@inproceedings{8326d356d3df4b6982e77c25fa754233,
title = "Comparison between pixel and region based sits analysis approaches",
abstract = "Temporal sequences of images called Satellite Image Time Series (SITS) allow land cover monitoring and classification by affording a large amount of images. Many approaches attempt to exploit this multi-temporal data in order to extract relevant information such as classification-based techniques. In this paper we compare low and high levels classification-based approaches that aim to reveal the SITS pixels or regions spatio-temporal evolutions through a temporal map. The first approach is a graph region-based classification approach that proved its performances for Very High Resolution (VHR) optical SITS analysis. The second one is a change detection pixel-based approach that has been successfully applied for SAR SITS multi-temporal classification. The experimental results have been conducted on both synthesized and real data in order to compare those approaches and conclude about their accuracies.",
keywords = "Satellite Image Time Series SITS, Spatio-temporal classification, change detection, graph kernel",
author = "S. Rejichi and F. Chaabane and F. Tupin",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017 ; Conference date: 23-07-2017 Through 28-07-2017",
year = "2017",
month = dec,
day = "1",
doi = "10.1109/IGARSS.2017.8127357",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1934--1937",
booktitle = "2017 IEEE International Geoscience and Remote Sensing Symposium",
}