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Trajectory analysis and scenario simulation of land use change in the Yihe River Basin
QIAO Xinru, LI Zijun, LIN Jinkuo, YANG Shuyuan
PDF(7462 KB)
Trajectory analysis and scenario simulation of land use change in the Yihe River Basin
Based on the land use data of the Yihe River Basin from 1975 to 2020, the GIS technology was used to construct and analyze the land use change trajectories. It also used the FLUS (further land use simulation) model to simulate land use scenarios of the basin in 2030 and 2050 under the “production-living-ecological” space paradigm, and visualize development patterns of the land use under different management modes. The results showed that: 1) From 1975 to 2020, the land use was primarily characterized by the reduction of arable land (accounting for about 10% of the basin area) and the expansion of construction land (accounting for about 8% of the basin area). 2) The land use change the Yihe River Basin could be divided into two stages: the early stage (1975-1995) and the later stage (1995-2020). During the early stage, about 22% of the area suffered land use transfer, mainly manifesting as mutual change of arable land, forest, and grassland. In the later stage, about 46% of the total area changed to another land use type, with a major tendency of arable land transferring to construction land. Both the trajectory changes and the spatial pattern of land use were more complex and significant. 3) The land use pattern of the basin was transferring towards a focus on ecological construction. From 2020 to 2030, the natural development scenarios was more consistent with the ecological space priority scenarios, but this convergence declined by 2050. This study can serve as a reference for further optimization of the “production-living-ecological” space pattern and ecological construction in the basin.
land use change / scenario simulation / trajectory analysis / FLUS model / Yihe River Basin {{custom_keyword}} /
Tab.1 Conversion cost matrix表1 转移成本矩阵 |
| 情景类型 | 土地利用类型 | 耕地 | 林地 | 草地 | 水域 | 建设用地 | 未利用地 |
|---|---|---|---|---|---|---|---|
| NDS | 耕地 | 1 | 1 | 1 | 0 | 1 | 0 |
| 林地 | 1 | 1 | 1 | 0 | 1 | 0 | |
| 草地 | 1 | 1 | 1 | 0 | 1 | 1 | |
| 水域 | 1 | 0 | 0 | 1 | 0 | 0 | |
| 建设用地 | 1 | 0 | 0 | 0 | 1 | 0 | |
| 未利用地 | 1 | 1 | 1 | 0 | 1 | 1 | |
| PPS | 耕地 | 1 | 0 | 0 | 0 | 0 | 0 |
| 林地 | 1 | 1 | 1 | 1 | 1 | 0 | |
| 草地 | 1 | 1 | 1 | 1 | 1 | 0 | |
| 水域 | 1 | 1 | 1 | 1 | 1 | 0 | |
| 建设用地 | 0 | 0 | 0 | 0 | 1 | 0 | |
| 未利用地 | 1 | 1 | 1 | 1 | 1 | 1 | |
| LPS | 耕地 | 1 | 0 | 0 | 0 | 1 | 0 |
| 林地 | 1 | 1 | 0 | 0 | 1 | 0 | |
| 草地 | 1 | 1 | 1 | 0 | 1 | 0 | |
| 水域 | 1 | 1 | 1 | 1 | 1 | 0 | |
| 建设用地 | 0 | 0 | 0 | 0 | 1 | 0 | |
| 未利用地 | 1 | 1 | 1 | 1 | 1 | 1 | |
| EPS | 耕地 | 1 | 1 | 1 | 1 | 1 | 0 |
| 林地 | 0 | 1 | 0 | 0 | 0 | 0 | |
| 草地 | 0 | 1 | 1 | 1 | 0 | 0 | |
| 水域 | 0 | 0 | 0 | 1 | 0 | 0 | |
| 建设用地 | 0 | 0 | 0 | 0 | 1 | 0 | |
| 未利用地 | 1 | 1 | 1 | 1 | 1 | 1 |
| 注:0表示不允许该土地利用类型进行转移,1表示允许该土地利用类型向其他地类进行转移;NDS为自然发展情景,PPS为生产优先情景,LPS为生活优先情景,EPS为生态优先情景。 |
Tab.2 Changes of land use dynamic degree from 1975 to 2020 in the Yihe River Basin 单位:%表2 1975—2020年沂河流域土地利用动态度变化 |
| 时段 | 耕地 | 林地 | 草地 | 水域 | 建设用地 | 未利用地 | 综合 |
|---|---|---|---|---|---|---|---|
| 1975—1995年 | -0.04 | 0.06 | 0.02 | -0.01 | 0.23 | -0.01 | 0.37 |
| 1995—2020年 | -0.60 | 0.94 | -0.50 | 1.04 | 4.44 | 2.13 | 0.57 |
