本文關(guān)鍵詞： 血吸蟲(chóng)病 鄱陽(yáng)湖 洲灘 釘螺 遙感 決策樹(shù) 特征提取 BP神經(jīng)網(wǎng)絡(luò) 智能體 分布式計(jì)算 Swarm Java3D VRML　出處：《中國(guó)科學(xué)院研究生院（遙感應(yīng)用研究所）》2006年博士論文　論文類(lèi)型：學(xué)位論文

【摘要】：隨著空間信息技術(shù)的更新和發(fā)展，其在公共衛(wèi)生領(lǐng)域的應(yīng)用也更加深入和廣泛。遙感能夠快速、全面地探索、發(fā)現(xiàn)、監(jiān)測(cè)與人類(lèi)健康相關(guān)的環(huán)境因素，地理信息系統(tǒng)為傳染病相關(guān)流行因素?cái)?shù)據(jù)的管理和分析提供了快速、先進(jìn)、可靠的技術(shù)手段，結(jié)合多維信息可視化、計(jì)算機(jī)模擬等數(shù)據(jù)分析與表達(dá)方法不僅能動(dòng)態(tài)分析傳染病的時(shí)間與空間分布特征，而且可以使我們從全新的角度和方式來(lái)研究和認(rèn)識(shí)傳染病，從而為傳染病時(shí)空傳播和流行規(guī)律的研究提供新的思路和方法。 血吸蟲(chóng)病是一種具有地方性和自然疫源性的人畜共患傳染病，在我國(guó)存在歷史悠久，分布面積廣泛，傳播過(guò)程又涉及眾多的自然因素和社會(huì)因素，，從而給血吸蟲(chóng)病防制工作帶來(lái)了極大的困難。近幾年來(lái)，由于西部大開(kāi)發(fā)、三峽移民等工程的實(shí)施，我國(guó)的自然、社會(huì)和經(jīng)濟(jì)等因素變化較大，血吸蟲(chóng)病疫情回升顯著，表現(xiàn)為血吸蟲(chóng)病患病人數(shù)增多，急性感染人數(shù)呈上升趨勢(shì)，局部地區(qū)釘螺擴(kuò)散明顯，感染性釘螺分布范圍逐漸擴(kuò)大，部分已經(jīng)達(dá)到傳播控制標(biāo)準(zhǔn)和傳播阻斷標(biāo)準(zhǔn)的地區(qū)疫情嚴(yán)重回升，出現(xiàn)向城市蔓延的趨勢(shì)等，對(duì)人民健康、經(jīng)濟(jì)發(fā)展和社會(huì)進(jìn)步構(gòu)成威脅，血防工作形勢(shì)嚴(yán)峻。 我國(guó)血吸蟲(chóng)病流行區(qū)具有嚴(yán)格的地方性，它與釘螺的分布基本一致。可分為水網(wǎng)、湖沼和山丘三種不同類(lèi)型。流行區(qū)中，湖沼型釘螺面積占全國(guó)釘螺總面積3400km~2的95％以上，其中，江西省鄱陽(yáng)湖周?chē)?1個(gè)縣為血吸蟲(chóng)病流行區(qū)。本文基于空間信息技術(shù)研究鄱陽(yáng)湖區(qū)洲灘環(huán)境下血吸蟲(chóng)病相關(guān)因素的監(jiān)測(cè)方法及其時(shí)空傳播規(guī)律，旨在為我國(guó)湖區(qū)GIS血吸蟲(chóng)病預(yù)警系統(tǒng)的建設(shè)提供方法和技術(shù)的貢獻(xiàn)，從而為血吸蟲(chóng)病防制提供輔助決策和為應(yīng)急反應(yīng)奠定基礎(chǔ)。本文主要開(kāi)展了以下四部分的研究工作。 (1) 基于TM遙感影像的釘螺可疑孳生地的識(shí)別研究。 針對(duì)鄱陽(yáng)湖區(qū)釘螺分布面積廣泛的特點(diǎn)，本文基于流行病學(xué)現(xiàn)場(chǎng)調(diào)查的方法，在2005年現(xiàn)場(chǎng)考察鄱陽(yáng)湖區(qū)血吸蟲(chóng)病流行地區(qū)，同時(shí)測(cè)量和收集疫區(qū)洲灘上的植被數(shù)據(jù)和釘螺數(shù)據(jù)。結(jié)合歷史文獻(xiàn)資料以及合作單位提供的數(shù)據(jù)，分析了鄱陽(yáng)湖區(qū)洲灘和有螺洲灘的分布狀況，進(jìn)而分析了鄱陽(yáng)湖區(qū)植被分布狀況及其與釘螺分布的關(guān)系。采用同一時(shí)相的覆蓋鄱陽(yáng)湖區(qū)的TM遙感影像，選取合適的研究區(qū)，仔細(xì)分析研究區(qū)地貌，典型地物的光譜特征，地面考察收集樣本點(diǎn)的光譜特征，形成用于分類(lèi)的專(zhuān)家經(jīng)驗(yàn)性知識(shí)，然后采用基于知識(shí)模型的專(zhuān)家決策分類(lèi)方法分類(lèi)識(shí)別釘螺可疑孳生地，分類(lèi)精度較已做過(guò)的研究有提高，總體精度為88.94％。將分類(lèi)結(jié)果與鄱陽(yáng)湖區(qū)釘螺分布地圖集進(jìn)行了對(duì)比分析，并統(tǒng)計(jì)分析了2005年研究區(qū)內(nèi)釘螺孳生面積情況，結(jié)果表明整個(gè)研究區(qū)面積為1567.720km~2，其中適合釘螺孳生的面積
[Abstract]:With the updating and development of spatial information technology, its application in the field of public health has become deeper and wider. Remote sensing can rapidly and comprehensively explore, detect and monitor environmental factors related to human health, Geographic Information system (GIS) provides rapid, advanced and reliable technical means for the management and analysis of epidemic factors related to infectious diseases. The methods of data analysis and expression, such as computer simulation, can not only dynamically analyze the temporal and spatial distribution of infectious diseases, but also enable us to study and understand infectious diseases from a completely new perspective and way. Therefore, it provides new ideas and methods for the study of the temporal and spatial spread and epidemic law of infectious diseases. Schistosomiasis is a zoonotic infectious disease with local and natural epidemic origin. Schistosomiasis has a long history and is widely distributed in China. The transmission process involves many natural and social factors. This has brought great difficulties to the prevention and control of schistosomiasis. In recent years, due to the great development of the western region and the implementation of the three Gorges resettlement project, the natural, social and economic factors in our country