Xiaobing Sun
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Xiaobing Sun has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Bailin Zhang
School of Environmental Science and Engineering, Tiangong University, Tianjin 300387, China
1 shared publication - Ming Lei
College of Land Science and Technology, China Agricultural University, Beijing 100193, China
1 shared publication - Quanfeng Li
School of Public Administration and Law, Northeast Agricultural University, Harbin 150030, China
1 shared publication - Weimin Cai
School of Environmental Science and Engineering, Tiangong University, Tianjin 300387, China
1 shared publication - Xiangbin Kong
China Agr Univ, Coll Land Sci & Technol, Beijing 100193, Peoples R China
1 shared publication
Latest Publications
- Open Access
Spatial Characteristics and Obstacle Factors of Cultivated Land Quality in an Intensive Agricultural Region of the North China Plain
Cultivated land quality (CLQ) is at the core of the trinity protection of cultivated land in China. Scientific evaluation of CLQ and identification of its obstacle factors are the foundation for the construction and improvement of the quality of cultivated land. The main objective of this study was to evaluate CLQ and identify its obstacle factors, and Quzhou County, an intensive agricultural region in the North China Plain (NCP), was selected as a case study. The evaluation index system of CLQ was constructed based on five dimensions, including climate condition, topographic characteristic, soil property, farming status, and environmental condition, by analyzing the logical evolution of elements, processes, functions, and quality of cultivated land. A methodological system based on the Weighted Summation Method (WSM) and the “1 + X” model was developed to evaluate the CLQ. Then, the obstacle diagnosis model constructed based on the Cask Law and relevant academic studies was used to identify the obstacle factors of CLQ. The results showed that the proportion of high-, medium-, and low-quality cultivated land in Quzhou County was 36.19%, 33.60%, and 30.21%, respectively, and the average grade of CLQ was 2.97, which was considered to be at a medium level. Moran’s I of global spatial autocorrelation in Quzhou County was 0.8782, indicating a significant positive autocorrelation of the cultivated land quality index (CLQI). The main obstacle factors of CLQ in Quzhou County were soil profile constitution, irrigation guarantee rate, groundwater depth, and soil microbial biomass carbon. Therefore, based on the stable and dynamic characteristics of the obstacle factors, suggestions were provided to improve the quality of cultivated land in terms of strengthening the consolidation of cultivated land, transforming the concept of agricultural fertilization, and carrying out cultivated land recuperation. This study provides a new perspective on the cognition, evaluation, and identification of obstacle factors of CLQ, and the findings of this study can provide a reference for the consolidation and improvement of CLQ in the NCP.
Open AccessSpatial Characteristics and Obstacle Factors of Cultivated Land Quality in an Intensive Agricultural Region of the North China Plain
Cultivated land quality (CLQ) is at the core of the trinity protection of cultivated land in China. Scientific evaluation of CLQ and identification of its obstacle factors are the foundation for the construction and improvement of the quality of cultivated land. The main objective of this study was to evaluate CLQ and identify its obstacle factors, and Quzhou County, an intensive agricultural region in the North China Plain (NCP), was selected as a case study. The evaluation index system of CLQ was constructed based on five dimensions, including climate condition, topographic characteristic, soil property, farming status, and environmental condition, by analyzing the logical evolution of elements, processes, functions, and quality of cultivated land. A methodological system based on the Weighted Summation Method (WSM) and the “1 + X” model was developed to evaluate the CLQ. Then, the obstacle diagnosis model constructed based on the Cask Law and relevant academic studies was used to identify the obstacle factors of CLQ. The results showed that the proportion of high-, medium-, and low-quality cultivated land in Quzhou County was 36.19%, 33.60%, and 30.21%, respectively, and the average grade of CLQ was 2.97, which was considered to be at a medium level. Moran’s I of global spatial autocorrelation in Quzhou County was 0.8782, indicating a significant positive autocorrelation of the cultivated land quality index (CLQI). The main obstacle factors of CLQ in Quzhou County were soil profile constitution, irrigation guarantee rate, groundwater depth, and soil microbial biomass carbon. Therefore, based on the stable and dynamic characteristics of the obstacle factors, suggestions were provided to improve the quality of cultivated land in terms of strengthening the consolidation of cultivated land, transforming the concept of agricultural fertilization, and carrying out cultivated land recuperation. This study provides a new perspective on the cognition, evaluation, and identification of obstacle factors of CLQ, and the findings of this study can provide a reference for the consolidation and improvement of CLQ in the NCP.