基于FLUS的长春市土地利用动态变化与预测分析

doi:10.13278/j.cnki.jjuese.20180312

吉林大学学报(地球科学版) ›› 2019, Vol. 49 ›› Issue (6): 1795-1804.doi: 10.13278/j.cnki.jjuese.20180312

基于FLUS的长春市土地利用动态变化与预测分析

王明常^1,2, 郭鑫¹, 王凤艳¹, 张馨月¹

1. 吉林大学地球探测科学与技术学院, 长春 130026;
2. 国土资源部城市土地资源监测与仿真重点实验室, 广东深圳 518000

收稿日期:2018-11-27 发布日期:2019-11-30
通讯作者: 郭鑫(1994-),男,硕士研究生,主要从事遥感技术与应用研究,E-mail:guoxin17@mails.jlu.edu.cn E-mail:guoxin17@mails.jlu.edu.cn
作者简介:王明常(1975-),男,教授,博士,主要从事遥感与地理信息系统研究,E-mail:wangmc@jlu.edu.cn
基金资助:
国家自然科学基金项目（41430322）；国土资源部城市土地资源监测与仿真重点实验室开放基金项目（KF-2018-03-020）；上海市地质调查研究院（国土资源部地面沉降检测与防治重点实验室）开放基金项目（KLLSMP201901）

Dynamic Change and Predictive Analysis of Land Use Types in Changchun City Based on FLUS Model

Wang Mingchang^1,2, Guo Xin¹, Wang Fengyan¹, Zhang Xinyue¹

1. College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China;
2. Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Land and Resources, Shenzhen 518000, Guangdong, China

Received:2018-11-27 Published:2019-11-30
Supported by:
Supported by National Natural Science Foundation of China(41430322),Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources(KF-2018-03-020)and the Opening Fund of Key Laboratory of Land Subsidence Monitoring and Prevention,Ministry of Land and Resources of China (KLLSMP201901)

摘要/Abstract

摘要： 研究城乡土地利用变化规律与驱动机制，有利于实现区域土地资源可持续发展。本文以长春市为例，以监督分类与人工解译相结合的方式对1997、2007和2017年Landsat卫星影像进行分类，总体精度分别为93.06%，90.70%和94.12%。1997-2017年，草地、耕地和其他土地面积分别减少354.74、922.11和55.35 km²，建设用地、水域和林地面积分别增加1 154.14、70.38和107.54 km²，整体表现为建设用地向周边扩张，侵占其他用地类型面积。利用未来土地利用模拟（future land use simulation，FLUS）模型，以2007年分类数据为基础，结合地形、交通区位和社会经济等土地利用变化驱动因子，仿真2017年土地利用格局，仿真结果与真实情况吻合较好，仿真精度达85.10%，Kappa系数为0.821 2，验证了模型和驱动因子精度可靠，符合土地利用变化趋势。以此模型因子预测2027年土地利用格局，结果表明：在城镇周围，建设用地将持续侵占耕地、林地、草地和其他土地的面积，但趋势减缓，同时林地面积和水域面积增加。

关键词: 动态变化, FLUS模型, 情景模拟, 预测分析, 长春市

Abstract: Studying the pattern and driving factors of urban and rural land use change is conducive to the sustainable development of regional land resources. Taking Changchun City as an example, combined with manual interpretation, the overall accuracy of the Landsat satellite supervised classification images in 1997, 2007 and 2017, is 93.06%, 90.70%,and 94.12%, respectively. From 1997 to 2017, the grassland, cultivated land and other land area decreased by 354.74 km², 922.11 km²,and 55.35 km² respectively, and the construction land, water area, and forest land increased by 1 154.14 km², 70.38 km², and 107.54 km² respectively. The overall trend is that the construction land expanded to the periphery and encroached on the area of other land types. Based on the 2007 classification data, combined with the driving factors of land use change of terrain, traffic location and social economy, the land use pattern was simulated for 2017 with FLUS (future land use simulation) model. The simulation is in good agreement with the real results. The simulation accuracy is 85.10%, Kappa coefficient is 0.821 2, and the verification model and the driving factors are reliable and consistent with the trend of land use change. The model is used to predict the land use pattern of 2027, showing that the construction land will slowly invade the area of cultivated land, forest land, grassland and other land around the town, and the area of forest land and water will increase.

Key words: dynamic change, FLUS model, scenario simulation, predictive analysis, Changchun City

中图分类号:

P237

王明常, 郭鑫, 王凤艳, 张馨月. 基于FLUS的长春市土地利用动态变化与预测分析[J]. 吉林大学学报(地球科学版), 2019, 49(6): 1795-1804.

Wang Mingchang, Guo Xin, Wang Fengyan, Zhang Xinyue. Dynamic Change and Predictive Analysis of Land Use Types in Changchun City Based on FLUS Model[J]. Journal of Jilin University(Earth Science Edition), 2019, 49(6): 1795-1804.

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基于FLUS的长春市土地利用动态变化与预测分析

Dynamic Change and Predictive Analysis of Land Use Types in Changchun City Based on FLUS Model

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