| 1975—2020年 | -0.35 | 0.56 | -0.27 | 0.57 | 2.68 | 1.17 | 0.32 |
Tab.3 The main change trajectories of land use from 1975 to 2020 in the Yihe River Basin表3 1975—2020年沂河流域主要土地利用变化轨迹 |
| 类别 | 主要变化轨迹 | 面积/km2 |
|---|---|---|
| 耕地-草地 | 耕-耕-耕-耕-草-草-草 | 198.34 |
| 耕-耕-草-耕-耕-耕-耕 | 190.26 | |
| 草-草-草-草-耕-耕-耕 | 142.73 | |
| 草-草-耕-草-耕-耕-耕 | 104.96 | |
| 草-草-耕-草-草-草-草 | 54.63 | |
| 耕地-林地 | 耕-耕-耕-耕-林-林-林 | 181.23 |
| 林-林-林-林-耕-耕-耕 | 130.46 | |
| 耕-耕-耕-耕-耕-耕-林 | 106.98 | |
| 耕-耕-耕-耕-耕-林-林 | 98.81 | |
| 耕-耕-耕-林-耕-耕-耕 | 59.17 | |
| 林地-草地 | 草-草-草-草-林-林-林 | 86.73 |
| 林-林-林-林-草-草-草 | 84.34 | |
| 耕地-水域 | 耕-耕-耕-耕-水-水-水 | 89.12 |
| 水-水-水-水-耕-耕-耕 | 52.15 | |
| 耕地-建设用地 | 耕-耕-耕-耕-建-建-建 | 360.41 |
| 耕-耕-耕-耕-耕-耕-建 | 191.62 | |
| 耕-耕-耕-耕-耕-建-建 | 137.63 | |
| 耕-耕-耕-建-建-建-建 | 83.56 | |
| 耕-耕-建-建-建-建-建 | 72.53 | |
| 耕-耕-耕-建-耕-耕-耕 | 64.79 | |
| 建-建-建-建-耕-耕-耕 | 117.90 |
Fig.7 Land use scenarios in 2030 and 2050 in the Yihe River Basin图7 沂河流域2030年、2050年土地利用情景 注:NDS为自然发展情景,PPS为生产优先情景,LPS为生活优先情景,EPS为生态优先情景。网络版为彩图。 |
Tab.4 Dynamic degree of land use under different scenarios in the Yihe River Basin 单位:%表4 沂河流域不同情景下土地利用动态度 |
| 时间段 | 地类 | 土地利用情景 | |||
|---|---|---|---|---|---|
| NDS | PPS | LPS | EPS | ||
| 2020—2030年 | 耕地 | -0.86 | 0.05 | -0.45 | -1.10 |
| 林地 | 1.00 | -0.02 | -0.05 | 1.64 | |
| 草地 | -0.22 | -0.21 | 0.13 | -0.01 | |
| 水域 | 0.95 | -0.18 | 0.11 | 0.97 | |
| 建设用地 | 2.23 | 0.05 | 1.75 | 2.16 | |
| 未利用地 | 3.22 | -0.94 | -0.93 | -0.92 | |
| 综合动态度 | 1.49 | 1.31 | 1.38 | 1.44 | |
| 2030—2050年 | 耕地 | -0.13 | 0.03 | -0.12 | -0.03 |
| 林地 | 0.14 | -0.03 | -0.07 | -0.11 | |
| 草地 | -0.14 | -0.15 | -0.15 | -0.02 | |
| 水域 | -0.01 | -0.17 | -0.09 | 0.25 | |
| 建设用地 | 0.33 | 0.04 | 0.53 | 0.27 | |
| 未利用地 | 0.02 | -0.21 | -0.22 | -0.17 | |
| 综合动态度 | 0.61 | 0.01 | 0.05 | 0.07 | |
| 注:NDS为自然发展情景,PPS为生产优先情景,LPS为生活优先情景,EPS为生态优先情景。 |
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Constructing a scientific, reasonable, and feasible land resource classification system is the premise and foundation for effectively carrying out land resources survey, correctly making land resource development and rehabilitation planning, and scientifically managing land resources. Based on the definition and connotation of land resource classification, this study compared six representative land resource classification systems internationally and eight land classification systems in China, analyzed the main problems of China’s current land resource classification system, and put forward some recommendations for improving the classification system of land resources in China. The results indicate that there are three main problems in China’s current land resource classification systems. First, the current systems may not be able to accurately reflect the complex and diverse land use types and the regional differentiation of land use due to the two land use classification levels and insufficient land use types, which compromises the actual application effect of land resource classification as a result. Second, land resource classification standards are sometimes confusing, with the form classification standards and functional classification standards coexisting in the same classification level and classifications lacking scientific and logical rigor. Third, the classification standards of some land use types are unclear, and some land use types have no