Sub-pixel area estimation of European forests using NOAA-AVHRR data

Pamela Kennedy, Sten Folving, Tuomas Häme, Kaj Andersson, Seppo Väätäinen, Pauline Stenberg, Janne Sarkeala

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientific

Abstract

A map of European forests has been produced for the pan-European area. In the database, the forest area within each NOAA-AVHRR (National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer) pixel has been estimated. A new approach, presented in another paper at this conference was utilized in the estimation procedure. The method takes into account both the uncertainty of a pixel to belong to a specific ground class and the mixed ground contents of a spectral class. The image interpretation was carried out using an AVHRR image mosaic compiled from the red and near infra-red channels, for the entire pan-European area. This mosaic was composited from forty-nine AVHRR images acquired in late summer 1996. Atmospheric correction of the data was performed to the individual images using the SMAC (Simplified Method for Atmospheric Corrections) procedure. An additional BRDF (Bi-directional Reflectance Distribution Function) correction was made to each image. The reflectance mosaic was computed using the weighted mean of the reflectance values of cloud-free pixels. The CORINE Land Cover database was used to represent the ground information. This study fulfils some of the key objectives of the FIRS (Forest Information from Remote Sensing) Project of the Space Applications Institute (SAI) at the Joint Research Centre, Ispra, of the European Commission. In particular, the work represents an attempt to improve upon the reliability of existing mapped information for Europe. Firstly, the method results in a continuous variable of forest probability representing an estimate of forest area for each pixel. Secondly, the likelihood of under-estimating the forest cover in areas where the forest is fragmented or over-estimating if the cover is uniform and homogeneous, is reduced. Thirdly, the resulting image database could also be utilized to estimate other forest characteristics, if relevant ground data are available. Forest area statistics derived from the probability database for Italy and France were compared with area estimates taken from EUROSTAT's (Statistical Office of the European Communities) database for 1995. The correlation coefficients were found to be 0.89 and 0.85 for Italy and France respectively.
Original languageEnglish
Title of host publicationConference on remote sensing and forest monitoring
Subtitle of host publicationProceedings
PublisherEuropean Commission, Joint Research Center (JRC)
Number of pages12
Publication statusPublished - 1999
MoE publication typeNot Eligible
EventIUFRO Conference on Remote Sensing and Forest Monitoring - Rogow, Poland
Duration: 1 Jun 19993 Jun 1999

Conference

ConferenceIUFRO Conference on Remote Sensing and Forest Monitoring
CountryPoland
CityRogow
Period1/06/993/06/99

Fingerprint

AVHRR
pixel
atmospheric correction
reflectance
bidirectional reflectance
European Commission
forest cover
European Union
near infrared
land cover
remote sensing
summer
method
mosaic

Cite this

Kennedy, P., Folving, S., Häme, T., Andersson, K., Väätäinen, S., Stenberg, P., & Sarkeala, J. (1999). Sub-pixel area estimation of European forests using NOAA-AVHRR data. In Conference on remote sensing and forest monitoring: Proceedings European Commission, Joint Research Center (JRC).
Kennedy, Pamela ; Folving, Sten ; Häme, Tuomas ; Andersson, Kaj ; Väätäinen, Seppo ; Stenberg, Pauline ; Sarkeala, Janne. / Sub-pixel area estimation of European forests using NOAA-AVHRR data. Conference on remote sensing and forest monitoring: Proceedings. European Commission, Joint Research Center (JRC), 1999.
@inproceedings{9794df106bf34420b53e7ac2b577b195,
title = "Sub-pixel area estimation of European forests using NOAA-AVHRR data",
abstract = "A map of European forests has been produced for the pan-European area. In the database, the forest area within each NOAA-AVHRR (National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer) pixel has been estimated. A new approach, presented in another paper at this conference was utilized in the estimation procedure. The method takes into account both the uncertainty of a pixel to belong to a specific ground class and the mixed ground contents of a spectral class. The image interpretation was carried out using an AVHRR image mosaic compiled from the red and near infra-red channels, for the entire pan-European area. This mosaic was composited from forty-nine AVHRR images acquired in late summer 1996. Atmospheric correction of the data was performed to the individual images using the SMAC (Simplified Method for Atmospheric Corrections) procedure. An additional BRDF (Bi-directional Reflectance Distribution Function) correction was made to each image. The reflectance mosaic was computed using the weighted mean of the reflectance values of cloud-free pixels. The CORINE Land Cover database was used to represent the ground information. This study fulfils some of the key objectives of the FIRS (Forest Information from Remote Sensing) Project of the Space Applications Institute (SAI) at the Joint Research Centre, Ispra, of the European Commission. In particular, the work represents an attempt to improve upon the reliability of existing mapped information for Europe. Firstly, the method results in a continuous variable of forest probability representing an estimate of forest area for each pixel. Secondly, the likelihood of under-estimating the forest cover in areas where the forest is fragmented or over-estimating if the cover is uniform and homogeneous, is reduced. Thirdly, the resulting image database could also be utilized to estimate other forest characteristics, if relevant ground data are available. Forest area statistics derived from the probability database for Italy and France were compared with area estimates taken from EUROSTAT's (Statistical Office of the European Communities) database for 1995. The correlation coefficients were found to be 0.89 and 0.85 for Italy and France respectively.",
author = "Pamela Kennedy and Sten Folving and Tuomas H{\"a}me and Kaj Andersson and Seppo V{\"a}{\"a}t{\"a}inen and Pauline Stenberg and Janne Sarkeala",
note = "LB-NA-19530-EN-C",
year = "1999",
language = "English",
booktitle = "Conference on remote sensing and forest monitoring",
publisher = "European Commission, Joint Research Center (JRC)",

}

Kennedy, P, Folving, S, Häme, T, Andersson, K, Väätäinen, S, Stenberg, P & Sarkeala, J 1999, Sub-pixel area estimation of European forests using NOAA-AVHRR data. in Conference on remote sensing and forest monitoring: Proceedings. European Commission, Joint Research Center (JRC), IUFRO Conference on Remote Sensing and Forest Monitoring, Rogow, Poland, 1/06/99.

