南方红壤典型水土流失区植被分类及植被类型变化的遥感评估——以福建省长汀县河田地区为例

发布时间：2018-04-30 06:53

本文选题：长汀县 + 遥感　；参考：《遥感技术与应用》2017年03期

【摘要】：以福建省长汀县河田地区的植被为研究对象,选取2010年Landsat 5和2014年Landsat 8遥感影像,基于影像的植被光谱特征曲线和纹理波段,对该区进行植被分类和植被类型变化的研究。精度验证表明,两年份的植被分类的总精度分别为85.62%和86.44%,Kappa系数分别为0.804和0.818。研究结果表明:2010~2014年间河田地区共增加植被面积590.40hm~2,并且两年份的植被类型均以马尾松为主,其面积占各自年份植被总面积的69%以上,而其它植被类型的面积比例各异。分析发现,政策的支持是该区植被在这4年间发生变化的主要驱动力。研究表明该方法能够有效地对植被进行分类,并且可以准确地掌握河田地区各植被的分布及面积,较好地了解各植被的变化及变化原因,为水土流失治理及植被优化提供科学决策依据。
[Abstract]:Taking the vegetation of Hetian area of Changting County, Fujian Province as the research object, the vegetation classification and vegetation type change in this area were studied based on the spectral characteristic curve and texture band of vegetation in 2010 Landsat 5 and 2014 Landsat 8 remote sensing images. The accuracy verification shows that the total accuracy of vegetation classification in the two years is 85.62% and 86.44% respectively, and the Kappa coefficient is 0.804 and 0.818 respectively. The results showed that the vegetation area increased by 590.40hmm-2 between 2010 and 2014, and the main vegetation types in the two years were Pinus massoniana, which accounted for more than 69% of the total vegetation area in their respective years, but the proportion of other vegetation types was different. It is found that the policy support is the main driving force of vegetation change in this area during the past four years. The research shows that this method can classify vegetation effectively, and can accurately understand the distribution and area of vegetation in river field, and better understand the change of vegetation and its reasons. It provides scientific decision basis for soil erosion control and vegetation optimization.
【作者单位】：福州大学环境与资源学院;福州大学遥感信息工程研究所;福建省水土流失遥感监测评估与灾害防治重点实验室;
【基金】：国家科技支撑项目(2013BAC08B01-05) 福建省教育厅重点项目(JA13030)
【分类号】：Q948;TP751

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