corresponding categories in the classification systems, which is contrary to the principle of “no repetition and no omission” in land use classification setting. The following recommendations were put forward to improve the classification system of land resources in China. First, future revision of land resource classification system should adhere to the six basic principles of land use classification in China. Second, it is practicable to learn from the experience of the four levels of classification in the United Kingdom and the United States, and we put forward the basic framework of China’s land resource classification system with four levels. Third, it is necessary to upgrade the national land use classification standard system to national laws and regulations referring to Russian’s experience, and thereby comprehensively enhance the seriousness and authority of the national land resource classification system. {{custom_citation.content}}
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Simulation of urban land use change is the scientific basis for optimizing land resource allocation, and improving its refinement and reliability is helpful to accurately grasp the development trend of urban land use. This is immensely crucial for accurate regulation of urban land resources. The simulation of land use change based on remote sensing classification is macroscopic and simple. However, it is difficult to apply this approach to reveal the change in urban land use social functions, as well as the source and mechanism of spatial scale effect in the refined simulation at block scale. This study identified the refined urban land use characteristics by combining remote sensing images and POI data. Moreover, the optimal spatial scale combination was calibrated for refined land use simulation with the response surface method. Based on the optimal spatial scale combination, the refined simulation of future land use change was performed by using the CA-Markov model. Considering the Wuhan core urban area as an example, the results demonstrate that: (1) POI-based refined urban land use identification method can deeply analyze the social functions of urban construction land, which greatly improves the traditional remote sensing-based macro interpretation of land cover. (2) Optimal spatial scale combination of CA-Markov model for refined land use change simulation in the study area is at the cell size of 30 m and neighborhood size of 7 using the Von Neumann neighborhood type, at which the reliability of refined land use change simulation can be improved. The results of the response surface design can effectively distinguish not only the main sources of the spatial scale effect, but also the magnitude of their influence and the positive or negative effects on the simulation accuracy in the refined simulation process. (3) It is predicted that by 2025 the construction land scope of the study area will continue to expand to the periphery with various types of land interlaced, and the spatial pattern of land use will become more fragmented. {{custom_citation.content}}
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基于关中—天水经济区2000年、2005年和2010年三期TM遥感影像数据，利用CA-Markov模型对土地利用格局进行模拟验证并预测2015年土地利用格局.结果表明：关中—天水经济区土地利用变化模拟的Kappa系数为0.79，模型的模拟精度高； 2005—2015年，关中—天水经济区耕地、林地将呈现减少趋势，建设用地显著增加，草地、水域略有变化，未利用地几乎没有变化；研究区生态环境总体上有恶化的趋势，需加强对耕地、林地的保护.
