Joint supervised classification and reconstruction of irregularly sampled satellite image times series

A Constantin, M Fauvel, S Girard - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Recent satellite missions have led to a huge amount of Earth observation data, most of them
being freely available. In such a context, satellite image time series have been used to study …

Pixel‐based Classification Techniques for Satellite Image Time Series

C Pelletier, S Valero - Change Detection and Image Time Series …, 2021 - books.google.com
Satellite image time series have proven to be an effective tool for monitoring vegetation
dynamics, resources and the effects of climate change. These multitemporal data offer …

Filtering mislabeled data for improving time series classification

C Pelletier, S Valero, J Inglada… - … workshop on the …, 2017 - ieeexplore.ieee.org
The supervised classification of optical image time series allow the production of accurate
land cover maps over large areas. However, the precision yielded by learning algorithms …

[PDF][PDF] Classifying Land Cover from Satellite Images Using Time Series Analytics.

P Schäfer, D Pflugmacher, P Hostert, U Leser - EDBT/ICDT Workshops, 2018 - ceur-ws.org
The Earth's surface is continuously observed by satellites, leading to large multi-spectral
image data sets of increasing spatial resolution and temporal density. One important …

Classification of time series of multispectral images with limited training data

B Demir, F Bovolo, L Bruzzone - IEEE Transactions on Image …, 2013 - ieeexplore.ieee.org
Image classification usually requires the availability of reliable reference data collected for
the considered image to train supervised classifiers. Unfortunately when time series of …

Analysis of multitemporal classification techniques for forecasting image time series

R Flamary, M Fauvel, M Dalla Mura… - IEEE Geoscience and …, 2014 - ieeexplore.ieee.org
The classification of an annual time series by using data from past years is investigated in
this letter. Several classification schemes based on data fusion, sparse learning, and …

Cost-sensitive self-paced learning with adaptive regularization for classification of image time series

H Li, J Li, Y Zhao, M Gong, Y Zhang… - IEEE Journal of Selected …, 2021 - ieeexplore.ieee.org
The classification of image time series has potential significance in the field of land-cover
analysis with the increasing number of remote sensing images. The key problem of the …

Stmetrics: a python package for satellite image time-series feature extraction

AR Soares, HN Bendini, DV Vaz… - IGARSS 2020-2020 …, 2020 - ieeexplore.ieee.org
Producing reliable land use and land cover maps to support the deployment and operation
of public policies is a necessity, especially when environmental management and economic …

Spatio-temporal reasoning for the classification of satellite image time series

F Petitjean, C Kurtz, N Passat, P Gançarski - Pattern Recognition Letters, 2012 - Elsevier
Satellite image time series (SITS) analysis is an important domain with various applications
in land study. In the coming years, both high temporal and high spatial resolution SITS will …

Aggregation of Sentinel-2 time series classifications as a solution for multitemporal analysis

S Lewiński, A Nowakowski… - Image and Signal …, 2017 - spiedigitallibrary.org
The general aim of this work was to elaborate efficient and reliable aggregation method that
could be used for creating a land cover map at a global scale from multitemporal satellite …