have changed greatly, and the epidemic situation of schistosomiasis has picked up significantly. The results showed that the number of schistosomiasis cases increased and the number of acute infections increased. The distribution of infected snails was gradually expanded in some areas, the spread of Oncomelania hupensis was obvious in some areas. The epidemic situation in some areas which have reached the standard of communication control and blocking has risen seriously, and the trend of spreading to cities has emerged, which poses a threat to the health of the people, economic development and social progress, and the situation of blood control work is grim. The schistosomiasis endemic area in China is strictly endemic, which is basically consistent with the distribution of snail. It can be divided into three types: water net, lake and marsh, and hilly. In the endemic area, the area of lake-marsh snail accounts for more than 95% of the total snail area of 3400kmm-2 in China. The 11 counties around Poyang Lake in Jiangxi Province are endemic areas of schistosomiasis. Based on spatial information technology, this paper studies the monitoring method of schistosomiasis related factors and its space-time transmission law in the beach environment of Poyang Lake region. In order to provide methods and techniques for the construction of GIS schistosomiasis warning system in the lake area of China, and to provide a basis for decision making and emergency response to schistosomiasis prevention and control, four parts of research work are carried out in this paper. 1) Identification of suspected breeding ground of Oncomelania hupensis based on TM remote sensing image. In view of the widespread distribution of Oncomelania hupensis in Poyang Lake region, based on the method of epidemiological field investigation, the endemic area of schistosomiasis in Poyang Lake region was investigated in 2005. At the same time, the vegetation data and snail data were measured and collected on the beaches in the epidemic area. Based on the historical literature and the data provided by the cooperating units, the distribution of the beaches and the beaches with Luozhou in the Poyang Lake region were analyzed. The distribution of vegetation and the relationship between vegetation distribution and snail distribution in Poyang Lake region are analyzed. The TM remote sensing image covering Poyang Lake region with the same time phase is used to select the suitable research area, and the spectral characteristics of the landforms and typical features of the study area are carefully analyzed. The spectral characteristics of sample points were collected on the ground to form expert empirical knowledge for classification. Then the expert decision classification method based on knowledge model was used to classify and identify the suspected breeding areas of Oncomelania hupensis. The classification accuracy was improved compared with the previous research. The total accuracy is 88.94. The classification results are compared with the distribution atlas of Oncomelania hupensis in Poyang Lake region, and the breeding area of Oncomelania hupensis in 2005 is statistically analyzed. The results show that the area of the whole study area is 1 567.720 km / m ~ 2, and the area suitable for snail breeding is suitable for snail breeding.
【學(xué)位授予單位】：中國(guó)科學(xué)院研究生院（遙感應(yīng)用研究所）
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2006
【分類(lèi)號(hào)】：R184

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本文編號(hào)：1525645