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首先采用队列因素法和CA-Markov模型对区域未来人口规模和土地利用格局进行模拟预测，并结合POI地理大数据，利用多源信息融合法构建区域未来人口精细化空间分布模拟模型，以珠江三角洲城市群2030年各区县精细化的人口空间分布预测进行实证分析。结果表明：① 采用队列因素法进行珠江三角洲各区县人口规模预测的相对误差大部分在5%以下，基于CA-Markov模型土地利用模拟的Kappa系数达到0.97；② 珠江三角洲城市群精细化的人口空间分布模拟数据与实际人口数据的拟合趋势线R<sup>2</sup>达到了0.90，模拟效果优于Worldpop数据集，体现了POI地理大数据与多源信息融合在精细化人口空间分布模拟上的优势；③ 珠江三角洲未来人口呈现由中心向外围扩散和递减的空间分布格局，空间差异显著且较为稳定，70%的人口集中在广州、深圳、东莞和佛山等核心城市。
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黄河流域城镇扩张对区域景观格局影响显著,城市群人口聚集与增长引发了流域“人-地”矛盾和“空间冲突”等一系列生态环境问题。基于土地利用数据和FLUS模型对2025年和2035年呼包鄂榆城市群城镇化与土地利用时空演化特征进行多情景模拟预测。结果表明：① 1990—2018年呼包鄂榆城市群整体发展水平较低,建设用地面积经历了“平稳增加-缓慢增加-急剧增加”的变化过程,区域总体以草地为主,其占土地总面积的50%以上,其次是未利用土地和耕地,林地和建设用地次之。② 城市群扩张最剧烈地区在空间上主要发生在呼和浩特市、包头市等城市主城区,且扩张模式以外延式扩张为主,扩张来源主要是耕地、草地等生态用地。③ 三种情景模拟发现,2025年和2035年区域土地利用变化的空间结构和特征差异明显。自然发展情景下,城市扩张不受约束,高速增长占据了大量生态用地;加入生态约束条件很好的控制了对草地和林地的占用;经济发展情景下,城市扩张将进一步占据更多的未利用土地和耕地。本研究通过城市群扩张时空格局演化及情景模拟分析,尝试为区域规划、城市空间规划和区域生态空间保护提供多角度、多情景和可选择的政策决策参考。
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以曲沟镇多期高清遥感影像、问卷访谈及大量一手数据为基础,综合运用参与式农村评估（PRA）、GIS空间分析及土地利用转型矩阵等方法,剖析了研究区1991-2017年“三生”空间格局演变及驱动因素,对引导其“三生”空间协调发展有重要的现实意义。结果显示:① 研究期内,以工矿用地为主的建设用地增量显著,总体呈现高速扩展、局部集聚及多样化发展态势;② 生产空间由农业为主转变为农业与工业两强并存,工业生产空间嵌入到农业生产空间中形成“马赛克”式格局;③ 生活空间演变呈现空间扩展与质量提升并存的趋势;④ 生态空间的变化则具备面积缩减与质量下降2个特征;⑤ 工业镇“三生”空间的演变过程,是乡村能人带动、产业结构演变、路径依赖累积、政府宏观调控及综合地理条件约束等内外因素综合作用的结果。
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土地利用多功能性识别是城市用地组织,协调与配置的基础信息源,是判定城市用地内在功能形态,功能组合模式和功能之间动态权衡的关键,具有重要的理论和实践意义,但长期以来并未构建一套可行的识别方法体系.本文从土地功能,生态系统服务和景观功能综合的视角构建城市生态--生产--生活空间功能分类体系,并以生态系统服务价值评估为基础系统整合空间功能价值量核算函数群,通过纵横对比的方法确定空间功能主导类型.研究区实证分析表明,城市生态--生产--生活功能分类体系较好反映了不同地类的功能类型;空间主导功能的识别也与不同地类的功能匹配;同时也发现三生空间的整体毗邻性较低,空间功能的互补和融合性较差的问题;三生空间功能存在一定的空间集聚性.
