DyNeXtFusion-UNet： A remote sensing image cultivated land semantic segmentation model based on content-driven dynamic upsampling and feature fusion

Liang Jiaping; Zhong Yuhui; Wang Xiaoxuan; Yan Chaohui; Yang Qiliang; Li Jie; Wang Liuyanjun

doi:10.11834/jrs.20266072

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DyNeXtFusion-UNet： A remote sensing image cultivated land semantic segmentation model based on content-driven dynamic upsampling and feature fusion
“The rapid and accurate identification of arable land resources is an important foundation for supporting arable land protection, use control, and 'double non' supervision work. The research progress in the field of remote sensing image arable land segmentation was introduced. The research team established the DyNeXtFusion UNet semantic segmentation model to provide a solution to the problems of incomplete arable land parcels and insufficient boundary continuity.”
- role：First author第一作者
- Affiliation：
  Faculty of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming 650500, China
  Yunnan Key Laboratory of Efficient Utilization of Agricultural Water Resources and Intelligent Control, Kunming 650500, China
  Yunnan International Joint Laboratory of Intelligent Agricultural Engineering Technology and Equipment, Kunming 650500, China
  Yunnan Intelligent Water-Fertilizer-Pesticide Integration Technology and Equipment Innovation Team, Kunming 650500, China
  Seasonal Arid Region, Water-Soil-Crop System Observation and Research Station of Yunnan Province, Kunming 650500, China
- Email：liangjpxaut@163.com
- Introduction：梁嘉平，研究方向为农业信息化。E-mail： liangjpxaut@163.com
Liang Jiaping
12345 * ,
- Affiliation：
  Faculty of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming 650500, China
  Yunnan Key Laboratory of Efficient Utilization of Agricultural Water Resources and Intelligent Control, Kunming 650500, China
  Yunnan International Joint Laboratory of Intelligent Agricultural Engineering Technology and Equipment, Kunming 650500, China
  Yunnan Intelligent Water-Fertilizer-Pesticide Integration Technology and Equipment Innovation Team, Kunming 650500, China
  Seasonal Arid Region, Water-Soil-Crop System Observation and Research Station of Yunnan Province, Kunming 650500, China
Zhong Yuhui
12345 * ,
- role：Corresponding author通信作者
- Affiliation：
  Faculty of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming 650500, China
  Yunnan Key Laboratory of Efficient Utilization of Agricultural Water Resources and Intelligent Control, Kunming 650500, China
  Yunnan International Joint Laboratory of Intelligent Agricultural Engineering Technology and Equipment, Kunming 650500, China
  Yunnan Intelligent Water-Fertilizer-Pesticide Integration Technology and Equipment Innovation Team, Kunming 650500, China
  Seasonal Arid Region, Water-Soil-Crop System Observation and Research Station of Yunnan Province, Kunming 650500, China
- Email：112004010002@home.hpu.edu.cn
- Introduction：王枭轩，研究方向为农业定量遥感与语义分割。E-mail： 112004010002@home.hpu.edu.cn
Wang Xiaoxuan
12345 * ,
- Affiliation：
  Faculty of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming 650500, China
  Yunnan Key Laboratory of Efficient Utilization of Agricultural Water Resources and Intelligent Control, Kunming 650500, China
  Yunnan International Joint Laboratory of Intelligent Agricultural Engineering Technology and Equipment, Kunming 650500, China
  Yunnan Intelligent Water-Fertilizer-Pesticide Integration Technology and Equipment Innovation Team, Kunming 650500, China
  Seasonal Arid Region, Water-Soil-Crop System Observation and Research Station of Yunnan Province, Kunming 650500, China
Yan Chaohui
12345 * ,
- Affiliation：
  Faculty of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming 650500, China
  Yunnan Key Laboratory of Efficient Utilization of Agricultural Water Resources and Intelligent Control, Kunming 650500, China
  Yunnan International Joint Laboratory of Intelligent Agricultural Engineering Technology and Equipment, Kunming 650500, China
  Yunnan Intelligent Water-Fertilizer-Pesticide Integration Technology and Equipment Innovation Team, Kunming 650500, China
  Seasonal Arid Region, Water-Soil-Crop System Observation and Research Station of Yunnan Province, Kunming 650500, China
Yang Qiliang
12345 * ,
- Affiliation：
  Faculty of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming 650500, China
  Yunnan Key Laboratory of Efficient Utilization of Agricultural Water Resources and Intelligent Control, Kunming 650500, China
  Yunnan International Joint Laboratory of Intelligent Agricultural Engineering Technology and Equipment, Kunming 650500, China
  Yunnan Intelligent Water-Fertilizer-Pesticide Integration Technology and Equipment Innovation Team, Kunming 650500, China
  Seasonal Arid Region, Water-Soil-Crop System Observation and Research Station of Yunnan Province, Kunming 650500, China
Li Jie
12345 * ,
- Affiliation：
  Faculty of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming 650500, China
  Yunnan Key Laboratory of Efficient Utilization of Agricultural Water Resources and Intelligent Control, Kunming 650500, China
  Yunnan International Joint Laboratory of Intelligent Agricultural Engineering Technology and Equipment, Kunming 650500, China
  Yunnan Intelligent Water-Fertilizer-Pesticide Integration Technology and Equipment Innovation Team, Kunming 650500, China
  Seasonal Arid Region, Water-Soil-Crop System Observation and Research Station of Yunnan Province, Kunming 650500, China
Wang Liuyanjun
12345 *
Pages: 1-13(2026)
DOI：10.11834/jrs.20266072
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DyNeXtFusion-UNet： A remote sensing image cultivated land semantic segmentation model based on content-driven dynamic upsampling and feature fusion

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DyNeXtFusion-UNet： A remote sensing image cultivated land semantic segmentation model based on content-driven dynamic upsampling and feature fusion

Liang Jiaping

Zhong Yuhui

Wang Xiaoxuan

Yan Chaohui

Yang Qiliang

Li Jie

Wang Liuyanjun

DOI：10.11834/jrs.20266072

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