Optimization of Spatial Layout of Ecological-Production-Living Spaces in Mountainous Characteristic Towns Based on Micro-Topography Constraints
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摘要: 优化国土空间开发格局是生态文明建设的重要内容，在村镇尺度下生态-生产-生活(简称“‘三生’”)空间结构与布局，对于特色小镇绿色发展具有重要意义.为优化山区以工业和旅游融合为优势的特色小镇“三生”空间布局，以茅台镇为研究对象，基于“产业兴旺、生态宜居”乡村振兴战略要求，通过10 m分辨率DEM、土地利用等数据，以主导生态功能和山区微地貌为约束条件，通过GeoSOS-FLUS模型开展了生态优先情景下茅台镇“三生”空间布局优化研究，并与无地貌约束的自然演变和经济优先2种情景做了对比.结果表明：①茅台镇生态空间和农业生产空间在峡谷底、陡坡和山脊区域均有大量分布且面积数量差异较小，而生活空间和工业生产空间多分布在峡谷底部.②自然演变情景模拟下，河谷地带的缓坡和部分陡坡位置均被转换为建设用地；经济优先情景模拟下，缓坡位置的耕地较易转化为建设用地；而生态优先情景模拟下，林地实现了空间上的连通和聚集，建设用地主要在茅台镇中南部河谷地带以及缓坡地区适度扩张.③生态优先情景下，峡谷底区域“三生”空间布局得到优化，生态空间面积从41.29 km2增至43.80 km2，工业生产空间面积由6.86 km2增至7.89 km2，农业生产空间由24.29 km2降至20.00 km2.研究显示，对于山区型村镇，微地貌约束土地利用模拟使得工业生产空间和生活空间集中分布在峡谷底区域，而生态空间则较多分布在缓坡和陡坡区域.Abstract: Optimizing the spatial development pattern of land is an important part of the construction of ecological civilization, especially the optimization of the structure and layout of Ecological-Production-Living Spaces of villages and towns is of great significance for the green development of characteristic towns. In order to optimize the spatial layout of Ecological-Production-Living Spaces in mountainous characteristic towns, taking Maotai Town as the research object, the land use layout of Maotai Town was optimized with the dominant ecological function and mountain micro-topography as constraints based on the strategic requirements for rural revitalization of 'industrial prosperity, ecological livability', through DEM with 10 m resolution, land use, and traffic location data with the GeoSOS-FLUS model. Meanwhile, this paper studies the spatial layout optimization of Ecological-Production-Living Spaces in Maotai Town under the ecological priority scenario, and makes a comparison with natural evolution and economical priority scenarios. The results showed that: (1) The ecological space and agricultural production space in Maotai Town were distributed at the valley bottom, steep slope and ridge area, and the difference in area number was small, while the living space and industrial production space were mostly distributed at the bottom of the canyon. (2) Under the natural evolution scenario simulation, the gentle slopes and some steep slopes of the valley are converted into construction land. Under the economic priority scenario, the cultivated land on the gentle slopes is easier to convert into construction land. And under the ecological priority scenario simulation, the forest lands are connected and gathered in space, and the construction land in the valley area and gentle slope area in the middle and south of Maotai Town is moderately expanded. (3) Under the ecological priority scenario, the spatial layout of Ecological-Production-Living Spaces at the valley bottom area is optimized. Specifically, the ecological space area increases from 41.29 km2 to 43.80 km2, the industrial production space area increases from 6.86 km2 to 7.89 km2, and the agricultural production space decreases from 24.29 km2 to 20.00 km2. This study shows that for mountainous villages and towns, micro-topography constrained land use simulation concentrates industrial production space and residential space at the valley bottom area, while ecological space is more distributed in gentle and steep slope areas.
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图 4 不同情景下土地利用布局模拟
注：与2018年土地利用现状相比，模拟数据在A和B区域较为集中地将耕地错误模拟为建设用地.在自然演变情景下，C区域被预测为建设用地，D和E区域也从农田和林地被预测为建设用地(工业建设用地).在经济优先情景下，F区域坡耕地被预测为建设用地.在生态优先情景下，G和H区域耕地较多被预测为林地，而I区域生态保护红线和基本农田区域相较2018年变化较小.
