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Automated land cover change detection: the quest for meaningful high temporal time series extraction
conference contribution
posted on 2023-05-23, 07:36 authored by Brian SalmonBrian Salmon, Jan OlivierJan Olivier, Kleynhans, W, Wessels, KJ, van den Bergh, FAn automated land cover change detection method is proposed that uses coarse resolution hyper-temporal satellite time series data. The study compared two different unsupervised clustering approaches that operate on the short term Fourier transform coefficients of subsequences of 8-day composite MODerate-resolution Imaging Spectroradiometer (MODIS) surface reflectance data that were extracted with a temporal sliding window. The method uses a feature extraction process that creates meaningful sequential time series that can be analyzed and processed for change detection. The method was evaluated on real and simulated land cover change examples and obtained a change detection accuracy higher than 76% on real land cover conversion and more than 70% on simulated land cover conversion.
History
Publication title
IEEE International Geoscience and Remote Sensing SymposiumPagination
1968 - 1971ISBN
978-1-4244-9564-1Department/School
School of EngineeringPublisher
IEEEPlace of publication
USAEvent title
IEEE International Geoscience and Remote Sensing SymposiumEvent Venue
Hawaii, USADate of Event (Start Date)
2010-07-25Date of Event (End Date)
2010-07-30Rights statement
Copyright 2012 IEEERepository Status
- Restricted