CLASSIFICATION OF WHEAT AND BARLEY FIELDS USING SENTINEL-1 BACKSCATTER

被引：2

作者：

Pfeil, Isabella ^{[1
,2
]}

Reuss, Felix ^{[1
]}

Vreugdenhil, Mariette ^{[1
,2
]}

Navacchi, Claudio ^{[1
]}

Wagner, Wolfgang ^{[1
,2
]}

机构：

[1] TU Wien, Dept Geodesy & Geoinformat, Vienna, Austria

[2] TU Wien, Ctr Water Resource Syst, Vienna, Austria

来源：

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

关键词：

CROP CLASSIFICATION; TIME-SERIES;

D O I：

10.1109/IGARSS39084.2020.9323560

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The knowledge of the distribution of crop types is of great importance to numerous applications at regional to global scales. Different techniques, including microwave remote sensing methods, have been developed for automatized, accurate crop mapping, however, the discrimination of crops with similar morphology and phenology remains a challenge. In this study, we investigate how to distinguish wheat and barley fields by applying statistical methods and a long-short term memory network to backscatter observed by the C-band SAR instrument onboard the Sentinel-1 satellite.

引用

页码：140 / 143

页数：4

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