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

Abstract

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.