本文選題：臺風(fēng)災(zāi)害 + 福建省　； 參考：《福建師范大學(xué)》2013年碩士論文

【摘要】：我國是世界上少數(shù)幾個受臺風(fēng)影響最嚴(yán)重的國家之一,每年夏、秋季節(jié)臺風(fēng)都會給東南沿海地區(qū)人民造成重大損失。由于福建省靠近世界上最大的臺風(fēng)源地(西北太平洋),是臺風(fēng)災(zāi)害最嚴(yán)重的省份之一。登陸福建的臺風(fēng),具有暴雨強(qiáng)、路徑復(fù)雜、結(jié)構(gòu)和強(qiáng)度變化大、災(zāi)害嚴(yán)重等特點(diǎn),是福建省最主要的氣象災(zāi)害。隨著福建省沿海地區(qū)經(jīng)濟(jì)和人口的快速發(fā)展,臺風(fēng)的危害性日趨嚴(yán)峻。目前,對臺風(fēng)災(zāi)害時空格局的分析主要基于臺風(fēng)發(fā)生頻數(shù),尚局限于對致災(zāi)因子的時空分布的描述,對因臺風(fēng)災(zāi)害造成損失的格局分析研究還比較欠缺。如何利用歷史臺風(fēng)災(zāi)害資料及災(zāi)損數(shù)據(jù)建立歷史臺風(fēng)災(zāi)害時空數(shù)據(jù)庫,并進(jìn)行動態(tài)可視化表達(dá),對歷史臺風(fēng)災(zāi)害時空格局進(jìn)行分析,揭示了福建省歷史臺風(fēng)災(zāi)害的時空變化規(guī)律,對災(zāi)害風(fēng)險評估與防范具有重大意義。 本文采用地理信息系統(tǒng)(Geographical Information System, GIS)技術(shù),利用上海復(fù)旦大學(xué)“中國歷史地理信息系統(tǒng)”項(xiàng)目中的福建省縣級、府級行政區(qū)劃沿革空間數(shù)據(jù)庫,以及《福建省歷史上重大自然災(zāi)害年表》、《福建省歷史上自然災(zāi)害記錄》(修訂版)、《中國氣象災(zāi)害大典(福建卷)》等歷史臺風(fēng)資料,構(gòu)建福建省近500年歷史臺風(fēng)災(zāi)害時空數(shù)據(jù)庫,以實(shí)現(xiàn)對歷史臺風(fēng)災(zāi)害的多尺度時空格局分析。由于臺風(fēng)災(zāi)害評估涉及面廣,加之時間尺度大,災(zāi)情資料的多樣性,本文將結(jié)合實(shí)際分時段選擇不同災(zāi)情因子對歷史臺風(fēng)災(zāi)害進(jìn)行數(shù)據(jù)庫的構(gòu)建及動態(tài)分析。建庫前首先對歷史資料、統(tǒng)計(jì)數(shù)據(jù)、地理信息數(shù)據(jù)等進(jìn)行歸一化處理,例如,歷史地名、受災(zāi)時間以及統(tǒng)計(jì)數(shù)據(jù)的歸一化。1900-1950年臺風(fēng)災(zāi)害,引入“災(zāi)度”的概念,制定分級標(biāo)準(zhǔn)并劃分災(zāi)情等級,并將分級結(jié)果以視頻的形式進(jìn)行動態(tài)可視化表達(dá)；1951～2000年臺風(fēng)災(zāi)害,通過選擇指標(biāo)及評估模型的方式,分年度、分地區(qū)計(jì)算“災(zāi)情指數(shù)”,并結(jié)合二次開發(fā)組件ArcGIS Engine結(jié)合Visual Studio2005平臺設(shè)計(jì)災(zāi)情可視化界面。以上述兩種方式對福建省歷史臺風(fēng)災(zāi)害時空格局進(jìn)行動態(tài)分析,同時從地市級、縣級兩種空間單元分時段對福建省臺風(fēng)災(zāi)害發(fā)生頻次、災(zāi)情指數(shù)、災(zāi)情等級等因子進(jìn)行分析。結(jié)果表明：近500年福建臺風(fēng)災(zāi)害多發(fā)生于6-10月份,受災(zāi)程度深、受災(zāi)頻次高的地區(qū)均集中在漳州市、莆田市、寧德市、福州市、廈門市各沿海地市,受災(zāi)頻數(shù)由沿海向陸地大體上呈遞減的趨勢,但局部地區(qū)受災(zāi)程度和受災(zāi)頻數(shù)并無相關(guān)性。福建省歷史臺風(fēng)災(zāi)害數(shù)據(jù)庫的構(gòu)建為時空格局分析,災(zāi)害風(fēng)險分析及防范提供了重要科學(xué)依據(jù)。
[Abstract]:China is one of the few countries most seriously affected by typhoons in the world. Every summer and autumn typhoons cause great losses to the people in southeast coastal areas. Fujian Province is one of the most seriously affected provinces because of its proximity to the largest typhoon source in the world, the Northwest Pacific Ocean. Typhoon landing in Fujian is the most important meteorological disaster in Fujian province because of its strong rainstorm, complicated path, large change in structure and intensity, serious disaster, and so on. With the rapid development of economy and population in the coastal area of Fujian Province, the harmfulness of typhoon is becoming more and more serious. At present, the analysis of the temporal and spatial pattern of typhoon disaster is mainly based on the frequency of typhoon occurrence, but it is limited to the description of the temporal and spatial distribution of the disaster factors, and the analysis and research on the loss pattern caused by the typhoon disaster is still lacking. How to make use of the historical typhoon disaster data and the disaster damage data to establish the historical typhoon disaster time and space database, and carry on the dynamic visualization expression, carries on the analysis to the historical