發(fā)布時間：2018-06-22 05:36

  本文選題：曹妃甸工業(yè)園區(qū) + 景觀格局　； 參考：《蘭州交通大學》2015年碩士論文

【摘要】：曹妃甸工業(yè)園區(qū)的開發(fā)規(guī)劃建設(shè)日異月殊,瞬息萬變,經(jīng)濟高速發(fā)展,產(chǎn)業(yè)高度集聚,地表景觀格局正在發(fā)生著翻天覆地的變化,基于此現(xiàn)狀,本文借助第一次地理國情普查數(shù)據(jù),通過GIS平臺與景觀指數(shù)統(tǒng)計分析,對研究區(qū)的地表景觀格局時空變化進行分析,預測模擬出曹妃甸工業(yè)園區(qū)未來地表景觀格局結(jié)構(gòu)變化趨勢,以期對該區(qū)域國土空間開發(fā)合理提供建議,把握資源分布與利用,實現(xiàn)可持續(xù)發(fā)展的理念。本文把曹妃甸工業(yè)園區(qū)的地表景觀格局研究從整體上分為了兩個方面,一是把握土地覆被的結(jié)構(gòu)特征和空間動態(tài)變化;二是計算景觀格局指數(shù),進而從數(shù)量上的變化體現(xiàn)格局特征趨勢,結(jié)合兩方面的變化特征,定量地揭示該區(qū)域地表景觀格局的整體變化,主要對以下方面進行了研究分析。(1)通過GIS平臺強大的空間分析能力,分別對曹妃甸工業(yè)園區(qū)2000、2008、2011和2014年的四期地理國情數(shù)據(jù)空間疊加分析,生成轉(zhuǎn)移矩陣,從地表覆蓋轉(zhuǎn)化的角度入手,具體分析2000-2008、2008-2011、2011-2014和2000-2014年時期內(nèi)各地表景觀斑塊之間的相互結(jié)構(gòu)轉(zhuǎn)化,進行一定的圖表統(tǒng)計分析和繪制相對應(yīng)的空間分布圖,展現(xiàn)格局特征。接著從景觀斑塊的變化速率著手,用單一景觀斑塊動態(tài)度和綜合景觀格局的動態(tài)度兩個指標,定量計算分析曹妃甸工業(yè)園區(qū)動態(tài)度,研究發(fā)現(xiàn),該區(qū)域由于填海造地工程的原因,地表斑塊間的轉(zhuǎn)化較為復雜,其中,水域景觀在此期間變化最明顯,面積逐年減少,而區(qū)域內(nèi)綜合景觀格局的動態(tài)度呈逐年增加趨勢,在2011-2014年達到最大。(2)適當?shù)剡x取TA、NP、PD、LPI、LSI、PAFRAC、CONTAG、SPLIT、SHDI和AI這十個景觀指數(shù),從類型水平和景觀水平兩個層面對研究區(qū)2000-2014年內(nèi)四期數(shù)據(jù)的各類地表景觀斑塊分別計算分析,繪制指數(shù)變化走向圖,刻化景觀斑塊格局從數(shù)量上的變化趨勢,研究發(fā)現(xiàn),由于受到較大的人工干擾,該區(qū)域的景觀斑塊急劇上升,形狀趨于復雜,破碎化現(xiàn)象嚴重,景觀的多樣性較為豐富,空間分布的集聚性降低,特別是2000-2008年間,生態(tài)環(huán)境遭到了不同程度的破壞,較為脆弱,整體上景觀格局朝著由單一向復雜的方向發(fā)展。(3)結(jié)合馬爾科夫鏈和灰色預測模型的原理,利用數(shù)據(jù)對曹妃甸工業(yè)園區(qū)2014年地表景觀格局進行預測,然后與2014年真實的數(shù)據(jù)對比,通過相對誤差和中誤差兩個指標對模型預測精度評定,研究發(fā)現(xiàn),灰色預測模型精度更高,最后,用該模型對未來做出預測,并對結(jié)果進行一定的分析。(4)借助前文中的分析研究結(jié)果,定性的分析曹妃甸工業(yè)園區(qū)地表景觀格局變化的驅(qū)動因子,主要分為科技、經(jīng)濟、自然因素、人文因素和政策輔助因素。
[Abstract]:The development planning and construction of the Caofeidian Industrial Park are changing day and month, the economy is developing at a high speed, the industry is gathering highly, and the landscape pattern of the land surface is undergoing earth-shaking changes, based on the present situation. In this paper, with the help of the data of the first General Survey of Geographical conditions, the spatial and temporal changes of the surface landscape pattern in the study area are analyzed by means of GIS platform and landscape index statistical analysis. The forecast simulates the change trend of the future surface landscape pattern structure in Caofeidian Industrial Park in order to provide reasonable suggestions for the development of land and space in the region, grasp the distribution and utilization of resources, and realize the idea of sustainable development. In this paper, the study on the surface landscape pattern of Caofeidian Industrial Park is divided into two aspects as a whole, one is to grasp the structural characteristics of land cover and spatial dynamic change, the other is to calculate the landscape pattern index. From the quantitative changes to reflect the pattern characteristics of the trend, combined with the two aspects of the characteristics of change, quantitative reveal the overall changes of the landscape pattern of the region, The following aspects are mainly studied and analyzed. (1) through the powerful spatial analysis ability of GIS platform, the spatial superposition analysis of the four periods of geographical national conditions data of the Caofeidian Industrial Park 20002008 / 2011 and 2014 respectively is carried out to generate the transfer matrix. From the point of view of land surface cover transformation, this paper analyzes the mutual structure transformation of landscape patches in different places during the period of 2011-2014 and 2000-2014 from 2008 to 2011 to 2014 and 2000-2014, and makes a statistical analysis of charts and draws corresponding spatial distribution maps to show the pattern characteristics. Then, the dynamic degree of Caofeidian Industrial Park is calculated and analyzed quantitatively by using the dynamic attitude of single landscape patch and the dynamic degree of comprehensive landscape pattern. Because of the reclamation engineering, the transformation of surface patches in this area is more complex, among which, the water landscape changes most obviously, the area decreases year by year, and the dynamic degree of the comprehensive landscape pattern in the region increases year by year. In 2011-2014, the maximum was reached. (2) Ten landscape indices, namely, TANPNPPDLPII / LSIPAFRACU PAFRACU PANTAGANG / ITSPLSHDI and AI, were selected to calculate and analyze the various types of landscape patches in four periods of data from 2000 to 2014 in the study area from two levels of type and landscape level, and to map the trend of index change. The change trend of landscape patch pattern from the number of engraved landscape, the study found that, due to the larger artificial interference, the landscape patch increased sharply, the shape tended to be complex, the fragmentation phenomenon was serious, and the diversity of the landscape was relatively rich. The agglomeration of spatial distribution is reduced, especially from 2000 to 2008, the ecological environment has been destroyed to varying degrees, which is relatively fragile, and the overall landscape pattern is developing from a single to a complex direction. (3) combining the principle of Markov chain and grey prediction model, The surface landscape pattern of Caofeidian Industrial Park in 2014 was forecasted by data, then compared with the real data in 2014, the prediction accuracy of the model was evaluated by two indexes: relative error and middle error. The grey prediction model is more accurate. Finally, the model is used to predict the future and the results are analyzed. (4) with the help of the above analysis results, the driving factors of the surface landscape pattern change in Caofeidian Industrial Park are analyzed qualitatively. Mainly divided into science and technology, economy, natural factors, human factors and policy auxiliary factors.
【學位授予單位】：蘭州交通大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：P901

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相關(guān)碩士學位論文 前1條

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本文編號：2051796