摘要:
土地利用/土地覆盖(land use/land cover,LULC)模拟是土地变化研究的重要一环。基于谷歌地球引擎(Google Earth Engine,GEE)平台提取禄劝县1991—2021年高精度的LULC信息,分析其时空演变特征; 利用随机森林模型探究LULC变化的驱动因素; 对比元胞自动机-马尔科夫模型(cellular automata-Markov, CA-Markov)、土地变化模型(land change modeler,LCM)、未来土地利用模拟模型(future land use simulation,FLUS)和斑块生成土地利用模拟模型(patch-generating land use simulation,PLUS)4种模型在禄劝县的模拟效果; 根据模拟效果最好的模型预测禄劝县2027年的LULC状况。结果表明: ①1991— 2021年,禄劝县LULC空间格局以林地、草地和耕地为主; 耕地和水体分别波动增加89.26 km2和27.72 km2,林地、建设用地和裸地面积分别持续增加724.25 km2,21.08 km2和13.67 km2,草地面积以年均29.20 km2的速度波动减少。②禄劝县LULC变化主要受到地形条件(高程和坡度)的影响。③4种LULC模型的模拟效果排行为PLUS>FLUS>CA-Markov>LCM,其Kappa系数分别为0.63,0.58,0.46和0.35,总体精度分别为0.78,0.75,0.66和0.58。④禄劝县2027年的LULC空间格局与2021年相似,2021—2027年,耕地、草地和水体的面积分别以40.21 km2/a,4.51 km2/a和0.70 km2/a的速率减少,而林地、建设用地和裸地分别向外扩张265.52 km2,4.85 km2和2.08 km2。
Abstract:
Land use/land cover (LULC) simulation is essential for research on changes in land use. Based on the Google Earth Engine (GEE) platform, this study extracted the high-precision LULC information of Luquan County from 1991 to 2021 and analyzed the spatio-temporal evolution pattern. Then, this study analyzed the factors driving LULC changes using a random forest model and compared the simulation results of Luquan County obtained using the cellular automata-Markov (CA-Markov), land change modeler (LCM), future land use simulation (FLUS), and patch-generating land use simulation (PLUS). Finally, this study forecast the LULC change scenario in Luquan County in 2027 using the optimal model. The results show that: ① From 1991 to 2021, the spatial LULC pattern of Luquan County was dominated by forestland, grassland, and farmland. The areas of farmland and waterbodies increased by 89.26 km2 and 27.72 km2, respectively, the areas of forestland, construction land, and bare land increased continuously by 724.25 km2, 21.08 km2, and 13.67 km2, respectively, and the grassland decreased at an annual average rate of 29.20 km2; ② The LULC in Luquan County was primarily influenced by topographic conditions (elevation and slope); ③ The simulation effects of the four LULC models were in the order of PLUS > FLUS > CA-Markov > LCM, with Kappa coefficient of 0.63, 0.58, 0.46 and 0.35, respectively and the overall accuracy of 0.78, 0.75, 0.66 and 0.58, respectively; ④ The spatial LULC pattern in Luquan County in 2027 will share similarities with that in 2021. From 2021 to 2027, the areas of farmland land, grassland, and water bodies will decrease at a rate of 40.21 km2/a, 4.51 km2/a, and 0.70 km2/a, respectively, while the forestland, construction land, and bare land will expand by 265.52 km2, 4.85 km2, and 2.08 km2, respectively.
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