基于随机森林的遥感土地利用分类及景观格局分析
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国家重点研发计划(SQ2018YFGH000008)


Remote Sensing Land Usage Classification and Landscape Pattern Analysis Based on Random Forest
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    摘要:

    2009年福建平潭综合实验区设立,作为闽台合作及国家对外开放的窗口,其土地利用变化主要受社会经济因素的影响和自然地理环境的制约,也与未来的土地利用规划密切相关.本文利用1990、2000、2010和2017年4期Landsat遥感影像数据,定量分析近27年的土地利用变化对景观格局的影响.结果表明:(1)在选择合适训练样本的情况下,利用随机森林方法可获得较高的遥感土地利用分类精度(4期遥感影像分类的总体精度均在87%以上,Kappa系数均在0.84以上);(2)1990~2017年,水域面积急剧减少31.04 km2,流失的水域主要转化为建设用地和林地;建设用地增加40.98 km2,年平均增长1.52 km2.近十年呈快速增长趋势,年平均增长3.87 km2;(3)在斑块类型级别上,逐年增加的建设用地导致最大斑块占景观面积比例(LPI)、聚合度(AI)和边缘密度(ED)呈上升趋势,其中LPI受到建设用地增加的影响最显著.在景观类型级别上,多样性(SHDI)和景观形状(LSI)呈下降趋势.

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    In 2009, Fujian Pingtan Comprehensive Experimental Zone was established as a window for cooperation between Fujian and Taiwan and the country's opening to the outside world. Its land use change is mainly affected by social and economic factors and natural geographical environment, and is also closely related to future land use planning. Landsat remote sensing image data of 1990, 2000, 2010, and 2017 is used to quantitatively analyze the impact of land use change on landscape pattern in the past 27 years. The results show that:(1) high accuracy of remote sensing land use classification can be obtained by using random forest method when selecting suitable training samples (the overall accuracy of the 4 remote sensing image classifications is above 87%, and the Kappa coefficient is above 0.84). (2) From 1990 to 2017, the water area decreased sharply by 31.04 km2, and the lost water area is mainly converted into construction land and forest land; the construction land is increased by 40.98 km2, and the annual average growth is 1.52 km2. In the past ten years, it has shown a rapid growth trend with an average annual growth of 3.87 km2. (3) At the plaque type level, the construction land is increasing year by year. The largest plaques accounted for the proportion of landscape area (LPI), degree of polymerization (AI), and edge density (ED), and the LPI was most affected by the increase of construction land. At the landscape type level, diversity (SHDI) and landscape shape (LSI) are declining.

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周正龙,沙晋明,范跃新,帅晨,高尚.基于随机森林的遥感土地利用分类及景观格局分析.计算机系统应用,2020,29(2):40-48

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  • 收稿日期:2019-06-09
  • 最后修改日期:2019-07-05
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  • 在线发布日期: 2020-01-16
  • 出版日期: 2020-02-15
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