@inbook{0ba40e3f6d1c4d69879ece9a72f387b0,
title = "Clearcut Detection between Aerial and Satellite Imagery Supporting Species-wise Forest Variable Estimates",
abstract = "This study is part of the on-going NewForest project, whose objective is to develop remote sensing data analysis methods for producing species-wise forest variable estimates with accuracy that is adequate for operational forest inventory. Species-wise forest estimates relies on individual treetop locations detection from the remote sensing imagery. As ground data used for validation has been acquired at a different date as the satellite and aerial imagery, one of the first step was to identify clearcuts and thinning areas that occurred within the temporal span of all gathered data. This was done using image-based change detection.",
author = "Matthieu Molinier and Heikki Astola",
note = "Project code: 32655",
year = "2010",
language = "English",
isbn = "978-952-60-3054-8",
series = "TKK Radio Science and Engineering Publications",
publisher = "Helsinki University of Technology",
number = "Report R13",
pages = "98",
booktitle = "Proceedings of Nordic Remote Sensing Days 2009",
address = "Finland",
}