| 英文摘要： |
Arable land suitability evaluation (ALSE) is one of the tools to ensure sustainable agricultural production and achieve the global food security goal. Determining the relationship between the suitability score of arable land (AL) and the corresponding influencing factors (e.g. precipitation and temperature) is the key step to ALSE. How-ever, the traditional method gets discontinuous suitability scores by classification based on expert knowledge, which contains considerable subjective uncertainty. This study proposes a proportion-based method, aiming to construct the suitability function based on the rule of survival of the fittest, thus the suitability score can be expressed in continuous curves with less uncertainty. ALSE can be concluded in three steps. First, the evaluation objects, i.e., current arable land (CAL) and potential arable land (PAL), and influencing factors are determined by environmental constraints and screening principles respectively. Second, the suitability functions of the influenc-ing factors are constructed by counting the proportion of CAL to AL. Third, the suitability order and class for AL are divided respectively by influencing factors and Jenks classification. The results show that: (1) The development of CAL basically adapts to local natural conditions in China's Qinghai-Tibet Plateau (QTP). Suitable CAL is mainly dis-tributed in the river valleys, where the elevation is low. Unsuitable CAL is mainly distributed in the Hengduan Mountains, where the slope is steep and the gravel content is high. (2) The area of suitable PAL is 5.3 times of suit-able CAL, with grassland accounting for 95.2% and bare land accounting for 4.8%, meaning that there is great po-tential to exploit PAL. The proposed suitability function is easy to generalize and use, and ALSE in QTP can provide support for land use planning. (c) 2021 Elsevier B.V. All rights reserved. |
在线留言
联系我们
所长信箱