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    Author(s): Erkki Tomppo; Raymond L. Czaplewski; Kai Makisara
    Date: 2002
    Source: Forest Resources Assessment (FRA) Working Paper 61. Rome, Italy: Food and Agriculture Organization of the United Nations, Forest Resources Division, Forest Resources Assessment Programme. 72 p.
    Publication Series: Miscellaneous
    Station: Rocky Mountain Research Station
    PDF: View PDF  (433.76 KB)

    Description

    The approach of FRA 2000 by FAO was the reliance on the participation of individual countries for both supply and analysis of information. It is hoped that this approach will lead for further capacity building in countries (FRA 2000 -main report). While countries firmly support this approach, it has sometimes been criticised on the basis that country information may be inaccurate, incomplete, out-of-date, or internationally inconsistent (Stokstad, 2001; Czaplewski, 2002). According to the FRA 2000 main report, many countries still lack reliable primary information at the national level. Some examples of country level changes in FRA 1990 and FRA 2000, as well as reliability assessment of TBFRA 2000, support this concern. One goal of the future assessments will be to further strengthen country capabilities and participation. In this way, FAO intends to improve the information quality as well as to assist developing countries in their inventories. FAO should also work towards reducing the interval between successive assessments, or towards the establishment of continuous regional assessments.

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    Citation

    Tomppo, Erkki; Czaplewski, Raymond L.; Makisara, Kai. 2002. The role of remote sensing in global forest assessment: A remote sensing background paper for Kotka IV expert consultation; 01.07-05.07.2002, Kotka, Finland. Forest Resources Assessment (FRA) Working Paper 61. Rome, Italy: Food and Agriculture Organization of the United Nations, Forest Resources Division, Forest Resources Assessment Programme. 72 p.

    Keywords

    Forest Resources Assessment, FRA 2000, Global Forest Survey (GFS), remote sensing aided forest resource survey (RSFS)

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