Dataset of Identifying Aircraft Groups by Remote Sensing Images

CHEN Junyu1,2LI Haiwei*1ZHANGGeng1WANG Shuang1CHEN Tieqiao1

1Xi’an Institute of Optics and Precision Mechanics，Chinese Academy of Sciences，Xi’an 710119，China2University of Chinese Academy of Sciences，Beijing 100049，China

DOI:10.3974/geodb.2020.03.25.V1

Published:Jun. 2020

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Key Words：

Classification of remote sensing images,dataset of aircraft classification,Google Earth,Attention Mechanism

Abstract：

The aircraft is a typical object in remote sensing images. The authors selected several airports around the world and 3594 airplane images based on the public datasets - DIOR, UCAS_AOD, NWPU VHR-10, DOTA and Google earth images. Then seven aircraft groups in terms of wings and propellers based on the attention mechanism were identified. Following, the fourteen sub-groups in terms of color of aircraft and engine position were recognized. Dataset of Identifying Aircraft Groups by Remote Sensing Images include: (1) Swept-back wing aircraft; (2) Swept-back aircraft with leading edge; (3) Forward-swept wing airplane with trailing edge; (4) Delta-wing aircraft; (5) Flat-wing aircraft; (6) Propeller aircraft; (7) Helicopter. The dataset is archived in .png data format, and consists of 3594 data files with data size of 69.3MB (compressed to one single file with 69.3MB).

Foundation Item：

Chinese Academy of Sciences (XAB2017B19)

Data Citation：

CHEN Junyu,LI Haiwei*,ZHANGGeng,WANG Shuang,CHEN Tieqiao.Dataset of Identifying Aircraft Groups by Remote Sensing Images[DB/J].Global Change Data Repository,2020.DOI:10.3974/geodb.2020.03.25.V1.

Data Product: