發(fā)布時(shí)間：2018-03-09 06:19

  本文選題：干熱河谷　切入點(diǎn)：土地利用　出處：《昆明理工大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：景觀格局一直是景觀生態(tài)學(xué)研究的重點(diǎn),土地利用變化直接影響著地表的景觀格局。元江干熱河谷生態(tài)脆弱區(qū)域內(nèi)土地利用不當(dāng)使之存在潛在荒漠化的問題。本研究以景觀生態(tài)學(xué)和人工神經(jīng)網(wǎng)絡(luò)為理論基礎(chǔ),選取元江干熱河谷生態(tài)脆弱區(qū)部分區(qū)域作為研究區(qū),采用遙感技術(shù)和地理信息系統(tǒng)技術(shù),對(duì)研究區(qū)2006年和2012年兩期衛(wèi)星遙感影像進(jìn)行解譯,從而得到這兩個(gè)時(shí)期的土地利用數(shù)據(jù)。在此基礎(chǔ)上,采用土地利用類型轉(zhuǎn)移矩陣分析模型對(duì)研究區(qū)土地利用的時(shí)空變化進(jìn)行分析,進(jìn)而解釋研究區(qū)土地利用結(jié)構(gòu)時(shí)空變化規(guī)律,再利用人工神經(jīng)網(wǎng)絡(luò)模型對(duì)研究區(qū)景觀格局進(jìn)行動(dòng)態(tài)模擬和預(yù)測(cè),定量分析演變特點(diǎn)。研究發(fā)現(xiàn)：研究區(qū)的土地利用類型主要以耕地、林地和稀樹灌木草叢為主：2006年到2012年6年間,耕地、稀樹灌木草叢、灘涂、居民用地、園地和工礦倉儲(chǔ)用地面積增加,林地和水域面積減少；林地和耕地的面積變化最大,分別為-106.70 km2和81.57 km2。動(dòng)態(tài)度最大的為灘涂,為9.90%/a,此外為工礦倉儲(chǔ)用地和水域。耕地的貢獻(xiàn)主要來自于林地和稀樹灌木草叢；灘涂的貢獻(xiàn)主要來自于水域和稀樹灌木草叢；工礦倉儲(chǔ)用地的貢獻(xiàn)主要來自于稀樹灌木草叢。林地主要轉(zhuǎn)出為耕地和稀樹灌木草叢：水域主要轉(zhuǎn)出為園地和稀樹灌木草叢。研究區(qū)受自然因素和人為因素的干擾,土地利用結(jié)構(gòu)發(fā)生了明顯變化,水域明顯減少、灘涂明顯增加,大量的林地被砍伐,并且開發(fā)了很多耕地。研究區(qū)林地和耕地具有較高的聚集度,斑塊形狀較復(fù)雜,灘涂和居民地斑塊形狀較簡單；工礦倉儲(chǔ)用地和水域斑塊間平均最近距離較遠(yuǎn)；與稀疏灌木草叢、水域和園地這三類土地利用類型相鄰的斑塊類型較豐富,與工礦倉儲(chǔ)用地和林地相鄰的斑塊類型比較單一,工礦倉儲(chǔ)用地主要被稀樹灌木草叢包圍,林地主要被耕地包圍;稀樹灌木草叢主要分布在河谷兩側(cè),聚集度高。從斑塊水平上看,2006到2012年以來,大部分的斑塊類型趨于破碎化,邊緣復(fù)雜化。林地一直為斑塊數(shù)量最大的景觀地類；受人類活動(dòng)影響,林地和耕地景觀破碎化加重明顯,且其受干擾的范圍分布廣且分散；稀樹灌木草叢斑塊間的連通性增強(qiáng),斑塊平均大小值較大。從景觀水平上看,從2006至2012年,研究區(qū)總體景觀格局呈現(xiàn)了一種多樣化、破碎化的趨勢(shì)。斑塊數(shù)、斑塊平均大小、面積加權(quán)平均形狀因子、蔓延度和散布與并列指數(shù)等景觀指數(shù)均表現(xiàn)出景觀破碎化程度的提高。香農(nóng)多樣性指數(shù)與香農(nóng)均度指數(shù)的持續(xù)增加表明其均勻度程度增加,從而揭示了研究區(qū)八類景觀類型間存在均勻化分布的趨向。所建神經(jīng)網(wǎng)絡(luò)模型對(duì)測(cè)試集的預(yù)測(cè)值與實(shí)際值具有較好的擬合性,說明利用人工神經(jīng)網(wǎng)絡(luò)來研究干熱河谷景觀間接驅(qū)動(dòng)因子對(duì)景觀格局的影響是可行的。模型預(yù)測(cè)顯示,隨著林地、灘涂、居民用地、工礦倉儲(chǔ)用地、耕地所占面積比增加,景觀斑塊密度增加；隨著水域、稀樹灌木草叢和園地所占面積比增加,景觀斑塊密度下降。景觀多樣性指數(shù)會(huì)隨著居民用地和園地所占面積比的增加而增加,隨著耕地所占面積比的增加而降低。景觀聚集度會(huì)隨著水域、稀樹灌木草叢和園地所占面積的增加而增加；隨著灘涂、居民用地和耕地所占面積比的增加而下降。隨著林地、耕地、工礦倉儲(chǔ)用地和灘涂所占面積比的增加,景觀斑塊形狀更加復(fù)雜化,隨著水域、稀樹灌木草叢和園地所占面積比的增加,景觀斑塊形狀趨于規(guī)范化。
[Abstract]:The landscape pattern has been the focus of research in landscape ecology, land use change has a direct impact on the landscape pattern of the surface. The Yuanjiang valley ecological fragile region land use improper to potential desertification problems. Based on landscape ecology and artificial neural network theory, selection of Yuanjiang river ecological fragile zone region as the research part area, using remote sensing and GIS technology, the study area in 2006 and 2012 satellite remote sensing image interpretation, so as to obtain the land use data of the two periods. On this basis, the analysis of land use type transfer matrix analysis model of spatial and temporal changes of land use in the study area, and then explain the variation of structure time and space of land use in the study area, using artificial neural network model for dynamic simulation and the landscape pattern of the study area Measurement, quantitative analysis of evolution characteristics. The study found: land use types in the study area is mainly farmland, woodland and savanna: 2006 to 2012 6 years, cultivated land, savanna, beaches, land, garden land and mining warehouse land area increased, woodland and water area decreased; and the changes of forest area arable land was the largest, respectively -106.70 km2 and 