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Conference papers
Classification of MODIS Time Series with Dense Bag-of-Temporal-SIFT-Words: Application to Cropland Mapping in the Brazilian Amazon
Abstract : Mapping croplands is a challenging problem in a context of climate change and evolving agricultural calendars. Classification based on MODIS vegetation index time series is performed in order to map crop types in the Brazilian state of Mato Grosso. We used the recently developed Dense Bag-of-Temporal-SIFT-Words algorithm, which is able to capture temporal locality of the data. It allows the accurate detection of around 70% of the agricultural areas. It leads to better classification rates than a baseline algorithm, discriminating more accurately classes with similar profiles.
Cited literature [12 references]
https://halshs.archives-ouvertes.fr/halshs-01343211
Contributor : Romain Tavenard Connect in order to contact the contributor
Submitted on : Thursday, July 7, 2016 - 5:55:42 PM
Last modification on : Wednesday, November 17, 2021 - 12:31:03 PM
Contributor : Romain Tavenard Connect in order to contact the contributor
Submitted on : Thursday, July 7, 2016 - 5:55:42 PM
Last modification on : Wednesday, November 17, 2021 - 12:31:03 PM
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classification-modis-time.pdf
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