Abstract
The paper proposes a novel approach for change detection
from image time series. In this approach changes are
detected from evaluated distances between the (possibly
multivariate) distributions of pixel values. Basing
change detection on these distributions facilitates,
e.g., joint analysis of images having different
resolutions and comparisons of smaller areas against
larger images. Furthermore, clouded areas can be excluded
from each image separately, allowing the data in the
remaining pixels to be utilized independent on the
whether the corresponding pixels have been covered by
clouds in the other images in the time series. In the
paper the proposed method is applied to forest cover
change detection using Landsat data covering Mexico.
Original language | English |
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Title of host publication | Proceedings of ESA Living Planet Symposium |
Subtitle of host publication | SeaSAR 2013 |
Editors | Leny Ouwehand |
Publisher | European Space Agency (ESA) |
Number of pages | 1 |
ISBN (Print) | 978-9-2922-1286-5 |
Publication status | Published - 2013 |
MoE publication type | A4 Article in a conference publication |
Event | ESA Living Planet Symposium 2013 - Edinburgh, United Kingdom Duration: 9 Sept 2013 → 13 Sept 2013 Conference number: ESA SP-722 |
Conference
Conference | ESA Living Planet Symposium 2013 |
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Country/Territory | United Kingdom |
City | Edinburgh |
Period | 9/09/13 → 13/09/13 |
Keywords
- time series
- change detection