| 淮南市土地利用程度变化过程的时空演化特征 |
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| 引用本文： | 梁明,聂拼,陆胤昊,孙晓娟.淮南市土地利用程度变化过程的时空演化特征[J].农业工程学报,2019,35(22):99-106. |
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| 作者姓名： | 梁明 聂拼 陆胤昊 孙晓娟 |
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| 作者单位： | 1. 安徽大学资源与环境工程学院，合肥 230601；2. 安徽大学安徽省矿山生态修复工程实验室，合肥 230601,3. 南京大学地理与海洋科学学院，南京 210023,1. 安徽大学资源与环境工程学院，合肥 230601；2. 安徽大学安徽省矿山生态修复工程实验室，合肥 230601,4. 武汉大学资源与环境科学学院，武汉 430079 |
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| 基金项目： | 国家自然科学基金（41602173，41771188）；安徽省自然科学基金（1908085QD164）；安徽省高等学校自然科学研究项目（KJ2019A0046）；安徽省国土厅科技项目（2016-K-12） |
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| 摘 要： | 土地利用变化研究中存在重格局轻过程、重模拟轻度量的现象,缺乏对序列快照间土地利用单元演化过程的时空模式的探查和度量研究。该文以土地利用变化的序列时空数据为研究对象,以时空栅格为建模手段,以土地利用程度累积变化度为时空过程的基本度量工具,对淮南市土地利用变化过程的时空模式进行分析。结果表明:2008—2017年间研究区的土地利用程度的剧烈变化在特定尺度下呈现显著的时空聚集性特征;同时土地利用程度的平缓变化也呈现出较为显著的时空聚集性特征;介于二者之间的较为剧烈的土地利用程度变化的时空聚集性不显著,表明研究时段人类干扰活动具有明显的时空异质性。进一步研究发现,3种土地利用程度在距离交通网络较近的范围内(300和600 m范围内)均呈现聚集性,而在更远的距离上(900 m范围内)趋于随机分布,表明交通网络对土地利用变化具有较强烈的影响;在距离交通网络的不同空间尺度上,土地利用程度的剧烈变化和平缓变化在较小的空间尺度上时空聚集性呈现显著性,而较为剧烈的土地利用程度变化在多个尺度上的时空聚集性都不显著,表明交通网络对土地利用程度时空变化的影响存在尺度差异,且较为极端的土地利用变化过程更容易呈现时空聚集性。
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| 关 键 词： | 土地利用 遥感 时空过程 时空聚集性 土地利用程度 最邻近距离 |
| 收稿时间： | 2019/1/2 0:00:00 |
| 修稿时间： | 2019/8/15 0:00:00 |
Spatiotemporal evolution characteristics of land use intensity change process of Huainan |
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| Liang Ming,Nie Pin,Lu Yinhao and Sun Xiaojuan.Spatiotemporal evolution characteristics of land use intensity change process of Huainan[J].Transactions of the Chinese Society of Agricultural Engineering,2019,35(22):99-106. |
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| Authors: | Liang Ming Nie Pin Lu Yinhao and Sun Xiaojuan |
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| Institution: | 1. School of Resources and Environmental Engineering, Anhui University, Hefei 230601, China; 2. Anhui Province Engineering Laboratory for Mine Ecological Rmediation, Anhui University, Hefei 230601, China;,3. School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China,1. School of Resources and Environmental Engineering, Anhui University, Hefei 230601, China; 2. Anhui Province Engineering Laboratory for Mine Ecological Rmediation, Anhui University, Hefei 230601, China; and 4. School of Resource and Environment Sciences, Wuhan University, Wuhan 430079, China |
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| Abstract: | Abstract: Land use and coverage change (LUCC) is an important research field of global change. Currently, land use and coverage change research focuses on the analysis of land use structures during the same period, and structure changes in the overall quantity of land use between time-series periods. While, the study of quantitative analysis of land use evolution process in different periods is deficient, which results difficulty to profoundly reveal the temporal and spatial patterns and evolution laws that may exist in the process of land change. Therefore, in this paper, we proposed a spatiotemporal pattern analysis of land use change based on the spatiotemporal process of land use. In this paper, the spatiotemporal variation sequence data of land use was the study object. Firstly, the spatiotemporal variation sequence of land use intensity in the study area was extracted by the spatiotemporal network. Secondly, as the basic measurement tool, the cumulative value of land use intensity change (CVLUIC) of different spatiotemporal variation sequences of land use was calculated. Thirdly, the CVLUIC is divided into three grades by K-means clustering. Finally, the spatiotemporal clustering analysis of different land use change grades was carried out. From the global perspective, the spatiotemporal pattern of land use change process was measured by the nearest neighbor distance analysis method. On the other hand, based on Ripley''s k function, the multi-scale impact of traffic network on land use temporal and spatial change patterns was analyzed. The results showed that the dramatic land use intensity change (Type I) and the gradual land use intensity change (Type III) over the 10-year period from 2008 to 2017 in the study area showed significant clustering characteristics. While, the spatiotemporal clustering characteristics of the more severe land use intensity change (Type II) between Type I and Type III was not significant, The results showed that the human disturbance activities have obvious spatiotemporal heterogeneity during the study period. Additionally, the traffic network had a strong influence on land use and coverage change. The three types of land use intensity were clustered in the range close to the traffic network (in the range of 300 m and 600 m), and tend to be randomly distributed in the farther distance (within 900 m), which showed that the transportation network had a strong impact on land use change. At different spatial scales from the transportation network, the dramatic land use intensity change (Type I) and the gradual land use intensity change (Type III) showed significant significance on the small spatial scale, while the more severe land use intensity change (Type II) at multiple scales was not significant. This indicated that there were scale differences in the impact of transportation network on spatial and temporal changes of land use degree, and more extreme land use change processes (Type I and Type III) were more likely to show spatial and temporal aggregation. Through analyzing the land use change from the perspective of the spatiotemporal evolution process, our work will be useful supplement to the LUCC research. |
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| Keywords: | land use remote sensing spatiotemporal process spatiotemporal clustering land use intensity nearest neighbor distance |
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