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Experimental Dataset of Identifying Road Material Using GF-6 Images

CUI Yuping1
1 China Highway Engineering Consulting Corporation,Beijing 100097,China


Published:Aug. 2022

Visitors:5310       Data Files Downloaded:145      
Data Downloaded:67366.62 MB      Citations:

Key Words:

road material,machine learning,GF-6,Langfang


Based on the GF-6 images, the spectral characteristic indexes - spectral difference index, spectral ratio index, spectral variance index and spectral normalization index - were calculated in the experimental area in Langfang, Hebei Province of China. The sample data of road material was obtained based on Google Earth images and Baidu Maps. The machine learning technology was used to develop the experimental dataset of identifying road material from GF-6 images. Compared with the samples, the road material identification accuracy is 80.07%, and the Kappa coefficient is 0.70. The dataset consists of: (1) spectral characteristic index data; (2) road material sample data; (3) road material identification result. The dataset is archived in .dat, .shp. and .xlsx formats, and consists of 16 data files with data size of 3.69 GB (compressed into 4 files, 1.62 GB).Browse

Foundation Item:

GF-6 (07-Y30B03-9001-19/21, 87-Y50G28-9001-22/23);

Data Citation:

CUI Yuping. Experimental Dataset of Identifying Road Material Using GF-6 Images[J/DB/OL]. Digital Journal of Global Change Data Repository, 2022.

CUI Yuping. Methods and results of identifying a road material dataset from GF-6 remote sensing data in the Langfang area [J]. Journal of Global Change Data & Discovery, 2022, 6(4): 607–618.


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Data Product:

ID Data Name Data Size Operation
1 1_SpectralCharacteristicIndex_SDI_SVI.rar 210870.80KB
2 1_SpectralCharacteristicIndex_SNI.rar 757602.06KB
3 1_SpectralCharacteristicIndex_SRI.rar 730480.19KB
4 2&3_SampleData_RoadMaterial.rar 1705.59KB