本文選題：城市洪澇 + 大數(shù)據(jù)��； 參考：《華中科技大學(xué)》2015年碩士論文

【摘要】：近年來極端天氣增多,暴雨天氣頻繁使得城市的暴雨洪澇災(zāi)害風(fēng)險(xiǎn)陡增。而短時(shí)期內(nèi),城市的排水設(shè)施建設(shè)又不可能有明顯的改善,城市洪澇災(zāi)害的分析預(yù)警就變得尤為重要。但是,現(xiàn)有的城市洪澇分析預(yù)警系統(tǒng)還十分不完善,甚至有許多城市根本沒有城市洪澇分析預(yù)警系統(tǒng),并且傳統(tǒng)的模型也有很多缺陷和不足。因此,城市洪澇災(zāi)害的分析預(yù)警亟需一個(gè)新的解決方案。針對(duì)日趨嚴(yán)峻的城市洪澇災(zāi)害現(xiàn)象,本論文對(duì)當(dāng)今新興的大數(shù)據(jù)技術(shù)在城市洪澇分析預(yù)警中的應(yīng)用進(jìn)行了研究,對(duì)適合進(jìn)行大數(shù)據(jù)分布式運(yùn)算的城市洪澇模型和算法進(jìn)行了探索,確定了城市洪澇大數(shù)據(jù)分析模型的框架。并且對(duì)城市洪澇大數(shù)據(jù)分析模型進(jìn)行了Hadoop的MapReduce模型編程實(shí)現(xiàn),還根據(jù)模型所涉及到的數(shù)據(jù)設(shè)計(jì)了Hbase非關(guān)系型數(shù)據(jù)庫(kù)。在Hbase數(shù)據(jù)庫(kù)的基礎(chǔ)上,以城市洪澇分析大數(shù)據(jù)分析模型為核心設(shè)計(jì)了一個(gè)城市洪澇災(zāi)害預(yù)警平臺(tái)的原型系統(tǒng)。本論文對(duì)平臺(tái)的拓?fù)浣Y(jié)構(gòu),功能架構(gòu)以及數(shù)據(jù)流程等進(jìn)行了詳細(xì)的設(shè)計(jì),并在平臺(tái)內(nèi)集成了物聯(lián)網(wǎng)應(yīng)用平臺(tái)用于實(shí)現(xiàn)漬水點(diǎn)的實(shí)時(shí)信息監(jiān)測(cè)。平臺(tái)還結(jié)合Google Map二次開發(fā)對(duì)平臺(tái)的模型處理結(jié)果進(jìn)行可視化顯示。平臺(tái)可根據(jù)降雨積水和空間地理信息等數(shù)據(jù)通過大數(shù)據(jù)技術(shù)建立的城市洪澇模型進(jìn)行分布式并行處理,對(duì)城市洪澇漬水區(qū)域的積水情況進(jìn)行分析預(yù)警,以便于能夠在城市內(nèi)澇發(fā)生時(shí),提前做出應(yīng)對(duì)措施,減小因城市內(nèi)澇災(zāi)害帶來的損失,為水利相關(guān)部門制定決策以及出行人群提供參考依據(jù)和建議。論文的最后還以武漢市部分區(qū)域?yàn)槔龑?duì)平臺(tái)的可行性進(jìn)行了驗(yàn)證并對(duì)比分析了結(jié)果。采用新興的大數(shù)據(jù)以及物聯(lián)網(wǎng)等先進(jìn)技術(shù)對(duì)城市洪澇災(zāi)害的分析預(yù)警將會(huì)帶來巨大的變革。大數(shù)據(jù)技術(shù)的應(yīng)用弱化了過程,直接分析數(shù)據(jù)與結(jié)果之間的聯(lián)系,打破了傳統(tǒng)模型固定模式的思維定式。并且大數(shù)據(jù)技術(shù)在城市洪澇模型中的應(yīng)用使得計(jì)算更加高效,存儲(chǔ)更加穩(wěn)定,可以適應(yīng)海量數(shù)據(jù)的存儲(chǔ)和處理,突破了數(shù)據(jù)量限制所造成的技術(shù)瓶頸。
[Abstract]:In recent years, the risk of urban torrential rain and waterlogging has increased sharply due to the increase of extreme weather and frequent rainstorm weather. However, in a short period of time, the construction of urban drainage facilities can not be improved obviously, and the analysis and warning of urban flood disaster becomes particularly important. However, the existing urban flood analysis early warning system is still very imperfect, even many cities do not even have urban flood analysis early warning system, and the traditional model also has a lot of defects and deficiencies. Therefore, the analysis and warning of urban flood disaster need a new solution. In view of the increasingly severe phenomenon of urban flood and waterlogging, this paper studies the application of the emerging big data technology in urban flood analysis and early warning. The urban flood model and algorithm suitable for big data distributed operation are explored, and the framework of urban flood big data analysis model is established. The big data analysis model of urban flood is programmed by Hadoop MapReduce model, and the Hbase non-relational database is designed according to the data involved in the model. Based on the Hbase database, a prototype system of urban flood disaster warning platform is designed based on the urban flood analysis big data analysis model. In this paper, the topology, function structure and data flow of the platform are designed in detail, and the Internet of things application platform is integrated into the platform to realize the real-time information monitoring of waterlogging points. The platform also visualizes the model processing results of the platform in combination with Google Map secondary development. Based on the data of rainfall water accumulation and spatial geographic information, the platform can be used to analyze and warn the waterlogging situation in urban waterlogging areas through distributed parallel processing of urban flood and waterlogging model established by big data technology. In order to reduce the loss caused by urban waterlogging and provide reference and suggestions for water conservancy departments to make decisions and travel people, it is convenient to make countermeasures in advance when urban waterlogging occurs, and to reduce the losses caused by urban waterlogging disasters. Finally, the feasibility of the platform is verified and the results are compared and analyzed by taking some areas of Wuhan as an example. The application of advanced technologies such as big data and Internet of things to the analysis and early warning of urban flood disaster will bring great changes. The application of big data technology weakens the process and directly analyzes the relationship between data and results. And the application of big data technology in urban flood model makes the calculation more efficient and the storage more stable. It can adapt to the storage and processing of massive data and break through the technical bottleneck caused by the limitation of data volume.
【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TP311.13;TU998.4

