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Multitemporal MERIS images for land-cover mapping at a national scale: a case study of Portugal

机译:用于全国范围内土地覆盖制图的多时MERIS图像:葡萄牙案例研究

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摘要

Medium-spatial-resolution satellite images have already proved to be successful in automatic production of global land-cover maps. However, their operational use for land-cover mapping at a national scale has not yet been well established. We find that the reasons for this are not data-source dependent, but are due to the land-cover nomenclatures properties adopted, regional landscape specificities and the methodological approaches used. The aim of this paper is to evaluate the suitability for national applications of land-cover maps derived from automatic classification of medium-spatial-resolution satellite images. To tackle this issue, we produce a land-cover map of Continental Portugal from multitemporal MEdium Resolution Imaging Spectrometer (MERIS) full-resolution satellite images of 2005 and evaluate its accuracy. For the accuracy assessment of the final map, we compute unbiased estimates of overall, user and producer accuracies using an independent testing sample collected through a stratified random sampling design. The overall accuracy of the final map is 80%, with an absolute precision of 2% at the 95% confidence level. High independent accuracy assessment results demonstrate that medium-spatial-resolution satellite images can be used on an operational basis for annual production of land-cover maps suitable for national applications.
机译:中等空间分辨率的卫星图像已被证明在自动生产全球土地覆盖图方面是成功的。但是,它们尚未在全国范围内用于土地覆盖制图的业务用途。我们发现这样做的原因与数据源无关,而是由于采用了土地覆被命名法属性,区域景观特殊性和所使用的方法论方法。本文的目的是评估由中空分辨率卫星图像的自动分类得出的土地覆盖图在国家应用中的适用性。为解决此问题,我们使用2005年多时相中分辨率成像光谱仪(MERIS)的全分辨率卫星图像制作了葡萄牙大陆的土地覆盖图,并对其准确性进行了评估。为了对最终地图进行准确性评估,我们使用通过分层随机抽样设计收集的独立测试样本来计算总体,用户和生产者准确性的无偏估计。最终贴图的整体精度为80%,在95%置信度下的绝对精度为2%。高度独立的准确性评估结果表明,中等空间分辨率的卫星图像可以在业务基础上用于每年生产适合国家应用的土地覆盖图。

著录项

  • 来源
    《International journal of remote sensing》 |2010年第8期|P.2063-2082|共20页
  • 作者单位

    Portuguese Geographic Institute (IGP), Remote Sensing Unit (RSU), Rua Artilharia Urn, 107, 1099-052 Lisboa, Portugal CEGI, Instituto Superior de Estatistica e Gestao de Informacao, ISEGI, Universidade Nova de Lisboa 1070-312 Lisboa, Portugal;

    Portuguese Geographic Institute (IGP), Remote Sensing Unit (RSU), Rua Artilharia Urn, 107, 1099-052 Lisboa, Portugal;

    INRIA, RESO - Universite de Lyon, ENS Lyon, 46 Allee d'ltalie, 69364 Lyon Cedex, 07, France;

    Portuguese Geographic Institute (IGP), Remote Sensing Unit (RSU), Rua Artilharia Urn, 107, 1099-052 Lisboa, Portugal CEGI, Instituto Superior de Estatistica e Gestao de Informacao, ISEGI, Universidade Nova de Lisboa 1070-312 Lisboa, Portugal;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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