@inproceedings{4df173906d1b4220bbfed19c71201385,
title = "Effects of shadow correction on vegetation and land cover classification from high resolution aerial images",
abstract = "The effects of shadow correction on the classification of vegetation and land cover is studied in high resolution (10 × 10 cm) aerial images. Shadow detection reuses the feature set derived from the imagery for vegetation classification. A separate model is used to classify data in the first pass into three classes: water, land and shadows. Areas classified as shadow are then corrected using a regression based model and the shadow pixel features are recalculated and updated into the feature set. The results indicate that shadow correction can significantly improve classification results in vegetation mapping; in our case the classification accuracy increased from 35.1 to 46.1 in a shadowy test area.",
author = "Teemu Kumpum{\"a}ki and Tarmo Lipping",
year = "2016",
doi = "10.1109/IGARSS.2016.7729189",
language = "English",
publisher = "IEEE",
pages = "751--754",
booktitle = "2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)",
address = "United States",
note = "INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM ; Conference date: 02-12-2016",
}