STMETRICS: A PYTHON']PYTHON PACKAGE FOR SATELLITE IMAGE TIME-SERIES FEATURE EXTRACTION

被引：1

作者：

Soares, Anderson R. ^{[1
]}

Bendini, Hugo N. ^{[1
]}

Vaz, Daiane V. ^{[1
]}

Uehara, Tatiana D. T. ^{[1
]}

Neves, Alana K. ^{[1
]}

Lechler, Sarah ^{[2
]}

Korting, Thales S. ^{[1
]}

Fonseca, Leila M. G. ^{[1
]}

机构：

[1] Brazils Natl Inst Space Res INPE, Gen Coordinat Earth Observat OBT, Av dos Astronautas 1758, Sao Jose Dos Campos, SP, Brazil

[2] Univ Munster, Inst Geoinformat, Munster, Germany

来源：

IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2020年

基金：

巴西圣保罗研究基金会;

关键词：

time-series; !text type='python']python[!/text; multi-temporal features; remote sensing; AREA;

D O I：

10.1109/IGARSS39084.2020.9323346

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：2061 / 2064

页数：4

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