| 基于CLUE-S模型县域土地利用情景模拟与碳排放效应分析 |
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| 引用本文： | 顾汉龙,马天骏,钱凤魁,蔡玉梅.基于CLUE-S模型县域土地利用情景模拟与碳排放效应分析[J].农业工程学报,2022,38(9):288-296. |
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| 作者姓名： | 顾汉龙 马天骏 钱凤魁 蔡玉梅 |
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| 作者单位： | 1. 沈阳农业大学土地与环境学院，沈阳 110161; 2. 耕地立体保护与监测重点实验室，沈阳 110161; 3. 土肥高效利用国家工程研究中心，沈阳 110161;;4. 中国土地勘测规划院，北京 100035; |
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| 基金项目： | 辽宁省科学研究经费项目（WSNZK202002）；辽宁省哲学社会科学规划基金项目（L19CGL009）；全国博士后科学基金特别资助项目（2020T130433） |
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| 摘 要： | 土地利用与变化产生的碳排放是国家温室气体排放清单核算中的重要组成部分。该研究以辽宁省沈阳市法库县为研究区域，基于2013年土地利用现状数据，运用CLUE-S模型对法库县2019年土地利用变化格局进行模拟与验证。在此基础上，通过设置基线情景、农业发展、建设发展、生态保护、土地利用结构优化5种模拟情景预测2030年法库县土地利用分布空间格局及各情景下土地利用碳收支状况。结果表明：1）CLUE-S模型对法库县土地利用格局变化具有良好的模拟能力，Kappa系数为0.989 6，模拟总体精度达到99.14%；2）在5种模拟情景中，土地利用结构优化情景下2030年法库县土地资源利用效果最优，是法库县中长期发展阶段较为适宜的土地利用模式；3）法库县2013-2019年碳排放量增长5.53%。5种模拟情景同2019年相比，除生态保护和农业发展情景外，其余模拟情景下法库县碳排放量均呈现增长趋势，其中土地利用结构优化情景增幅最小，为2.29%。研究结果可为法库县土地利用优化布局、国土空间规划编制及碳减排相关政策制订提供参考依据和决策支持，研究方法也可为其他区域土地利用格局预测及碳收支变化提供借鉴。
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| 关 键 词： | 模型 土地利用 规划情景 碳排放 法库县 |
| 收稿时间： | 2021/11/4 0:00:00 |
| 修稿时间： | 2022/4/26 0:00:00 |
County land use scenario simulation and carbon emission effect analysis using CLUE-S model |
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| Gu Hanlong,Ma Tianjun,Qian Fengkui,Cai Yumei.County land use scenario simulation and carbon emission effect analysis using CLUE-S model[J].Transactions of the Chinese Society of Agricultural Engineering,2022,38(9):288-296. |
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| Authors: | Gu Hanlong Ma Tianjun Qian Fengkui Cai Yumei |
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| Institution: | 1. College of Land and Environment, Shenyang Agriculture University, Shenyang 110161, China; 2. Key Laboratory of Trinity Protection and Monitoring of Cultivated Land, Shenyang 110161, China; 3. National Engineering Research Center for Efficient Utilization of Soil and Fertilizer Resources, Shenyang 110161, China;; 4. Chinese Land Surveying and Planning Institute, Beijing 100035, China; |
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| Abstract: | Carbon emission from land-use change can be one of the most important parts of the national greenhouse gas emission inventory. In this study, Faku County, Shenyang City, Liaoning Province was taken as the study area. Based on the vector data of the land use change survey results in Faku County in 2013, the driving factors of land-use change were calculated using the Auto-Logistic model, and then the land-use change pattern in 2019 was simulated using the CLUE-S model, thereby verifying the simulation using the Kappa coefficient. The spatial pattern of land use distribution in 2030 was predicted using five scenarios, including baseline scenarios, agricultural development, construction development, ecological protection, and land use structure optimization. Finally, the carbon revenue and expenditure of land use were calculated in each scenario using the coefficient of carbon emission. The results showed that: 1) The CLUE-S model performed better to simulate the change of land use layout in the study area, where the Kappa coefficient and the overall accuracy of the simulation were 0.989 6, and 99.14%, respectively. It infers that the model and parameters were suitable for the prediction of future land use layout. 2) Among the five simulated scenarios, Faku County presented the best land use effect in 2030 under the optimized land use structure scenario, which was a more suitable land use mode in the middle and long-term development stage. Several hidden dangers were found in the land use under the other four simulation scenarios. Specifically, there was a risk to the regional ecology and food security under the baseline scenario. Some serious damages were found to the safety of ecological and water resources under the agricultural development scenario. The food and ecological security were also seriously damaged under the construction development scenario. There were some risks in the limited economic development of food security under the ecological protection scenario. 3) The carbon emissions increased by 5.53% from 2013 to 2019. Among the five simulation scenarios in 2030, the construction and development scenarios presented the largest carbon emission (121.79×103 t), whereas, the ecological protection scenario was the least (-218.71×103 t). Except for the ecological protection and agricultural development scenarios, the carbon emissions showed an upward trend under other scenarios, indicating the smallest growth rate (2.29%) of land use structure optimization scenarios. The auto-Logistic regression model was selected to calculate the driving coefficient of land-use change, leading to the high accuracy of the CLUE-S model to predict the regional land use pattern. The finding can provide an excellent evaluation system to calculate the carbon emission, and then predict the land use pattern for the decision-making on the carbon budget in other regions. Anyway, the land-use layout can be optimized for the land and space planning related to carbon emission reduction. |
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| Keywords: | models land use planning scenario carbon emissions Faku county |
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