基于MAS-LCM的沙漠化空間模擬方法研究
發(fā)布時間：2018-12-13 12:45
【摘要】：以干旱區(qū)典型城市磴口縣為研究區(qū),利用1995—2015年每隔5年的Landsat TM影像通過遙感解譯獲取研究區(qū)20年的各等級沙漠化空間分布,利用GIS空間分析和重心遷移模型分析沙漠化景觀時空變化趨勢。并以2010年沙漠化分類數(shù)據(jù)為基期年數(shù)據(jù),利用Logistic元胞自動機(Cellular automata-Markov,CA-Markov)模型(簡稱LCM)并引入多智能體系統(tǒng)(Multi-agent system,MAS)模型修正轉(zhuǎn)移規(guī)則,預測2015年沙漠化分類情況及其空間分布格局。研究結(jié)果表明:磴口縣20年間重度及極重度沙漠化面積減小,輕度沙漠化景觀面積逐漸增大,其中2015年的非沙漠化景觀達到37.09%,各類型沙漠化重心遠離磴口縣城,呈現(xiàn)良好態(tài)勢。引入MAS模型的CA-Markov預測模型能夠顯著提升模型的模擬精度,所預測的2015年數(shù)據(jù)結(jié)果 Kappa系數(shù)達到0.62,高于CA-Markov模型模擬結(jié)果,能較好預測干旱區(qū)沙漠化分布情況,為沙漠化監(jiān)管與治理提供了技術(shù)支持。
[Abstract]:Taking Dengkou County, a typical city in arid area, as the research area, the spatial distribution of desertification in the study area for 20 years was obtained by remote sensing interpretation using Landsat TM images every 5 years from 1995 to 2015. The spatial and temporal trends of desertification landscape were analyzed by GIS spatial analysis and barycenter migration model. Based on the annual data of desertification classification in 2010, the Logistic cellular automata (Cellular automata-Markov,CA-Markov) model (LCM) and the multi-agent system (Multi-agent system,MAS) model are introduced to modify the transfer rules. The classification of desertification and its spatial distribution pattern in 2015 are forecasted. The results show that in Dengkou County, the area of severe and extremely severe desertification decreases in 20 years, and the landscape area of light desertification gradually increases. The non-desertification landscape reaches 37.09 in 2015, and the center of various types of desertification is far away from Dengkou County. Present a good situation. The CA-Markov prediction model with MAS model can significantly improve the simulation accuracy of the model. The Kappa coefficient of the predicted data in 2015 is 0.62, which is higher than that of the CA-Markov model, which can better predict the desertification distribution in arid areas. It provides technical support for the regulation and control of desertification.
【作者單位】： 北京林業(yè)大學精準林業(yè)北京市重點實驗室;北京明德立達農(nóng)業(yè)科技有限公司;
【基金】：國家自然科學基金項目(41371189) “十二五”國家科技支撐計劃項目(2012BAD16B00)
【分類號】：X171;X87
本文編號：2376547
[Abstract]:Taking Dengkou County, a typical city in arid area, as the research area, the spatial distribution of desertification in the study area for 20 years was obtained by remote sensing interpretation using Landsat TM images every 5 years from 1995 to 2015. The spatial and temporal trends of desertification landscape were analyzed by GIS spatial analysis and barycenter migration model. Based on the annual data of desertification classification in 2010, the Logistic cellular automata (Cellular automata-Markov,CA-Markov) model (LCM) and the multi-agent system (Multi-agent system,MAS) model are introduced to modify the transfer rules. The classification of desertification and its spatial distribution pattern in 2015 are forecasted. The results show that in Dengkou County, the area of severe and extremely severe desertification decreases in 20 years, and the landscape area of light desertification gradually increases. The non-desertification landscape reaches 37.09 in 2015, and the center of various types of desertification is far away from Dengkou County. Present a good situation. The CA-Markov prediction model with MAS model can significantly improve the simulation accuracy of the model. The Kappa coefficient of the predicted data in 2015 is 0.62, which is higher than that of the CA-Markov model, which can better predict the desertification distribution in arid areas. It provides technical support for the regulation and control of desertification.
【作者單位】： 北京林業(yè)大學精準林業(yè)北京市重點實驗室;北京明德立達農(nóng)業(yè)科技有限公司;
【基金】：國家自然科學基金項目(41371189) “十二五”國家科技支撐計劃項目(2012BAD16B00)
【分類號】：X171;X87
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