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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。
Taking the vegetation of Hetian area of Changting County, Fujian Province as the research object, the Landsat 5 and Landsat 8 remote sensing images of 2010 were selected to study the vegetation classification and vegetation type change based on the vegetation spectral characteristic curve and texture band . Accuracy verification showed that the total accuracy of vegetation classification in two years were 85.62% and 86.44% respectively, and the Kappa coefficients were 0.804 and 0.818 respectively. The results showed that the total area of vegetation was 590.40hm ~ 2 in Hetian area from 2010 to 2014, and the two types of vegetation were dominated by masson pine, accounting for more than 69% of the total area of vegetation in each year, while those in other vegetation types Area ratio varies. The analysis found that the policy support is the main driving force for the vegetation in this area to change during these four years. The research shows that the method can effectively classify the vegetation, and can accurately grasp the distribution and area of the vegetation in Hetian area, understand the changes and causes of the vegetation well, and provide scientific decision-making basis for soil erosion control and vegetation optimization.