晋北地区土地利用覆被格局的演变与模拟

区域土地利用覆被变化及未来发展情景对区域土地管理和可持续发展具有重要意义。以地处农牧交错带、土地利用覆被变化剧烈的晋北地区为研究区,获取其2010、2015年的土地利用覆被(Land use/land cover,LULC)数据,选取高程、人口、经济、气温、降水等9种影响因素作为驱动因子,采用CLUE-S模型拟合研究区2015年的土地覆被格局并判断拟合精度,在此基础上,分别设置了3种社会经济发展情景,模拟这些情景下研究区2020年的土地利用覆被格局演变。结果表明:1)晋北地区土地利用覆被以耕地、林地和草地为主,各类型土地主要呈西北斜向的条带状分布;2)Logistic回归模型可以很好地提取LULC与驱动因子之间的关系,反映不同的驱动因素对不同的土地利用类型分布格局的影响效果及程度;3)CLUE-S模型在晋北地区土地利用覆被格局的拟合上有较好的精度,模拟Kappa系数值达0.89,表明该模型能够很好地模拟晋北地区的土地利用覆被;4)情景模拟结果表明,研究区生态保护情景(c)下的土地利用覆被格局明显优于维持现状情景(a)和经济优先情景(b),建议在未来土地开发利用过程中,应当减缓工矿用地增加速度,严格控制建设用地规模,优化土地利用格局。

Evolution and simulation of land use/land cover pattern in northern Shanxi Province

Regional land use/cover change and future development scenarios are of great significance for the regional sustainable development and land management. In this study, we selected northern Shanxi province, an agro-pastoral ecotone, as the research area. The land use/land cover (LULC) maps of the study area in 2010 and 2015, as well as the driving factors including elevation, population, economy, temperature, and precipitation were extracted from various national-level datasets. We first used the CLUE-S model to simulate the LULC of 2015 based on 2010 LULC data and driving factors, and evaluated the simulation accuracy with the obtained 2015 LULC data. Then, we used the evaluated CLUE-S model to simulate the LULC patterns in 2020 under three future development scenarios. The results showed that the LULC of northern Shanxi was dominated by cultivated land, forestland, and grassland. The LULCs mainly distributed in strip-shapes toward the northwest. The logistic regression model could extract the relationship between LULC and driving factors well, and reflected the effect and degree of different driving factors on the LULC pattern. The CLUE-S model had high accuracy in fitting the LULC of northern Shanxi, with a Kappa coefficient of 0.89. The scenario simulation showed that the LULC under the environmental protection scenario (c) was more sustainable than the business-as-usual scenario (a) and economic development scenario (b) in the study area. The results suggest that the increasing rate of the industrial and mining land should be slowed down, and the size of construction land should be strictly controlled in future land development, and the LULC pattern should be further optimized.