Dr. Junchuan Yu Profile

Dr. Junchuan Yu

at AGRS

SPIE Involvement:

Author

Publications (6)

Proceedings Article | 24 November 2021 Paper

Crop extraction combined with airborne hyperspectral images and deep convolutional neural network

Qiang Li, Zhitao Shao, Yaping Liu, Tian Li, Xiyao Wang, Junchuan Yu

Proceedings Volume 12065, 120653T (2021) https://doi.org/10.1117/12.2607131

KEYWORDS: RGB color model, Hyperspectral imaging, Spatial resolution, Data modeling, Principal component analysis, Convolutional neural networks, Remote sensing, Image classification, Feature extraction, Data acquisition

Read Abstract +

SPIE Journal Paper | 20 September 2021 Open Access

3D autoencoder algorithm for lithological mapping using ZY-1 02D hyperspectral imagery: a case study of Liuyuan region

Junchuan Yu, Liang Zhang, Qiang Li, Yichuan Li, Wei Huang, Zhiwei Sun, Yanni Ma, Peng He

JARS, Vol. 15, Issue 04, 042610, (September 2021) https://doi.org/10.1117/12.10.1117/1.JRS.15.042610

KEYWORDS: Hyperspectral imaging, 3D image processing, Machine learning, 3D modeling, Minerals, Computer programming, Associative arrays, Satellites, Data modeling, Spatial resolution

Read Abstract +

DOWNLOAD PAPER

Proceedings Article | 12 March 2021 Paper

Multi-period dynamic evaluation of soil loss in loess area

Yanni Ma, Yichuan Li, Xian Zhang, Junchuan Yu, Rongyuan Liu, Bokun Yan, Fuping Gan, Xinfeng Dong, Na Li, Yi Guo, Juan Bai

Proceedings Volume 11763, 117637S (2021) https://doi.org/10.1117/12.2587481

Read Abstract +

The loess area is located in the middle and upper reaches of the Yellow River Basin. This area has a large area of ecologically sensitive areas and fragile areas, and it is the region with the most serious soil erosion in the country. A lot of loess is attached to the surface of the loess area, the vegetation is relatively sparse, and the seasonal rainfall is obvious. Therefore, the amount of soil erosion is large, which has a significant impact on the soil fertility of the loess area. At the same time, a large amount of soil erosion poses a huge challenge to environmental protection in the middle and lower reaches. Therefore, the problem of soil erosion is a key phenomenon that needs attention in the loess area. This paper takes the loess area of Tongwei-Zhuanglang area in Gansu Province as the research object, uses the multi-year remote sensing image classification data as the background (2000, 2005, 2010, 2015), combined with meteorological data (this data is released according to CRU The global 0.5° climate data set and the high-resolution climate data set for China released by CNERN were generated by the Delta spatial downscaling scheme in the Loess Plateau area), soil data, and soil parameter data (source 1 from the second soil census: 1 million Chinese soil maps), topographic data (DEM), vegetation coverage data, and the use of an improved universal soil loss equation (RULSE) model to carry out soil erosion in the region for many years (2000, 2005, 2010, 2015) Strength information extraction and classification. Contrast and analyze the degree of soil erosion in the area for many years, and evaluate the local soil erosion prevention measures. Studies have shown that from 2000, 2010, and 2015, the degree of soil loss gradually decreased, and the total amount of soil loss gradually decreased. However, due to the abnormally reduced precipitation in 2005, the soil erosion was generally low, which was an abnormal situation. Overall, soil erosion has continued to decrease in recent years, and the effects of soil and water conservation have been remarkable.