Research on the index system of cultivated land quality grading based on random forest algorithm

LIN Zicong; REN Xiangning; ZHU Axing; ZHAO Xin; HU Yueming

doi:10.7671/j.issn.1001-411X.201909036

Journal of South China Agricultural University > 2020 > 41(4): 38-48. > DOI: 10.7671/j.issn.1001-411X.201909036

LIN Zicong, REN Xiangning, ZHU Axing, et al. Research on the index system of cultivated land quality grading based on random forest algorithm[J]. Journal of South China Agricultural University, 2020, 41(4): 38-48. DOI: 10.7671/j.issn.1001-411X.201909036

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Research on the index system of cultivated land quality grading based on random forest algorithm

LIN Zicong^1,,
REN Xiangning¹,
ZHU Axing^{1, 2},
ZHAO Xin¹,
HU Yueming^{1, 3, 4, ,}

1.
College of Natural Resources and Environment, South China Agricultural University/Institute of Geographic Information Engineering, South China Agricultural University/Key Laboratory of Construction Land Improvement, Ministry of Land and Resources/Guangdong Provincial Key Laboratory of Land Use and Consolidation, Guangzhou 510642, China
2.
Department of Geography, University of Wisconsin-Madison, Madison 53706, USA
3.
College of Agriculture and Animal Husbandry, Qinghai University, Xining 810016, China
4.
School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 610054, China

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Received Date: September 17, 2019
Available Online: May 17, 2023

Graphical Abstract

Abstract

Abstract

Objective
To analyze the difference of cultivated land quality in the study region, optimize the use and layout of cultivated land, and provide a reference for cultivated land protection.

Method
Taking the cultivated land in Gonghe County, Dulan County and Wulan County in Qinghai Province as the research object, the influencing factors of cultivated land quality were collected based on the history and existing literature, and the random forest algorithm and correlation analysis were used to screen the grading indicators and confirm the weight. We calculated the grading index and divided the levels by weighted sum method to get the grading result. We compared the results with the grading results of commonly used Delphi method.

Result
The value of variable importance I obtained by random forest algorithm ranged from 0.03 to 11.94. Correlation analysis showed that the correlation between most influencing factors was not significant, eight of which were significant correlation. The 14 rating indicators under four dimensions were astringed from 30 influencing factors. The main factors influencing the quality of cultivated land in the study area were ecosystem vulnerability, mean precipitation of growing season and annual solar radiation amount, with the weights of 0.11, 0.10 and 0.09, respectively.

Conclusion
Compared with Delphi method, the random forest algorithm has better stability and smaller level of index variation interval, which is more conducive to construct a comparable sequence of cultivated land levels at provincial spatial scale.
- cultivated land quality evaluation,
- grading indicators system,
- random forest algorithm,
- Delphi method

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References (36)

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