typhoon disaster time and space pattern. The temporal and spatial variation of historical typhoon disasters in Fujian Province is revealed, which is of great significance for disaster risk assessment and prevention. In this paper, geographical Information System, GIS) technology is adopted, and the spatial database of the evolution of administrative divisions at county and prefectural level in Fujian Province is used in the project of "Chinese Historical Geographic Information system" of Shanghai Fudan University. And historical typhoon data such as "chronology of Major Natural disasters in the History of Fujian Province", "record of Natural disasters in the History of Fujian Province" (revised edition), "China Meteorological disaster Dictionary (Fujian Volume)", and other historical typhoon data, to construct temporal and spatial database of historical typhoon disasters in Fujian Province in the past 500 years. In order to realize the multi-scale temporal and spatial pattern analysis of historical typhoon disaster. Due to the wide range of typhoon disaster assessment, the large time scale and the diversity of disaster data, this paper will select different disaster factors to construct and dynamically analyze the historical typhoon disaster database. The historical data, statistical data and geographic information data were normalized before the establishment of the database. For example, the concept of "disaster degree" was introduced into the normalization of historical place names, disaster time and statistical data. The classification standard was established and the disaster level was classified, and the classification results were visualized in the form of video to express the typhoon disaster from 1951 to 2000. By selecting the index and evaluating model, the disaster index was calculated year by year, and the disaster index was calculated by region. Combined with secondary development component ArcGIS Engine and Visual Studio2005 platform to design a visual disaster interface. The temporal and spatial patterns of historical typhoon disasters in Fujian Province are analyzed dynamically by the two methods mentioned above. At the same time, the occurrence frequency, disaster index and disaster grade of typhoon disasters in Fujian Province are analyzed from two spatial units at the city level and the county level. The results show that in recent 500 years, most of the typhoon disasters in Fujian occurred in June and October, and the most affected areas were concentrated in Zhangzhou City, Putian City, Ningde City, Fuzhou City, Xiamen City, and the coastal cities of Xiamen City, such as Zhangzhou City, Putian City, Fuzhou City and Xiamen City. The frequency of disaster is decreasing from coastal to land, but there is no correlation between the degree of disaster and the frequency of disaster in local area. The construction of historical typhoon disaster database in Fujian Province provides an important scientific basis for the analysis of temporal and spatial patterns, disaster risk analysis and prevention.
【學(xué)位授予單位】：福建師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：P208;P444

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本文編號：1958530