Community Research and Development Information Service - CORDIS

Abstract

A methodology was developed and applied to estimating forest areas and producing forest maps. The method utilities satellite data and ground reference data. It takes into consideration the fact that a pixel rarely represents any single ground cover class. This is particularly true for low-spatial-resolution data. It also takes into consideration that the spectral classes overlap. The image was first classified using an unsupervised clustering method. A (multinormal) spectral density function was estimated for each class based on the spectral vectors (reflectance values) of the cluster members. Values of the target variable -the proportion of forested area -were: determined for the spectral classes using sampling from CORINE (Coordination of Information on the Environment) Land Cover database.

The estimated forest areas were compared with those extracted from the full-coverage CORINE data and with official forest statistics reported to the European Commission's Statistical Office (EUROSTAT). The forest percentage (proportion of forest area of the total land area) of 12 countries of the European Union was underestimated by 1.8% compared to the CORINE data. It was underestimated by 4.2% when compared with EUROSTAT's statistics and 6.0% when compared to United Nations Economic Commission for Europe/Food and Agricultural Organization (UN-ECFJFAO) statistics. The largest underestimation of forest percentage within a country (compared to CORINE) was in France (5.9%). The largest overestimation was found in Ireland, 15.6%. .

Additional information

Authors: HAME T, VTT Automation (FI);ANDERSSON K, VTT Automation (FI);RAUSTE Y, VTT Automation (FI);STENBERG P, University of Helsinki (FI);KENNEDY P, Space Applications Institute, JRC (FI);FOLVING S, Space Applications Institute, JRC (FI);SARKEALA J, Stora Enshu Forest Consulting Ltd (FI)
Bibliographic Reference: An article published in: Elsevier, Remote Sensing of Environment, 77 (2001), pp.1-16
Record Number: 200013608 / Last updated on: 2001-07-30
Category: PUBLICATION
Original language: en
Available languages: en