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    • Multiscale feature extraction model for remote sensing identification of erosion gullies in Northeast China’s black soil region： A case study of Hailun City

    • “In the field of identifying erosion gullies in the black soil area of Northeast China, experts have established a new remote sensing recognition model based on multi-scale dense dilated convolutional neural networks, providing accurate data for comprehensive land management.”
    • Vol. 28, Issue 12, Pages: 3147-3157(2024)   

      Published： 07 December 2024 ，

    • DOI： 10.11834/jrs.20243139     

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  • Feng Q L，Jiang Z H，Niu B W，Gao B B，Yang J Y and Yang K. 2024. Multiscale feature extraction model for remote sensing identification of erosion gullies in Northeast China’s black soil region： A case study of Hailun City. National Remote Sensing Bulletin， 28（12）：3147-3157 DOI： 10.11834/jrs.20243139.
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YANG Jiangyu 中国农业大学土地科学与技术学院
ZHOU Weixun 南京信息工程大学 遥感与测绘工程学院;北京师范大学 遥感科学国家重点实验室
LIU Jinglei 南京信息工程大学 遥感与测绘工程学院
PENG Daifeng 南京信息工程大学 遥感与测绘工程学院
GUAN Haiyan 南京信息工程大学 遥感与测绘工程学院
SHAO Zhenfeng 武汉大学 测绘遥感信息工程国家重点实验室
ZHANG Sheng 中国矿业大学 环境与测绘学院;中国矿业大学 人工智能研究院
LI Shanshan 中国科学院空天信息创新研究院

相关机构

School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science and Technology
State Key Laboratory of Remote Sensing Science, Beijing Normal University
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University
School of Environment Science and Spatial Informatics, China University of Mining and Technology
Artificial Intelligence Research Institute, China University of Mining and Technology
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