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Citation:

Monitoring the Conversion of Farm land to Forests ProjectBased on QuickBird Image

  • Received Date: 2007-12-15
  • Based on the abundant textures of the high resolution remote sensing image, an ob jectorientedclassification was used to extract the artific ia l a fforestation from Qu ickB ird image in the area of the conversion ofcrop land to forest projec.t The classification adopted the object-distance-baged nearest c lassifiermethod and projectmode lorientedmembership function method. The resu lts ind icated that it was feasible to get the layou,t area,plantingmanner and standard of the conversion of farmland to forest project from high resolution remote sensingimage. The verac ity and stab ilityweremore than 88 percen.
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    [2] 杨清华, 齐建伟, 孙永军. 高分辨率卫星遥感数据在土地利用动态监测中的应用研究[J]. 国土资源遥感, 2001( 4): 20 - 27

    [3] 王晓红, 聂洪峰, 杨清华, 等. 高分辨率卫星数据在矿山开发状况及环境监测中的应用效果比较[J]. 国土资源遥感, 2004 ( 1):15 - 18

    [4] 吴 虹, 杨永德, 王松庆. Qu ickBird22& SPOT21矿山生态环境遥感调查试验研究[J]. 国土资源遥感, 2004 ( 4): 4 - 49

    [5] 高龙华, 程 芳. 基于Qu ickBird影像的滩涂资源监测研究[J].遥感技术与应用, 2004, 19( 2 ): 95- 97

    [6] 侯碧清, 谭宽祥, 李家湘. 运用QU ICKBIRD 卫星影像调查株洲市园林绿化现状[J]. 林业调查规划, 2005, 30( 1): 5 - 7

    [7] 杨泽运, 康家银, 赵广东. 利用Qu ickBird全色遥感影像更新城市大比例尺地形图[J]. 测绘工程, 2005, 14( 2): 29- 31

    [8] 黄建文, 鞠洪波, 赵 峰, 等. 快鸟数据在退耕还林中应用方法的研究[J]. 林业科学研究, 2004, 17( 3): 267- 271

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    Definiens. eCogn it ion User Gu ide 4[M], G ermany, 2000
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    H ofmann P. Detecting In formal Settlements from IKONOS ImageData U sing Method s of Ob ject O rien ted Image Analysis AnExamp le from Cape Town ( South Africa) [M] / /Regensbu rg. R emote Sen sing ofUrbanA reas /Fernerkundung inU rb anen Raumen.JURGENS, C. 2001: 41- 42
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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Monitoring the Conversion of Farm land to Forests ProjectBased on QuickBird Image

  • 1. Research In stitu te of Forest Resou rce In formation Techn iques, CAF, Beijing 100091, China

Abstract: Based on the abundant textures of the high resolution remote sensing image, an ob jectorientedclassification was used to extract the artific ia l a fforestation from Qu ickB ird image in the area of the conversion ofcrop land to forest projec.t The classification adopted the object-distance-baged nearest c lassifiermethod and projectmode lorientedmembership function method. The resu lts ind icated that it was feasible to get the layou,t area,plantingmanner and standard of the conversion of farmland to forest project from high resolution remote sensingimage. The verac ity and stab ilityweremore than 88 percen.

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