Identifying Peach Trees in Cultivated Land Using U-Net Algorithm

Qing Li and Xueyan Zhang
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Qing Li: Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Science and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Xueyan Zhang: Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Science and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

Land, 2022, vol. 11, issue 7, 1-15

Abstract: Non-grain production has emerged as a potential threat to grain production capacity and security in China. Agricultural products with higher economic returns are beginning to replace traditional grain crops, which have relatively low economic returns on a large scale. In this study, we proposed and verified an identification method utilizing an unmanned aerial vehicle and a U-net algorithm to distinguish peach trees in cultivated land; the overall accuracy for verification and prediction were 0.90 and 0.92, respectively. Additionally, a non-grain production index was developed to assess the degree of non-grain production in target plots. The index was 76.90% and 91.38% in the projected plots, representing a high degree of non-grain production. This combination of an identification method and non-grain production index could provide efficient tools for agricultural management to inspect peach trees in cultivated land, thus replacing field measurements to achieve significant labor savings. Furthermore, this method can provide a reference for creating high-standard farmland, sustainable development of cultivated land, and policymaking.

Keywords: peach trees; non-grain production; U-net; unmanned aerial vehicle; cultivated land; land policy (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
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