The identifying of land multifunctionality is a basic tool for organization, coordination and configuration of urban land, and is a key criterion for urban land functions forms, composite pattern and dynamic tradeoffs. This topic is of important theoretical and practical significance. An available identification system of urban land multifunctionality, however, had not been built for a long time. This paper develops a function classification system for urban ecological-production-living spaces from an integrated perspective of land function, ecosystem services and landscape function. We integrated a value function group of space function based on ecosystem services valuation. A comparison method of vertical and cross direction is proposed to identify dominant function type of urban land. The empirical results show that in the study area, function classification system of urban ecological-production-living spaces can reflect differentiated function types of different land use classes. The identified result of dominant function for urban space is matched with the functions of different land types. Meanwhile, we also found that there are some problems on urban land use, such as the low adjacency degree with different spaces, and poor complementarity with different space functions. The result indicates that the spatial distribution of urban ecological-production-living spaces is congregated in the study area. {{custom_citation.content}}
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工业化、城市化和经济的快速发展导致中国人地关系紧张,争地现象多发。为兼顾粮食安全、经济发展和生态保护之间的关系,需要协调土地不同功能用地的矛盾。现行的土地利用分类体系,注重土地的生产、生活功能,对生态功能考虑不够。本研究以土地的主体功能为出发点,兼顾其他功能,纳入生态用地的概念,构建了“三生用地”分类体系,统筹生产、生活和生态用地空间。通过先分区再分类的方法,提取了中国“三生用地”的分布范围。结果表明,生态用地、生态生产用地、生产生态用地和生活生产用地等面积分别为603.70万km<sup>2</sup>、135.38万km<sup>2</sup>、200.19万km<sup>2</sup>和20.73万km<sup>2</sup>,各占国土面积的62.89%、14.10%、20.85%和2.16%。生态用地主要分布在中西部,生态生产用地因其生产功能具有明显的地域分异,生产生态用地和生活生产用地则更集中分布在东部地区。
Rapid development of industrialization,urbanization and economy causes tension in the human-land relationship. To take into account the relationship between food security,economic development and ecological protection,one needs to coordinate contradictions and conflicts between different functional land types. The current land use classification system emphasizes the industrial and living function of lands but insufficiently considers ecological function. This study built an Ecological-living-industrial Land Classification System from the perspective of land functions incorporating the concept of ecological land. The new land classification is more suitable to coordinate ecological,living and industrial land spaces. The Ecological-living-industrial Land Classification System includes three levels. The first level includes four major types：ecological regulation land,ecological-industrial land,industrial land,and living-industrial-ecological land. The second level subdivides dominant functions into 15 functional land categories. The third level is based on land cover types. According to zoning and re-classification,we extracted ecological-living-industrial land and their spatial distribution at a national scale. The area of ecological regulation land,ecological-industrial land,industrial land,and living-industrial land area are 6 037 000km2,1 353 800km2,2 001 900km2 and 207 300km2 respectively;accounting for 62.89%,14.10%,20.85% and 2.16% of total area,respectively. Ecological land are mainly locate in central and western China, ecological-industrial land reflects obvious regional differentiation,and industrial-ecological land and living-industrial land are concentrated in eastern China. {{custom_citation.content}}
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PDF(7462 KB)
Fig.1 Geographical location of the study areaFig.2 Trajectory analysis roadmap in the Yihe River Basin
Tab.1 Conversion cost matrixFig.3 Flowchart of FLUS model operationFig.4 Change of land use construction from 1975 to 2020 in the Yihe River BasinTab.2 Changes of land use dynamic degree from 1975 to 2020 in the Yihe River Basin 单位:%Fig.5 Spatial change of land use from 1975 to 2020 in the Yihe River BasinTab.3 The main change trajectories of land use from 1975 to 2020 in the Yihe River BasinFig.6 Spatial distribution of main land use change trajectories in the Yihe River BasinFig.7 Land use scenarios in 2030 and 2050 in the Yihe River BasinFig.8 Land use transfer structure from 2020 to 2050 in the Yihe River BasinTab.4 Dynamic degree of land use under different scenarios in the Yihe River Basin 单位:%Fig.9 Land use change under natural development scenario from 2020 to 2050 in the Yihe River BasinFig.10 Land use pattern of each counties under different scenarios in the Yihe River Basin in 2030/
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