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基于高分辨率遙感影像分類(lèi)的城鎮(zhèn)土地利用規(guī)劃監(jiān)測(cè)
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北京市科技計(jì)劃資助項(xiàng)目(Z141100000614001)


Urbanrural Land Use Plan Monitoring Based on High Spatial Resolution Remote Sensing Imagery Classification
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    摘要:

    城鎮(zhèn)土地利用規(guī)劃是城鎮(zhèn)化健康有序推進(jìn)的基礎(chǔ),規(guī)劃實(shí)施監(jiān)測(cè)是其實(shí)施的保障。遙感和GIS相結(jié)合的方法可快速監(jiān)測(cè)城鎮(zhèn)土地利用規(guī)劃實(shí)施情況,保障土地利用規(guī)劃實(shí)施的動(dòng)態(tài)管理,。利用0.5m分辨率的WorldView 2衛(wèi)星遙感影像,,采用面向?qū)ο蟮挠跋穹治龇椒?,針?duì)基于知識(shí)規(guī)則分類(lèi)特征選取及閾值確定難點(diǎn),,將CART決策樹(shù)與面向?qū)ο蠓诸?lèi)方法結(jié)合,,實(shí)現(xiàn)參與分類(lèi)最優(yōu)對(duì)象特征的選擇以及特征閾值的自動(dòng)確定,。在分類(lèi)基礎(chǔ)上,,對(duì)每個(gè)規(guī)劃圖斑計(jì)算地類(lèi)規(guī)劃實(shí)施完成率,實(shí)現(xiàn)對(duì)土地利用規(guī)劃實(shí)施過(guò)程進(jìn)行監(jiān)測(cè)評(píng)價(jià),。最后,,以北京市房山區(qū)某區(qū)域?yàn)檠芯繀^(qū),進(jìn)行了試驗(yàn)驗(yàn)證,。結(jié)果表明:最終分類(lèi)總體精度達(dá)0.89,,Kappa系數(shù)為0.87,表明構(gòu)建的分類(lèi)算法基本能滿(mǎn)足城鎮(zhèn)土地利用規(guī)劃監(jiān)測(cè)的需求,。研究區(qū)東北部土地利用規(guī)劃實(shí)施情況比西部好,,公共綠地、水域等地類(lèi)需重點(diǎn)調(diào)查監(jiān)測(cè),,同時(shí)二類(lèi)居住用地的建筑密度偏高,,綠化率偏低,。

    Abstract:

    Urban-rural land use plan is the foundation of healthily and orderly sustainable development of urbanization and the monitoring of plan implementation is considered as the guarantee. The association of remote sensing and GIS is one of rapid and effective monitoring method for urban-rural land use plan implementation which strongly strengthens the dynamic management of land use plan implementation. We used high spatial resolution remote sensing imagery—WorldView2 with resolution of 0.5m and the objectoriented image analysis method to achieve the classification. The features and thresholds were determined with CART decision tree in objectoriented rule classification. On the basis of classification results, the completion rate of land plan for each plan patch was computed with the monitoring and evaluation of land use plan implementation. Finally, a subdistrict of Fangshan District,Beijing City was taken as the study area to illustrate the method. The results showed that the final overall accuracy of classification was 089 and Kappa coefficient was 0.87. The proposed classification algorithm can meet the basic needs of urbanrural land use plan monitoring. The implementation of land use plan in northeast study area is better than that in the west. The public green land and water area need to be investigated and monitored further as the key objects, at the same time, the density of second type residential building is a little high, while the green landrate is low.

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張 超,李智曉,李鵬山,楊建宇,朱德海.基于高分辨率遙感影像分類(lèi)的城鎮(zhèn)土地利用規(guī)劃監(jiān)測(cè)[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2015,46(11):323-329. Zhang Chao, Li Zhixiao, Li Pengshan, Yang Jianyu, Zhu Dehai. Urbanrural Land Use Plan Monitoring Based on High Spatial Resolution Remote Sensing Imagery Classification[J]. Transactions of the Chinese Society for Agricultural Machinery,2015,46(11):323-329.

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  • 收稿日期:2015-04-21
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  • 在線發(fā)布日期: 2015-11-10
  • 出版日期: 2015-11-10
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