Abstract

WHU-Hi dataset (Wuhan UAV-borne hyperspectral image) is collected and shared by the RSIDEA research group of Wuhan University, and it could serve as a benchmark dataset for precise crop classification and hyperspectral image classification studies. The WHU-Hi dataset contains three individual UAV-borne hyperspectral datasets: WHU-Hi-LongKou, WHU-Hi-HanChuan, and WHU-Hi-HongHu. All the datasets were acquired in farming areas with various crop types in Hubei province, China, via a Headwall Nano-Hyperspec sensor mounted on a UAV platform. Compared with spaceborne and airborne hyperspectral platforms, unmanned aerial vehicle (UAV)-borne hyperspectral systems can acquire hyperspectral imagery with a high spatial resolution (which we refer to here as H2 imagery). The research was published in Remote Sensing of Environment.

Description

The WHU-Hi dataset preprocessing included radiometric calibration and geometric correction, which were undertaken in the HyperSpec software provided by the instrument manufacturer. For the radiometric calibration, the raw digital number values were converted into radiance values by the laboratory calibration parameters of the sensor.

WHU-Hi-LongKou dataset

The WHU-Hi-LongKou dataset was acquired from 13:49 to 14:37 on July 17, 2018, in Longkou Town, Hubei province, China, with an 8-mm focal length Headwall Nano-Hyperspec imaging sensor equipped on a DJI Matrice 600 Pro (DJI M600 Pro) UAV platform. During the data collection, the weather was clear and cloudless, the temperature was about 36°C, and the relative air humidity was about 65%. The study area is a simple agricultural scene, which contains six crop species: corn, cotton, sesame, broad-leaf soybean, narrow-leaf soybean, and rice. The UAV flew at an altitude of 500 m, the size of the imagery is 550 x 400 pixels, there are 270 bands from 400 to 1000 nm, and the spatial resolution of the UAV-borne hyperspectral imagery is about 0.463 m.

No.	Class name	Samples
C1	Corn	34511
C2	Cotton	8374
C3	Sesame	3031
C4	Broad-leaf soybean	63212
C5	Narrow-leaf soybean	4151
C6	Rice	11854
C7	Water	67056
C8	Roads and houses	7124
C9	Mixed weed	5229

WHU-Hi-HanChuan dataset

The WHU-Hi-HanChuan dataset was acquired from 17:57 to 18:46 on June 17, 2016, in Hanchuan, Hubei province, China, with an 17-mm focal length Headwall Nano-Hyperspec imaging sensor equipped on a Leica Aibot X6 UAV V1 platform. During the data collection, the weather was clear and cloudless, the temperature was about 30°C, and the relative air humidity was about 70%. The study area is a rural-urban fringe zone with buildings, water, and cultivated land, which contains seven crop species: strawberry, cowpea, soybean, sorghum, water spinach, watermelon, and greens. The UAV flew at an altitude of 250 m, the size of the imagery is 1217 x 303 pixels, there are 274 bands from 400 to 1000 nm, and the spatial resolution of the UAV-borne hyperspectral imagery is about 0.109 m. Notably, since the WHU-Hi-HanChuan dataset was acquired during the afternoon when the solar elevation angle was low, there are many shadow-covered areas in the image.

No.	Class name	Samples
C1	Strawberry	44735
C2	Cowpea	22753
C3	Soybean	10287
C4	Sorghum	5353
C5	Water spinach	1200
C6	Watermelon	4533
C7	Greens	5903
C8	Trees	17978
C9	Grass	9469
C10	Red roof	10516
C11	Gray roof	16911
C12	Plastic	3679
C13	Bare soil	9116
C14	Road	18560
C15	Bright object	1136
C16	Water	75401

WHU-Hi-HongHu dataset

The WHU-Hi-HongHu dataset was acquired from 16:23 to 17:37 on November 20, 2017, in Honghu City, Hubei province, China, with a 17-mm focal length Headwall Nano-Hyperspec imaging sensor equipped on a DJI Matrice 600 Pro UAV platform. During the data collection, the weather was cloudy, the temperature was about 8°C, and the relative air humidity was about 55%. The experimental area is a complex agricultural scene with many classes of crops, and different cultivars of the same crop are also planted in the region, including Chinese cabbage and cabbage, and Brassica chinensis and small Brassica chinensis. Notably, the region is planted with different cultivars of the same crop type; for example, Chinese cabbage/cabbage and brassica chinensis/small brassica chinensis. The UAV flew at an altitude of 100 m, the size of the imagery is 940 x 475 pixels, there are 270 bands from 400 to 1000 nm, and the spatial resolution of the UAV-borne hyperspectral imagery is about 0.043 m.

No.	Class name	Samples
C1	Red roof	14041
C2	Road	3512
C3	Bare soil	21821
C4	Cotton	163285
C5	Cotton firewood	6218
C6	Rape	44557
C7	Chinese cabbage	24103
C8	Pakchoi	4054
C9	Cabbage	10819
C10	Tuber mustard	12394
C11	Brassica parachinensis	11015
C12	Brassica chinensis	8954
C13	Small Brassica chinensis	22507
C14	Lactuca sativa	7356
C15	Celtuce	1002
C16	Film covered lettuce	7262
C17	Romaine lettuce	3010
C18	Carrot	3217
C19	White radish	8712
C20	Garlic sprout	3486
C21	Broad bean	1328
C22	Tree	4040

Credits

The dataset was originally collected from the RSIDEA website at this link. The Matlab version of this dataset is also available on Kaggle.

Copyright

The copyright belongs to Intelligent Data Extraction, Analysis and Applications of Remote Sensing(RSIDEA) academic research group, State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing (LIESMARS), Wuhan University. The WHU-Hi dataset can be used for academic purposes only and need to cite the following papers, but any commercial use is prohibited. Otherwise, RSIDEA of Wuhan University reserves the right to pursue legal responsibility.

[1] Y. Zhong, X. Hu, C. Luo, X. Wang, J. Zhao, and L. Zhang, "WHU-Hi: UAV-borne hyperspectral with high spatial resolution (H2) benchmark datasets and classifier for precise crop identification based on deep convolutional neural network with CRF", Remote Sens. Environ., vol. 250, pp. 112012, 2020.
[2] Y. Zhong, X. Wang, Y. Xu, S. Wang, T. Jia, X. Hu, J. Zhao, L. Wei, and L. Zhang, "Mini-UAV-borne hyperspectral remote sensing: From observation and processing to applications", IEEE Geosci. Remote Sens. Mag., vol. 6, no. 4, pp. 46-62, Dec. 2018.

If you have any the problem or feedback in using WHU-Hi dataset, please contact:
Dr. Hu: whu_huxin@whu.edu.cn
Dr. Wang: wangxinyu@whu.edu.cn
Prof. Zhong: zhongyanfei@whu.edu.cn