【相似文獻(xiàn)】

相關(guān)期刊論文 前10條

1 ;城市洪澇災(zāi)害模擬及防治技術(shù)[J];中國(guó)防汛抗旱;2009年06期

2 ;劉樹坤:強(qiáng)化城市洪澇災(zāi)害風(fēng)險(xiǎn)管理 建設(shè)不怕水的城市[J];中國(guó)水利;2010年17期

3 曹玉堂,尤亞輝;漯河市城市洪澇災(zāi)害與對(duì)策[J];治淮;2000年03期

4 張忠訓(xùn);徐剛;張躍華;;氣候變化下重慶城市洪澇災(zāi)害研究[J];重慶三峽學(xué)院學(xué)報(bào);2011年05期

5 王毅;;北京城市洪澇災(zāi)害的主因和對(duì)策建議[J];中國(guó)防汛抗旱;2011年06期

6 和菊芳;;云南麗江城市洪澇災(zāi)害成因特點(diǎn)及對(duì)策淺析[J];人民長(zhǎng)江;2012年S1期

7 孫相海;樊秀平;;漯河市城市洪澇災(zāi)害與對(duì)策[J];河南水利;2004年02期

8 蔡開璽;;南京市消納城市洪澇災(zāi)害的多元化途徑[J];陜西水利;2012年03期

9 王超,丁向陽(yáng);河南省城市洪澇災(zāi)害[J];中國(guó)減災(zāi);1998年03期

10 高長(zhǎng)亮,劉艷明;棗莊城市洪澇災(zāi)害及對(duì)策[J];治淮;1999年11期

相關(guān)會(huì)議論文 前3條

1 趙太鵬;;蚌埠市城市洪澇災(zāi)害成因及其防治對(duì)策[A];第一屆全國(guó)城市防洪學(xué)術(shù)會(huì)議論文集[C];1992年

2 李漢浸;王運(yùn)行;張相梅;王建英;李麗平;高志軍;馮昌運(yùn);;城市洪澇災(zāi)害對(duì)濮陽(yáng)經(jīng)濟(jì)影響的預(yù)評(píng)估模式探究[A];中國(guó)氣象學(xué)會(huì)2008年年會(huì)極端天氣氣候事件與應(yīng)急氣象服務(wù)分會(huì)場(chǎng)論文集[C];2008年

3 呂蘭軍;盧兵;;水文在城市洪澇災(zāi)害防治中的作用與思考[A];中國(guó)水利學(xué)會(huì)2013學(xué)術(shù)年會(huì)論文集——S3防汛抗旱減災(zāi)[C];2013年

相關(guān)重要報(bào)紙文章 前3條

1 曹軒;防范城市洪澇災(zāi)害[N];吉林日?qǐng)?bào);2008年

2 何紹輝;多管齊下治理城市洪澇災(zāi)害[N];中國(guó)水利報(bào);2010年

3 中國(guó)水利水電科學(xué)研究院 劉樹坤;加強(qiáng)城市洪澇災(zāi)害的應(yīng)對(duì)能力[N];中國(guó)水利報(bào);2008年

相關(guān)碩士學(xué)位論文 前6條

1 劉雄;大數(shù)據(jù)技術(shù)在城市洪澇災(zāi)害分析預(yù)警中的應(yīng)用研究[D];華中科技大學(xué);2015年

2 李宇;山地城市洪澇災(zāi)害風(fēng)險(xiǎn)評(píng)估[D];重慶師范大學(xué);2013年

3 黃春豹;論我國(guó)城市洪澇災(zāi)害應(yīng)急管理[D];吉林大學(xué);2013年

4 盧悉早;城市洪澇災(zāi)害風(fēng)險(xiǎn)研究[D];武漢理工大學(xué);2005年

5 尚志海;當(dāng)代全球變化下城市洪澇災(zāi)害的形成機(jī)制與風(fēng)險(xiǎn)管理研究[D];華南師范大學(xué);2005年

6 項(xiàng)彥生;基于GIS的城市洪澇災(zāi)害評(píng)估及地理數(shù)據(jù)庫(kù)的建立[D];汕頭大學(xué);2004年

，

本文編號(hào)：2087626