81.57 km2. dynamic degree is the largest beach, 9.90%/a, in addition to industrial storage land and waters. The main contribution of cultivated land from woodland and savanna; tidal contributions mainly from waters and savanna; mining warehouse land contribution mainly from savanna woodland mainly turn into cultivated land and savanna: waters mainly turn into garden and savanna. The study area affected by natural factors and human factors interference, land Significant changes occurred in the water use structure, significantly reduced, beach increased significantly, a lot of forest have been cut down, and developed a lot of cultivated land. The aggregation degree of woodland and cultivated land in the area is high, the patch shape is more complex, and the beach residents patch shape is simple; the industrial storage land and water patches between the average nearest distance far away; and sparse shrubs, waters and garden of these three types of land use patch type adjacent to the rich, and industrial use patches and woodland adjacent single, mining warehouse land is mainly surrounded by dilute tree shrubs, woodland is mainly surrounded by farmland; savanna is mainly distributed in the valley on both sides and a high degree of aggregation. From the patch level, from 2006 to 2012, most of the types of plaque fragmentation, edge has been complicated. Forest landscape types of the largest number of plaque; Affected by human activities, landscape fragmentation of woodland and cultivated land increased significantly, and the interference range widely distributed and decentralized; savanna connectivity between patches increased, mean patch size is larger. On the landscape level, from 2006 to 2012, the overall landscape pattern of the study area showing a diversification, fragmentation trend. Number of patches, mean patch size, area weighted average shape factor, spread and interspersion and juxtaposition index landscape index showed the degree of landscape fragmentation increased. Increasing the Shannon diversity index and Shannon's evenness index showed that the evenness degree increases, which reveals the tendency to homogenization distribution of the study area eight kinds of landscape types. The neural network model to predict the test set value is in good agreement with the actual value, that view to study the dry hot valley by using artificial neural network The concept of indirect driving factors of landscape pattern is feasible. The model prediction indicates that with the land, beaches, land, mining warehouse land, cultivated land area increased, landscape patch density increased; with water, savanna and garden area increased, patch density, landscape diversity decreased. The index will increase with the residential area and the garden area ratio increases, decreases with the cultivated land area ratio increasing. The degree of landscape aggregation with waters, savanna and garden area increases with the increase of residents; with beaches, land and cultivated land area increased decreased. With forest land, cultivated land, mining warehouse land and beach area ratio increased, patch shape is more complex, with waters, savanna and garden area increased, landscape patch shape The form tends to be standardized.

【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：P901

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