Volume 29 Issue 6
Dec.  2019
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GENG Shoubao, SHI Peili, ZONG Ning, ZHU Wanrui. Agricultural Land Suitability of Production Space in the Taihang Mountains, China[J]. Chinese Geographical Science, 2019, 29(6): 1024-1038. doi: 10.1007/s11769-019-1075-6
Citation: GENG Shoubao, SHI Peili, ZONG Ning, ZHU Wanrui. Agricultural Land Suitability of Production Space in the Taihang Mountains, China[J]. Chinese Geographical Science, 2019, 29(6): 1024-1038. doi: 10.1007/s11769-019-1075-6

Agricultural Land Suitability of Production Space in the Taihang Mountains, China

doi: 10.1007/s11769-019-1075-6
Funds:

Under the auspices of the National Basic Research Program of China (No. 2015CB452705)

  • Received Date: 2019-01-24
  • Publish Date: 2019-12-01
  • The contradiction between the shortage of land for agriculture due to rapid expansion of industrialization and urbanization and increasing population pressure is projected to impose great threats to future food security. Agricultural land suitability evaluation is an effective approach to improve the utilization of land resources for crop production and thus enhance the capacity of food provision. In this study, we evaluated the land suitability for agriculture of the production space in the Taihang Mountains by three steps:establishing indicator system, determining weights for indicators, and constructing a fuzzy matter-element model to assess the grades of suitability. Results showed that the land suitability had a significant linear correlation with potential crop yields, indicating our evaluation was effective to predict crop production. The spatial pattern of land suitability for crop production demonstrated that land with higher suitability was generally located in piedmont plains and basins, while land with lower suitability was mostly situated in mountainous areas. The area of highly, moderately, marginally suitable and unsuitable land for agriculture was 32.13%, 28.58%, 37.49% and 1.80% of the production space, respectively. However, the correlation degree analysis indicated that the requirements of these four suitability grades were currently not satisfied but could be potentially fulfilled. In terms of indicator weights, soil properties were much more important than topography and location conditions to influence the grades of suitability. Among all indicators, slope, soil organic matter, soil texture and soil depth were the most influential factors, so slope farming prevention and organic fertilization were most likely to improve land suitability for agriculture. Compared the outputs of our land suitability evaluation model with the distribution of the existing croplands, we found that about 66.52% of marginally suitable and 54.55% of unsuitable land for agriculture were currently used for croplands. Therefore, de-farming policy should be implemented in areas of these two suitability grades. In contrast, cropland expansion was encouraged in the land that was highly or moderately suitable for agriculture. Our evaluation of agricultural land suitability is beneficial for future land use planning and decision-making in the Taihang Mountains.
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Agricultural Land Suitability of Production Space in the Taihang Mountains, China

doi: 10.1007/s11769-019-1075-6
Funds:

Under the auspices of the National Basic Research Program of China (No. 2015CB452705)

Abstract: The contradiction between the shortage of land for agriculture due to rapid expansion of industrialization and urbanization and increasing population pressure is projected to impose great threats to future food security. Agricultural land suitability evaluation is an effective approach to improve the utilization of land resources for crop production and thus enhance the capacity of food provision. In this study, we evaluated the land suitability for agriculture of the production space in the Taihang Mountains by three steps:establishing indicator system, determining weights for indicators, and constructing a fuzzy matter-element model to assess the grades of suitability. Results showed that the land suitability had a significant linear correlation with potential crop yields, indicating our evaluation was effective to predict crop production. The spatial pattern of land suitability for crop production demonstrated that land with higher suitability was generally located in piedmont plains and basins, while land with lower suitability was mostly situated in mountainous areas. The area of highly, moderately, marginally suitable and unsuitable land for agriculture was 32.13%, 28.58%, 37.49% and 1.80% of the production space, respectively. However, the correlation degree analysis indicated that the requirements of these four suitability grades were currently not satisfied but could be potentially fulfilled. In terms of indicator weights, soil properties were much more important than topography and location conditions to influence the grades of suitability. Among all indicators, slope, soil organic matter, soil texture and soil depth were the most influential factors, so slope farming prevention and organic fertilization were most likely to improve land suitability for agriculture. Compared the outputs of our land suitability evaluation model with the distribution of the existing croplands, we found that about 66.52% of marginally suitable and 54.55% of unsuitable land for agriculture were currently used for croplands. Therefore, de-farming policy should be implemented in areas of these two suitability grades. In contrast, cropland expansion was encouraged in the land that was highly or moderately suitable for agriculture. Our evaluation of agricultural land suitability is beneficial for future land use planning and decision-making in the Taihang Mountains.

GENG Shoubao, SHI Peili, ZONG Ning, ZHU Wanrui. Agricultural Land Suitability of Production Space in the Taihang Mountains, China[J]. Chinese Geographical Science, 2019, 29(6): 1024-1038. doi: 10.1007/s11769-019-1075-6
Citation: GENG Shoubao, SHI Peili, ZONG Ning, ZHU Wanrui. Agricultural Land Suitability of Production Space in the Taihang Mountains, China[J]. Chinese Geographical Science, 2019, 29(6): 1024-1038. doi: 10.1007/s11769-019-1075-6
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