Figure 4. Simulation of land use layout under different scenarios
表 1 2000—2018年茅台镇土地利用和“三生”空间变化
Table 1. Land use and Production-Life-Ecology Space change in Moutai Town from 2000 to 2018
km2 土地利用划分 2000年 2010年 2018年 2000—2010年变化 2010—2018年变化 2000—2018年变化 耕地 84.55 84.51 78.87 -0.03 -5.64 -5.68 林地 72.45 75.74 73.63 3.30 -2.11 1.19 草地 51.42 48.11 46.17 -3.31 -1.94 -5.25 水域 3.00 3.00 3.41 0.00 0.41 0.41 建设用地 1.43 1.48 10.76 0.04 9.28 9.33 农业生产空间 84.55 84.51 78.87 -0.03 -5.64 -5.68 工业生产空间 2.34 3.03 7.13 0.69 4.10 4.79 生活空间 1.23 1.43 3.63 0.20 2.20 2.40 生态空间 124.72 123.87 123.21 -0.85 -0.66 -1.51 
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表 2 数据信息说明
Table 2. Data information description
数据类型 数据来源 说明 用途 DEM 2017年6月资源三号卫星遥感影像立体像对提取 分辨率为10 m×10 m 求取坡度、坡向、TWI、TPI、微地貌等 茅台镇2000年、2010年、2018年土地利用数据 中国科学院资源环境科学数据中心 分辨率为30 m×30 m 模型输入数据 《全国生态功能区划(修编版)》 — 主导生态功能定位 规划资料 《贵州省生态保护红线》 — 生态约束条件 《仁怀市土地利用总体规划(2015—2020年)》 — 上位规划约束条件 基础地理信息数据 https://www.openstreetmap.org 比例尺为1:300 000 交通区位驱动因子
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表 3 基于TPI的地貌划分
Table 3. Division of landform classification based on TPI
坡度位置 划分方法 山脊 z0>8 陡坡 8≥z0>-8, slope>6° 缓坡 8>z0≥-8, slope≤6° 峡谷底 z0 < -8
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表 4 基于地形约束的茅台镇“三生”空间划分及优化策略
Table 4. Space division and optimization strategy of Production-Life-Ecology Space in Maotai Town based on terrain constraints
地貌 面积/km2 面积占比% 面积/km2 优化策略 农业生产空间 工业生产空间 生活空间 生态空间 峡谷底 75.57 35.51 24.29 6.86 3.13 41.29 适当约束建设用地扩增 缓坡 5.98 2.81 3.12 0.19 0.36 2.31 有限开发，做好生态涵养和环境保护 陡坡 66.39 31.19 26.54 0.01 0.12 39.72 适度农业生产，退耕还林 山脊 64.90 30.49 24.92 0.07 0.02 39.89 退耕还林，恢复为草地或林地 总计 212.84 100.00 78.87 7.13 3.63 123.21
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表 5 不同情景下土地利用布局
Table 5. Land use layout under different scenarios km2
土地利用划分 2018年现状 2018年模拟 自然演变情景 经济优先情景 生态优先情景 优化幅度 耕地 78.87 76.32 74.68 70.56 67.45 -11.42 林地 73.63 77.01 85.34 82.61 98.76 25.13 草地 46.17 47.30 28.38 33.42 27.35 -18.82 水域 3.41 3.40 3.43 3.43 3.52 0.11 建设用地 10.76 8.81 21.01 22.82 15.76 5.00 农业生产空间 78.87 76.32 74.68 70.56 67.45 -11.42 工业生产空间 7.13 5.46 15.65 17.57 9.87 2.74 生活空间 3.63 3.35 5.36 5.25 5.89 2.26 生态空间 123.21 127.71 117.15 119.46 129.63 6.42
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