Open AccessA STUDY ON PRODUCING HIGHLY RELIABILE REFERENCE DATA SETS FOR GLOBAL LAND COVER VALIDATION
Author(s) -
N. Soyama,
K. Muramatsu,
M. Daigo,
F. Ochiai,
N. Fujiwara
Publication year - 2016
Publication title -
the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.264
H-Index - 71
eISSN - 1682-1777
pISSN - 1682-1750
DOI - 10.5194/isprsarchives-xli-b8-1207-2016
Subject(s) - reference data , computer science , land cover , reliability (semiconductor) , cover (algebra) , ground truth , data mining , fluxnet , remote sensing , information retrieval , land use , artificial intelligence , geography , ecology , mechanical engineering , power (physics) , physics , eddy covariance , quantum mechanics , ecosystem , engineering , biology
Validating the accuracy of land cover products using a reliable reference dataset is an important task. A reliable reference dataset is produced with information derived from ground truth data. Recently, the amount of ground truth data derived from information collected by volunteers has been increasing globally. The acquisition of volunteer-based reference data demonstrates great potential. However information given by volunteers is limited useful vegetation information to produce a complete reference dataset based on the plant functional type (PFT) with five specialized forest classes. In this study, we examined the availability and applicability of FLUXNET information to produce reference data with higher levels of reliability. FLUXNET information was useful especially for forest classes for interpretation in comparison with the reference dataset using information given by volunteers.