Sub-pixel area estimation of European forests using NOAA-AVHRR data. / Kennedy, Pamela; Folving, Sten; Häme, Tuomas; Andersson, Kaj; Väätäinen, Seppo; Stenberg, Pauline; Sarkeala, Janne.

Conference on remote sensing and forest monitoring: Proceedings. European Commission, Joint Research Center (JRC), 1999.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientific

TY - GEN

T1 - Sub-pixel area estimation of European forests using NOAA-AVHRR data

AU - Kennedy, Pamela

AU - Folving, Sten

AU - Häme, Tuomas

AU - Andersson, Kaj

AU - Väätäinen, Seppo

AU - Stenberg, Pauline

AU - Sarkeala, Janne

N1 - LB-NA-19530-EN-C

PY - 1999

Y1 - 1999

N2 - A map of European forests has been produced for the pan-European area. In the database, the forest area within each NOAA-AVHRR (National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer) pixel has been estimated. A new approach, presented in another paper at this conference was utilized in the estimation procedure. The method takes into account both the uncertainty of a pixel to belong to a specific ground class and the mixed ground contents of a spectral class. The image interpretation was carried out using an AVHRR image mosaic compiled from the red and near infra-red channels, for the entire pan-European area. This mosaic was composited from forty-nine AVHRR images acquired in late summer 1996. Atmospheric correction of the data was performed to the individual images using the SMAC (Simplified Method for Atmospheric Corrections) procedure. An additional BRDF (Bi-directional Reflectance Distribution Function) correction was made to each image. The reflectance mosaic was computed using the weighted mean of the reflectance values of cloud-free pixels. The CORINE Land Cover database was used to represent the ground information. This study fulfils some of the key objectives of the FIRS (Forest Information from Remote Sensing) Project of the Space Applications Institute (SAI) at the Joint Research Centre, Ispra, of the European Commission. In particular, the work represents an attempt to improve upon the reliability of existing mapped information for Europe. Firstly, the method results in a continuous variable of forest probability representing an estimate of forest area for each pixel. Secondly, the likelihood of under-estimating the forest cover in areas where the forest is fragmented or over-estimating if the cover is uniform and homogeneous, is reduced. Thirdly, the resulting image database could also be utilized to estimate other forest characteristics, if relevant ground data are available. Forest area statistics derived from the probability database for Italy and France were compared with area estimates taken from EUROSTAT's (Statistical Office of the European Communities) database for 1995. The correlation coefficients were found to be 0.89 and 0.85 for Italy and France respectively.

AB - A map of European forests has been produced for the pan-European area. In the database, the forest area within each NOAA-AVHRR (National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer) pixel has been estimated. A new approach, presented in another paper at this conference was utilized in the estimation procedure. The method takes into account both the uncertainty of a pixel to belong to a specific ground class and the mixed ground contents of a spectral class. The image interpretation was carried out using an AVHRR image mosaic compiled from the red and near infra-red channels, for the entire pan-European area. This mosaic was composited from forty-nine AVHRR images acquired in late summer 1996. Atmospheric correction of the data was performed to the individual images using the SMAC (Simplified Method for Atmospheric Corrections) procedure. An additional BRDF (Bi-directional Reflectance Distribution Function) correction was made to each image. The reflectance mosaic was computed using the weighted mean of the reflectance values of cloud-free pixels. The CORINE Land Cover database was used to represent the ground information. This study fulfils some of the key objectives of the FIRS (Forest Information from Remote Sensing) Project of the Space Applications Institute (SAI) at the Joint Research Centre, Ispra, of the European Commission. In particular, the work represents an attempt to improve upon the reliability of existing mapped information for Europe. Firstly, the method results in a continuous variable of forest probability representing an estimate of forest area for each pixel. Secondly, the likelihood of under-estimating the forest cover in areas where the forest is fragmented or over-estimating if the cover is uniform and homogeneous, is reduced. Thirdly, the resulting image database could also be utilized to estimate other forest characteristics, if relevant ground data are available. Forest area statistics derived from the probability database for Italy and France were compared with area estimates taken from EUROSTAT's (Statistical Office of the European Communities) database for 1995. The correlation coefficients were found to be 0.89 and 0.85 for Italy and France respectively.

M3 - Conference article in proceedings

BT - Conference on remote sensing and forest monitoring

PB - European Commission, Joint Research Center (JRC)

ER -

Kennedy P, Folving S, Häme T, Andersson K, Väätäinen S, Stenberg P et al. Sub-pixel area estimation of European forests using NOAA-AVHRR data. In Conference on remote sensing and forest monitoring: Proceedings. European Commission, Joint Research Center (JRC). 1999