本稿では,沖縄県竹富島において島を代表する存在である「赤瓦の町並み」が,どのように保存され今のような姿に至ったか,また,「赤瓦の町並み」が町並み保存運動の中で,伝統的建造物群保存地区という文化財としてどのように再生されていったか,伝統文化の創造という観点から考察する.町並み保存のプロセスを検討していくことによって,「伝統的」であると見なされている町並みが本来はいかなるものであるのか,さらに,「伝統的」であるとはいかなることなのかが,明らかになるのである.
本研究の視点は,文化と真正性,伝統文化の創造,観光と伝統をめぐる諸研究と共通するものであり,本研究で取り上げた文化財として位置づけられている伝統的町並みは,研究者・行政・住民の三者の思惑が絡み合ったところに生じたもので,近年注目されっっある「ふるさと」の文化,地域の伝統文化を考える上で,格好の素材でもある.

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第二次世界大戦後の1946年から1995年までの50年間に日本本土に上陸して被害を与えた113の台風を対象とし,中心気圧深度,最大円形等圧線半径,時刻,地域,年代などを独立変数とする被害算定式を導き,時刻などの定性的要因が被害規模に与える影響度を求めた.ついで,単位台風勢力あたり被害高(被害度)の経年変化の趨勢から,戦後における災害環境の変化,防災対策の効果などについて考察した.深夜上陸台風は, 1940～50年代には朝・昼・夕の時間帯に上陸した台風に比べ5倍程度の死者をもたらしていたが,近年ではこの時刻差は非常に小さくなってきている.人的被害度は,防災対策の大きな進展が始まる以前の1960年ごろを境に急減し,その後はわずかな低下にとどまっている.一方,家屋損壊被害度は一貫した低下の趨勢を示す.家屋浸水被害度は低湿地の市街地化の進展などを反映して,長期間ほぼ一定値を保った.金額表示の公共土木施設被害度は1970～80年代に急増したが,これは高度成長期における公共投資額の著しい増大に並行した推移を示す.

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The recreational trip behavior pattern at destinations correlates with the “distance” from the departure point of the trip. This is regarded as an empirical model of spatial behavior in the literature on tourism (Mercer, 1970; Plog, 1973; Miossec, 1977; Pearce, 1981). According to Plog (1973), tourist behavior at nearer destinations is qualified as “psychocentric, ” and behavior at more distant destinations as “allocentric.” This model certainly represents the average and general tendency of tourist behavior, especially in Japan (Takinami, 1994).
If the model is perfect, there should be no exceptions. But in real situations, we observe many exceptional behaviors inconsistent with the model. What elements are related to these unexpected behaviors or behaviors that deviate from the model? Pred (1967) and Miossec (1977) insisted that the deviation can be explained by the actor's insufficient information level and his/her low ability to use information. This paper seeks to examine this interesting hypothesis. The data to be analyzed are trip matrix data collected by the author in an elementary school in Yokohama. The matrix has 338 trips in the row, and 7 tourist/11 behavior categories in the column.
First, I quantified every behavior category by putting them on the axis of “distance” (Takinami, 1994). This quantification was executed in order to maintain the prevalent feature of the tourist behavior model: the behavior correlates with the trip “distance.”
Second, the coordinate system has the two axes of the ordered destination “distance” and the quantified composite behavior pattern. The lattar variable was prepared by compounding all possible quantified behavior categories responding to a particular trip. In this coordinate system, all trips are plotted, and the model of tourist behavior is shown by the regression line related to all there trips (Fig. 1).
Third, based on the measurement of the differences between the regression line and several trip groups (one trip group shows those trips responding to one tourist/behavior category in the figure), the following results were obtained. Proximity to the model or regression line is provided by categories such as ‹higher frequency of travel›, ‹more information about tourism regions›, ‹higher information use ability› and ‹higher economic ability to travel›. Deviation from the model is given by categories such as complete dependence on tourist agency>, ‹sightseeing› and ‹fashion-oriented tourists›.
In conclusion, it is noted that the difference between the model pattern and the deviation pattern is sufficiently explained by the elements associated with tourism information: the information level, information use ability and use of a tourist agency, suggesting lower planning ability. Such findings exemplify, to some extent, the validity of Pred's original behavioral matrix.

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