基于高分2号遥感数据的三维绿量估算模型研究

发布时间：2018-11-05 09:18

【摘要】：本文通过结合遥感技术以及地理信息系统技术,以北京市朝阳区奥林匹克森林公园为研究对象,利用高分影像对该地区的森林植被进行了分类,提取了针叶林、阔叶林等,并以此进行了三维绿量遥感反演,结合实地调查的真实数据,计算出了该地区的三维绿量。论文中对2016年8月份北京市朝阳区奥林匹克森林公园的高分2号影像进行了植被信息的提取和分类,结合地面样地实际调查数据,采用多元回归分析方式建立了目标区域的三维绿量遥感反演模型,并通过模型对朝阳区奥林匹克森林公园进行了三维绿量的估算,建立了朝阳区的绿量分布专题图,本文研究主要的研究成果如下:(1)基于2016年3月份、6月份以及8月份的高分2号影像以及2016年8月份的landsat 8影像,结合2016年9、10月份的实地调查获取的每木检尺数据,利用抽样和主成分分析方法,对目标区域进行了遥感估测,分别得到基于高分2号影像的阔叶林和针叶林的反演回归模型,利用用于验证的剩余样方数据进行验证,其精度分别为85.03%和80.40%,结合国内外已有经验,模型精度达到80%即符合要求,因此模型满足需求。(2)通过对园区的针叶林和阔叶林分别建立的模型以及利用高分影像进行的植被分类信息,经过计算得出奥林匹克森林公园内阔叶林的三维绿量总和为506899.34 m~3,针叶林的三维绿量总和为215928.47m~3,由此得到北京市奥林匹克公园的总三维绿量为722827.81 m~3,同时得出南北园的植被分布状态,即南园进行了大量的人工干预,而北园地区存在开发空间。(3)本研究通过利用植被生态评价中的2个重要的因子即生态固碳和空气净化,对奥林匹克公园进行生态效益评价得到了该园区的固碳效果和空气净化效果,经过换算得出其对于对于减少空气中的二氧化碳和PM10具有较好的效果,其生态效果分别为117.8万元和125.4万元。
[Abstract]:In this paper, the forest vegetation in Chaoyang District of Beijing was classified by using high score image and the coniferous forest and broad-leaved forest were extracted by combining remote sensing technology and geographic information system technology, taking the Olympic Forest Park in Chaoyang District of Beijing as the research object. The 3D green quantity is retrieved by remote sensing and the real data of the field survey are used to calculate the 3D green quantity in this area. In this paper, the vegetation information is extracted and classified from the No. 2 image of the Olympic Forest Park in Chaoyang District, Beijing in August 2016. By using multivariate regression analysis, the 3D green quantity inversion model of the target area is established, and the three-dimensional green quantity estimation of the Olympic Forest Park in Chaoyang District is carried out through the model, and the thematic map of the distribution of green quantity in Chaoyang District is established. The main results of this study are as follows: (1) based on the high score 2 images in March, June and August 2016 and the landsat 8 image in August 2016, combined with the field survey in September and October 2016, By using the method of sampling and principal component analysis, the target area was estimated by remote sensing, and the inversion regression models of broad-leaved forest and coniferous forest based on high-score 2 image were obtained, respectively, and the residual sample data used for verification were used to verify the regression model of broad-leaved forest and coniferous forest. The accuracy of the model is 85.03% and 80.40% respectively. Therefore, the model can meet the demand. (2) the model of coniferous forest and broad-leaved forest in the park and the vegetation classification information based on high-score image are established separately. The total three dimensional green quantity of the broad-leaved forest in the Olympic Forest Park is 506899.34 mm2 and that of the coniferous forest is 215928.47 mm3, and the total three-dimensional green quantity of the Olympic Park in Beijing is 722827.81 mm3. At the same time, the vegetation distribution state of the north and south orchard is obtained, that is, the south garden has carried out a lot of artificial intervention, but there is space for development in the north garden area. (3) in this study, two important factors in vegetation ecological evaluation, namely, ecological carbon sequestration and air purification, are used. The carbon sequestration effect and air purification effect of the Olympic Park are obtained by ecological benefit evaluation. It is concluded that the Olympic Park has a better effect on reducing carbon dioxide and PM10 in the air by conversion. The ecological effects were 1.178 million yuan and 1.254 million yuan respectively.
【学位授予单位】：中国地质大学(北京)
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：P237

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