Land Cover Extraction in the Typical Black Soil Region of Northeast China Using High-Resolution Remote Sensing Imagery

Binbin Ding, Jianlin Tian (), Yong Wang () and Ting Zeng
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Binbin Ding: College of Civil Engineering and Architecture, Jishou University, Zhangjiajie 427000, China
Jianlin Tian: College of Civil Engineering and Architecture, Jishou University, Zhangjiajie 427000, China
Yong Wang: State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Ting Zeng: College of Civil Engineering and Architecture, Jishou University, Zhangjiajie 427000, China

Land, 2023, vol. 12, issue 8, 1-16

Abstract: The black soil region of Northeast China is one of the most fertile soil areas in the world and serves as a crucial grain-producing region in China. However, excessive development and improper utilization have led to severe land use issues. Conducting land cover extraction in this region can provide essential data support for monitoring and managing natural resources effectively. This article utilizes GF-6 remote sensing imagery as the data source and adopts the U-Net model as the backbone network. By incorporating residual modules and adjusting the convolution kernel size, a high-precision land cover extraction model called RAT-UNet is developed. Taking Qiqihar City as an example, the RAT-UNet model is applied to extract land cover information. The results are as follows: (1) The RAT-UNet model achieves high accuracy in land cover extraction, with the following accuracies for different land types: cropland (95.11%), forestland (93.61%), grassland (68.41%), water bodies (94.67%), residential land (89.40%), and unused land (87.25%). (2) The land cover extraction performance of the RAT-UNet model is superior to DeepLabV3, U-Net, SegNet, and LinkNet34 models. This research outcome provides methodological support for the intelligent and high-precision extraction of land cover information and also offers timely data for Qiqihar city’s land use planning.

Keywords: U-Net model; RAT-UNet model; land cover extraction; GF-6; Qiqihar City (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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