福建省近500a臺(tái)風(fēng)災(zāi)害多尺度時(shí)空數(shù)據(jù)庫(kù)構(gòu)建及動(dòng)態(tài)分析
本文選題:臺(tái)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(guó)是世界上少數(shù)幾個(gè)受臺(tái)風(fēng)影響最嚴(yán)重的國(guó)家之一,每年夏、秋季節(jié)臺(tái)風(fēng)都會(huì)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(tái)風(fēng)源地(西北太平洋),是臺(tái)風(fēng)災(zāi)害最嚴(yán)重的省份之一。登陸福建的臺(tái)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(tái)風(fēng)的危害性日趨嚴(yán)峻。目前,對(duì)臺(tái)風(fēng)災(zāi)害時(shí)空格局的分析主要基于臺(tái)風(fēng)發(fā)生頻數(shù),尚局限于對(duì)致災(zāi)因子的時(shí)空分布的描述,對(duì)因臺(tái)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(tái)風(fēng)災(zāi)害資料及災(zāi)損數(shù)據(jù)建立歷史臺(tái)風(fēng)災(zāi)害時(shí)空數(shù)據(jù)庫(kù),并進(jìn)行動(dòng)態(tài)可視化表達(dá),對(duì)歷史臺(tái)風(fēng)災(zāi)害時(shí)空格局進(jìn)行分析,揭示了福建省歷史臺(tái)風(fēng)災(zāi)害的時(shí)空變化規(guī)律,對(duì)災(zāi)害風(fēng)險(xiǎn)評(píng)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(guó)歷史地理信息系統(tǒng)”項(xiàng)目中的福建省縣級(jí)、府級(jí)行政區(qū)劃沿革空間數(shù)據(jù)庫(kù),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(guó)氣象災(zāi)害大典(福建卷)》等歷史臺(tái)風(fēng)資料,構(gòu)建福建省近500年歷史臺(tái)風(fēng)災(zāi)害時(shí)空數(shù)據(jù)庫(kù),以實(shí)現(xiàn)對(duì)歷史臺(tái)風(fēng)災(zāi)害的多尺度時(shí)空格局分析。由于臺(tái)風(fēng)災(zāi)害評(píng)估涉及面廣,加之時(shí)間尺度大,災(zāi)情資料的多樣性,本文將結(jié)合實(shí)際分時(shí)段選擇不同災(zāi)情因子對(duì)歷史臺(tái)風(fēng)災(zāi)害進(jìn)行數(shù)據(jù)庫(kù)的構(gòu)建及動(dòng)態(tài)分析。建庫(kù)前首先對(duì)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(shí)間以及統(tǒng)計(jì)數(shù)據(jù)的歸一化。1900-1950年臺(tái)風(fēng)災(zāi)害,引入“災(zāi)度”的概念,制定分級(jí)標(biāo)準(zhǔn)并劃分災(zāi)情等級(jí),并將分級(jí)結(jié)果以視頻的形式進(jìn)行動(dòng)態(tài)可視化表達(dá);1951~2000年臺(tái)風(fēng)災(zāi)害,通過(guò)選擇指標(biāo)及評(píng)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(kāi)發(fā)組件ArcGIS Engine結(jié)合Visual Studio2005平臺(tái)設(shè)計(jì)災(zāi)情可視化界面。以上述兩種方式對(duì)福建省歷史臺(tái)風(fēng)災(zāi)害時(shí)空格局進(jìn)行動(dòng)態(tài)分析,同時(shí)從地市級(jí)、縣級(jí)兩種空間單元分時(shí)段對(duì)福建省臺(tái)風(fēng)災(zāi)害發(fā)生頻次、災(zāi)情指數(shù)、災(zāi)情等級(jí)等因子進(jìn)行分析。結(jié)果表明:近500年福建臺(tái)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(shì),但局部地區(qū)受災(zāi)程度和受災(zāi)頻數(shù)并無(wú)相關(guān)性。福建省歷史臺(tái)風(fēng)災(zāi)害數(shù)據(jù)庫(kù)的構(gòu)建為時(shí)空格局分析,災(zāi)害風(fēng)險(xiǎn)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(jí)別】:碩士
【學(xué)位授予年份】:2013
【分類號(hào)】:P208;P444
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 楊慧娟;李寧;雷樝;;我國(guó)沿海地區(qū)近54a臺(tái)風(fēng)災(zāi)害風(fēng)險(xiǎn)特征分析[J];氣象科學(xué);2007年04期
2 梁必騏,樊琦,楊潔,王同美;熱帶氣旋災(zāi)害的模糊數(shù)學(xué)評(píng)價(jià)[J];熱帶氣象學(xué)報(bào);1999年04期
3 何敏,宋文玲,陳興芳;厄爾尼諾和反厄爾尼諾事件與西北太平洋臺(tái)風(fēng)活動(dòng)[J];熱帶氣象學(xué)報(bào);1999年01期
4 鄭穎青;吳啟樹(shù);林笑茹;陳瑞閃;;近106a來(lái)登陸福建臺(tái)風(fēng)的統(tǒng)計(jì)分析[J];臺(tái)灣海峽;2006年04期
5 舒紅,陳軍,杜道生,周勇前;面向?qū)ο蟮臅r(shí)空數(shù)據(jù)模型[J];武漢測(cè)繪科技大學(xué)學(xué)報(bào);1997年03期
6 張聰;張慧;;信息可視化研究[J];武漢工業(yè)學(xué)院學(xué)報(bào);2006年03期
7 雷小途,陳聯(lián)壽;西北太平洋熱帶氣旋活動(dòng)的緯度分布特征[J];應(yīng)用氣象學(xué)報(bào);2002年02期
8 李玉泉;徐學(xué)軍;曾致遠(yuǎn);鄢鐵平;趙愛(ài)軍;;基于Geodatabase數(shù)據(jù)模型設(shè)計(jì)實(shí)現(xiàn)水土保持規(guī)劃數(shù)據(jù)庫(kù)[J];中國(guó)水土保持;2007年06期
9 馮利華;;災(zāi)害損失的定量計(jì)算[J];災(zāi)害學(xué);1993年02期
10 陳香;沈金瑞;陳靜;;災(zāi)損度指數(shù)法在災(zāi)害經(jīng)濟(jì)損失評(píng)估中的應(yīng)用——以福建臺(tái)風(fēng)災(zāi)害經(jīng)濟(jì)損失趨勢(shì)分析為例[J];災(zāi)害學(xué);2007年02期
,本文編號(hào):1958530
本文鏈接:http://sikaile.net/kejilunwen/dizhicehuilunwen/1958530.html