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作 者:陆东海[1,2] 佘江峰[1,2] 宋晓群[3] 王铁成[4] 周阳[1,2]
机构地区:[1]南京大学地理信息科学系,江苏南京210023 [2]江苏省地理信息技术重点实验室,江苏南京210023 [3]江苏省国土资源信息中心,江苏南京210029 [4]江苏省测绘工程院,江苏南京210013
出 处:《测绘与空间地理信息》2014年第5期25-29,共5页Geomatics & Spatial Information Technology
基 金:国家自然基金项目(41371365);国土资源部公益性行业科研专项(201011015-1)资助
摘 要:土地执法监察的实施需明确土地利用变化区域的位置、是否违法及违法类型等信息。大多数土地动态监测手段只获取变化区域的位置信息,无法快速明确具体违法类型及识别伪变化,加大了土地动态巡查的工作量。基于此,本文提出针对非正常建设用地的分类识别模型,即一种可快速识别建设用地变化图斑违法类型的方法。该模型将变化检测获取的变化图斑与相关地政数据进行叠置分析,并设计非正常建设用地分类识别矩阵对变化图斑进行判断,采用计算机识别和人工辅助识别相结合的方式快速明确非正常建设用地的变化性质。应用结果表明,该模型可有效解决综合分析多层矢量数据时图斑要素的跨界问题,提高了识别效率;和现有监测方法结合使用,可快速了解监测区域的土地利用变化概况,较大地提高了土地执法工作的自动化程度。The implement of land law enforcement and supervision requires to clear the information about the position、Whether it is illegal and illegal type of the land use change region. Most of the land use dynamic monitoring means only get location information of changed area,which is not able to quickly identify specific illegal types and identifications pseudo-change,and it will increase the workload of land dynamic inspection. Based on this,this paper proposes an identification model for abnormal construction land,namely a mean of quickly identification the illegal type of changed polygons of construction land. This model compares the changed polygons from change detectionwith relevant land administrational data by means of overlapping,and designs an identification matrix of abnormal constructional land to rapidly judge and clear the changed types of abnormal constructional land by computer and artificial means. Application results show that this model can effectively solve the cross-border issue which is produced by comprehensively analyzing multi-element vector data,and improve the efficiency of identification. Combining this model with existing monitoring methods can learn to the overview of land use change of monitor region quickly,and improve the automation degree of land law enforcement greatly.
关 键 词:土地动态监测 非正常建设用地 分类识别模型 变化图斑 地政数据
分 类 号:P25[天文地球—测绘科学与技术] TU984.11[建筑科学—城市规划与设计]
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