a site environmental map with 500m resolutions was created. [This abstract is not included in the PDF]<br>

This paper describes the development of a novel time series modelling and spectrum anomaly-detection method, which takes into consideration wide-area seasonal changes. By taking advantage of both the high temporal resolution and the wide swath mode of multi-temporal satellite data, such as NOAA/AVHRR, MODIS, and SPOT/vegetation, it is possible to perform high-frequency monitoring of wide-area, land cover changes. However, since the multi-temporal satellite data are influenced by clouds and system noise, in many cases, they must be processed in order to accurately represent the actual surface conditions. We engineered a discrete time-series model using a self-organizing map (SOM) and a hidden Markov Model (HMM) to reduce the influence of clouds in order to improve the accuracy of the products. The spectral information of the pixels was first converted to nominal scale values, and the influence of clouds was eliminated through a time-series modelling using HMM. Since the anomaly-detection method requires a clustering of nominal vectors, dedicated software based on SOM algorithm was also developed. The data for anomaly detection is not dependent on the information of neighbouring pixels, and it is possible to detect an anomaly even if there is only one pixel.

Basic forest information of Siberia in global scale has been corrected as GIS datasets from the HASA, IGBP and other organizations as well as satellite image and field survey data. Thermal data as well as vegetation index is considered useful to evaluate environmental conditions taking into account the impact of global warming in Siberia. The NOAA Pathfinder data from 1981 to 2001 were used and the large fluctuations originated from noises have been removed by either method of IMF and LMF-KF As the land surface temperature (LST) data, the Channel 4 data of NOAA-AVHRR were used. By applying the LMF-KF to NOAA Pathfinder data, we could get cloud-free and noise-free images with 10 days interval for both NDVI and EST. The LST shows higher than station temperature in summer tune and the relation becomes inverted in winter time. The LST data is useful for understanding environmental condition of the terrain. One of such examples is the satellite warm index (the summation of temperature when it is higher than 5 degree C), which is considered useful for zoning the eco-region. The images of various indices of the world were created. The maximum NDVI of each year, for example, is a good indicator for annual changes of vegetation condition as each NDVI shows the seasonal condition of vegetation coverage. The trend of annual maximum EST for 20 years shows the average temperature changes of the surface, which are related to the impact of global environmental changes to the ground. The NPP in Russia in late 1990s was estimated as 7.8 million tC. The NPP in the whole Russia was increasing but it was decreasing in European Russia because of deforestation.

本研究ではメコン川流域全体を対象としてMODISデータを用い，著者が開発した記号列処理による離散的状態空間モデルを利用した異状検知法によって，森林開発地の抽出作業を行った．また，この手法が10日間毎の準リアルタイムでの森林開発地自動抽出にも応用可能となるようにパラメータを設定した．2005年～2007年の3年間108時期について森林開発地として抽出された地点について，雲の無い二時期以上の良好なASTER画像が取得できた164地点の中から21地点を選び出し森林開発地かどうか確認した．その結果，数km以上の大きさの森林開発地が抽出できることが明らかになった．［本要旨はPDFには含まれない］

Integration of knowledge on the sequence-structure correlation of proteins provides a basis for the structural design of artificial novel proteins. As one of strategies, it is effective to consider a short segment, whose size is in between an amino acid and a domain, as a correlation unit for exploring the structure-to-sequence relationship. Here we report the development of a database called ProSeg, which consists of two sub-databases, Segment DB and Cluster DB. Segment DB contains tens of thousands of segments that were prepared by dividing the primary sequences of 370 proteins using a sliding L-residue window (L = 5, 9, 11, 15). These segments were classified into several thousands of clusters according to their three-dimensional structural resemblance. Cluster DB contains much cluster-related information, which includes image, rank, frequency, secondary structure assignment, sequence profile, etc. Users can search for a suitable cluster by inputting an appropriate parameter (i.e., PDB ID, dihedral angles, or DSSP symbols), which identifies the backbone structure of a query segment. Analogous to a language, ProSeg could be regarded as a &apos;structure-sequence dictionary&apos; that contains over 10,000 &apos;protein words&apos;. ProSeg is freely accessible through the Internet (http://riodb.ibase.aist.go.jp/proseg/).

What is the smallest protein? This is actually not such a simple question to answer, because there is no established consensus among scientists as to the definition of a protein. We describe here a designed molecule consisting of only 10 amino acids. Despite its small size, its essential characteristics, revealed by its crystal structure, solution structure, thermal stability, free energy surface, and folding pathway network, are consistent with the properties of natural proteins. The existence of this kind of molecule deepens our understanding of proteins and impels us to define an "ideal protein" without inquiring whether the molecule actually occurs in nature.

The objective of this study was to produce land cover maps for the period between 1982 and 2000 using the Normalized Differential Vegetation Index (NDVI) data from the National Oceanic and Atmospheric Administration (NOAA) Pathfinder Advanced Very High Resolution Radiometer (AVHRR) 8-km land dataset for monitoring forest cover changes in the Mekong Riverbasin. Time-series analysis, named Local Maximum Fitting with Kalman Filter (LMF-KF), was applied to the NDVI data to remove noise such as clouds and produce cloudfree images at 10-day intervals. Multitemporal metrics such as annual mean, maximum, minimum, standard deviation, and range were calculated using LMF-KF-processed NDVI data. Classification was performed to produce land cover maps based on signatures from the multitemporal metrics of the NDVI time-series data. The GLC2000 land cover database produced by the joint Research Center of the European Commission was used as training data for the first classification, which is for the year 2000. Then, the results of the first classification were used as training data for the next classification, which is the previous year. Consequently, classification results for the period between 1982 and 2000 were obtained. It was found that the total forested area was stable in the classification images, whereas the proportion of deciduous forest area had increased.

