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The global Landsat imagery database for the FAO FRA remote sensing survey

机译:粮农组织FRA遥感调查的全球Landsat影像数据库

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To collect and provide periodically updated information on global forest resources, their management and use, the United Nations Food and Agriculture Organization (FAO) has been coordinating global forest resources assessments (FRA) every 5-10 years since 1946. To complement the FRA national-based statistics and to provide an independent assessment of forest cover and change, a global remote sensing survey (RSS) has been organized as part of FAO FRA 2010. In support of the FAO RSS, an image data set appropriate for global analysis of forest extent and change has been produced. Landsat data from the Global Land Survey 1990-2005 were systematically sampled at each longitude and latitude intersection for all points on land. To provide a consistent data source, an operational algorithm for Landsat data pre-processing, normalization, and cloud detection was created and implemented. In this paper, we present an overview of the data processing, characteristics, and validation of the FRA RSS Landsat dataset. The FRA RSS Landsat dataset was evaluated to assess overall quality and quantify potential limitations.
机译:为了收集并提供有关全球森林资源,其管理和使用的定期更新信息,自1946年以来,联合国粮食及农业组织(FAO)一直每5-10年协调一次全球森林资源评估(FRA)。基于统计数据并提供对森林覆盖率和变化的独立评估,作为粮农组织2010年森林资源评估的一部分,组织了一次全球遥感调查。为了支持粮农组织的RSS,建立了适合全球森林分析的图像数据集范围和变化已经产生。从1990-2005年全球土地调查获得的Landsat数据在陆地上所有点的每个经度和纬度交点处进行了系统采样。为了提供一致的数据源,创建并实现了用于Landsat数据预处理,规范化和云检测的运算算法。在本文中,我们概述了FRA RSS Landsat数据集的数据处理,特征和验证。对FRA RSS Landsat数据集进行了评估,以评估整体质量并量化潜在限制。

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