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基于面向对象分类的冬小麦种植面积遥感监测 —以淮北市临涣矿区为例
崔玉环,王杰,姚梦园
0
(安徽农业大学理学院,合肥 230036;安徽大学资源与环境工程学院,合肥 230039;高分辨率对地观测系统安徽数据与应用中心,合肥 230030)
摘要:
为揭示2000年以来淮北矿区冬小麦种植面积变化规律,以IKNOS、Worldview-III高分辨率遥感影像为数据源,采用基于多尺度分割的面向对象分类方法,提取安徽淮北临涣矿区冬小麦种植面积信息,分析其时空变化特征及其驱动因素。结果表明,基于多尺度分割的面向对象分类方法对冬小麦种植信息提取结果非常理想,Kappa系数达到0.92,总体精度为93%,制图精度可达到94%;临涣矿区现有冬小麦种植面积为21.16 km2,占矿区总面积的 55.1%;随着临涣矿区开采规模不断扩大与人口密度的增加,矿区冬小麦种植面积显著减少,交通运输用地、工业用地以及住宅用地均有不同程度增加。该研究对深入开展淮北矿区冬小麦长势监测和估产、区域粮食安全评估等工作提供重要的科学参考。
关键词:  冬小麦  面向对象  遥感监测  时空变化  淮北矿区
DOI:10.13610/j.cnki.1672-352x.20171214.003
基金项目:国家自然科学基金(41401022), 安徽省自然科学基金项目(1608085QD82), 安徽农业大学稳定与引进人才科研资助项目(yj2015-26)和安徽省高校青年优秀人才基金项目(2013KJT010022)共同资助。
Remote sensing monitoring of winter wheat planting area based on object-oriented method —a case study of Linhuan mining area in Huaibei city
CUI Yuhuan,WANG Jie,YAO Mengyuan
(School of Science, Anhui Agricultural University, Hefei 230036;School of Resources and Environmental Engineering, Anhui University, Hefei 230039;Anhui Data and Application Center for High-resolution Earth Observation System, Hefei 230030)
Abstract:
In order to reveal the spatial-temporal variation of winter wheat planting area in Huaibei mining area in Huaibei city since 2000, the information of winter wheat planting in this area was extracted by the object-oriented classification method based on multi-scale segmentation using high-resolution images of IKNOS and Worldview-III as data resource. The temporal and spatial characteristics and its driving factors were then analyzed. The results showed that the remote sensing interpretation of the object-oriented classification based on multi-scale segmentation performed well for the winter wheat planting information, with Kappa coefficient of 0.92, the overall accuracy of 93%, and the mapping accuracy of 94%. The current winter wheat planting region in Linhuan mining area was 21.16 km2, accounting for 55.1% of the total mining area. With an increase of mining in Linhuan mining area and regional population, the winter wheat planting area significantly decreased in recent years, while areas of transportation land, industrial land and residential land increased at different levels.
Key words:  winter wheat  object-oriented  remote sensing monitoring  temporal and spatial change  Huaibei mine area

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