Slide 1

Production, visualization and analysis of large volumes of remote sensing images modeled as multidimensional data cubes for the entire Brazilian territory.

Stmetrics: A Python Package for Satellite Image Time-Series Feature Extraction

by Anderson R. Soares¹; Hugo N. Bendini¹; Daiane V. Vaz¹; Tatiana D. T. Uehara¹; Alana K. Neves¹; Sarah Lechler²; Thales S. Körting¹; Leila M. G. Fonseca¹

¹General Coordination of Earth Observation – OBT, Brazil’s National Institute for Space Research (INPE), São José dos Campos, SP, Brazil

²Institute for Geoinformatics, University of Muenster

DOI: https://doi.org/10.1109/IGARSS39084.2020.9323346

Publisher: IEEE Explorer | Published: 2 Oct. 2020

Published in: IGARSS 2020 – 2020 IEEE International Geoscience and Remote Sensing Symposium

Abstract

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 development are considered. To increase the accuracy of these maps, satellite image time-series have been used, as they allow the understanding of land cover dynamics through the time. This paper presents the stmetrics, a python package that provides the extraction of state-of-the-art time-series features. These features can be used for remote sensing time-series image classification and analysis. stmetrics aims to be an easy-to-use package. The package is available under the GNU GPL software license, and the full source code is available for download at: github.com/andersonreisoares/stmetrics.

Keywords: time-series, python, multi-temporal features, remote sensing

Share and Cite

Soares, A. R.; Bendini, H. N.; Vaz, D. V.; Uehara, T. D. T.; Neves, A. K.; Lechler, Sarah; Korting, T. S.; Fonseca, L. M. G. STMETRICS: A Python Package for Satellite Image Time-Series Feature Extraction. In: IGARSS 2020: 2020 IEEE International Geoscience and Remote Sensing Symposium. Virtual Symposium. September 26 – October 2, 2020 2020.

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