時系列NDVIデータを樹形モデルに適用して熱帯季節林の分類を行った。対象地はカンボジア全土とした。分類カテゴリは,常緑林,混交落葉林,落葉林,農地を設定した。使用したデータは,既存の2つの地図と2000年1月から12月に取得された36シーンのSPOT-VEGETATION NDVIデータである。この時系列NDVIデータに対し,時系列方向の局所最大値フィルタと,主成分分析後に低次主成分だけを用いた逆変換によって画像を再生する,ノイズ除去処理を施した後,7つの季節変動特徴量を算出した。これらのデータから緯度経度が0.04度間隔のグリッドを用いてシステマティックにモデル構築用の教師データと評価用のテストデータを抽出し,2つの土地被覆情報と7つの季節変動特徴量をフィールドに持つデータセットを作成した。このデークセットから土地被覆情報を反応因子に,季節変動特徴量を予測変量として既存の地図それぞれに対し樹形モデルを構築し,土地被覆分類を行った。その結果,2つの土地被覆分類とも総合精度で70%前後の結果が得られた。また樹形モデルで,実際に使用された季節変動特徴量は,年平均NDVIとNDVIが0.7を越えるピクセル数で示される生育期間だけで,比較的少ない変数で分類が可能であることが示された。

The local structures of protein segments were classified and their distribution was analyzed to explore the structural diversity of proteins. Representative proteins were divided into short segments using a sliding L-residue window. Each set of local structures consisting of consecutive 1-31 amino acids was classified using a single-pass clustering method. The results demonstrate that the local structures of proteins are very unevenly distributed in the protein universe. The distribution of local structures of relatively long segments shows a power-law behavior that is formulated well by Zipf's law, implying that a protein structure possesses recursive and fractal characteristics. The degree of effective conformational freedom per residue as well as the structure entropy per residue decreases gradually with an increasing value of L and then converges to constant values. This suggests that the number of protein conformations resides within the range between 1.2(L) and 1.5(L) and that 10- to 20-residue segments are already protein-like in terms of their structural diversity.

We have designed a peptide termed chignolin, consisting of only 10 amino acid residues (GYDPETGTWG), on the basis of statistics derived from more than 10,000 protein segments. The peptide folds into a unique structure in water and shows a cooperative thermal transition, both of which may be hallmarks of a protein. Also, the experimentally determined beta-hairpin structure was very close to what we had targeted. The performance of the short peptide not only implies that the methodology employed here can contribute toward development of novel techniques for protein design, but it also yields insights into the raison d'etre of an autonomous element involved in a natural protein. This is of interest for the pursuit of folding mechanisms and evolutionary processes of proteins.

Leaf Water Content Index (LWCI) was proposed by Hunt et al (1987). At the beginning we tried and succeeded to develop this index for the practical application to the satellite remote sensing data such as Landsat TM. Next we performed vegetation monitoring using LWCI by SPOT/Vegetation and we got the same results. LWCI is not susceptible to influences from the atmospheric noise such as the haze and smoke, which are caused very often by fires or climatic conditions in the tropics, because it utilizes longer wavelength bands, SWIR (1.58-1.75mum) and NIR (0.79-0.89mum) than NDVI. This time we applied LWCI to the one-year time series of SPOT/Vegetation 10 days composite data that were processed in advance to exclude the influences of clouds (Sawada, 2001). We tried to compare the seasonal change profiles of LWCI between the tropical agricultural lands (Thailand) and the temperate agricultural lands (Japan) in addition to the forest zone. The seasonal change profiles of NDVI were created simultaneously and also compared. As a result, despite the influence of the snow in the case of Japanese winter season, both tropical and temperate evergreen forests in non-winter season showed a relatively similar trend. As for the temperate deciduous forest, such evident time lag that is seen in the tropical deciduous forest was not observed. It was found for the first time that the seasonal change of LWCI could be observed even in: the agricultural areas (paddy fields, upland farming fields, grassland), however in both; tropical and temperate zones the time lag between LWCI and NDVI profile was hardly observed This fact seems to indicate that in the plant phenology of the temperate zone like Japan the moisture. condition does not play more important role than that of the tropical zone.. Rather the cumulative temperature or photoperiod affects the plank phenology.

We have studied the reaction of allylsilanes with aldehydes by applying the ab initio MO theory. It has been shown that the reaction takes place via a transition state involving pentacoordinated silicon species, The oxygen of aldehyde attacks an apical site of the silicon center, while the allyl group departs directly from an equatorial site without causing a pseudorotation. The calculation has shown that the reaction of an allylsilacyclobutane model with formaldehyde has a lower activation barrier than the reaction of allylsilane or methyl-substituted allylsilanes. The barrier height is shown to be correlated well with the angle of coordination of substituents on the silicon center. The reactivity of allylsilanes against nucleophiles is discussed by evaluating the local acidic strength of the reaction site.

The photoreaction of a styrene/4-tributylstannylmethylstyrene (4:1) copolymer with di- and tetra-cyanoaromatic compounds in benzene-acetonitrile (1:1) gave polymers having cyanoaromatic functions in the side chain. These polymers were soluble in benzene and served as effective and recoverable sensitizers for three different types of photoinduced electron-transfer mediated organic photoreactions.