An Alternative Method of Cultivated Land Identification and Its Actual Change from 2009 to 2019: A Case Study of Gaochun, China

Zhuoran Jiang, Ming Jiang, Yahua Wang (), Can Ma and Weifeng Qiao
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Zhuoran Jiang: School of Geography, Nanjing Normal University, Nanjing 210023, China
Ming Jiang: School of Geography, Nanjing Normal University, Nanjing 210023, China
Yahua Wang: School of Geography, Nanjing Normal University, Nanjing 210023, China
Can Ma: School of Geography, Nanjing Normal University, Nanjing 210023, China
Weifeng Qiao: School of Geography, Nanjing Normal University, Nanjing 210023, China

Land, 2023, vol. 12, issue 3, 1-19

Abstract: As the largest developing country, China has permanently attached great importance to cultivated land protection. However, due to the different rules of cultivated land identification in the second and third national land surveys, the cultivated land area in the two surveys has changed greatly. Some agricultural lands in the south, such as plantations, forests, grasslands, aquaculture ponds, etc., belonged to cultivated land during the second survey, but they were identified as non-cultivated land in the third national land survey. This change has led to a sharp reduction in the area of cultivated land in some places. In order to calculate the actual change in the area of cultivated land since the second survey and provide a reasonable basis for the standard of cultivated land protection, this paper takes Gaochun District, a developed area in China, as an example; interprets the images of the second national land survey period with the deep learning network HRNet; and compares the results with the second and third national land survey rules. The results show that the actual reduction of cultivated land in Gaochun District in the past ten years accounts for 35.1% of the reduction of cultivated land in the two land surveys, while the reduction of cultivated land caused by the change of cultivated land identification rules accounts for 64.9% of the reduction of cultivated land in the two land surveys, indicating that the significant reduction in local cultivated land was mainly caused by the changes in the rules, and these cultivated land reduction behaviors existed before the second survey.

Keywords: cultivated land protection; deep learning; national land survey; change of cultivated land rules (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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