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作 者:马俊鹏 史科元 王晓飞[1] MA Junpeng;SHI Keyuan;WANG Xiaofei(College of Electronic Engineering,Heilongjiang University,Harbin 150080,China;College of Economics and Business Administration,Heilongjiang University,Harbin 150080,China)
机构地区:[1]黑龙江大学电子工程学院,哈尔滨150080 [2]黑龙江大学经济与工商管理学院,哈尔滨150080
出 处:《黑龙江大学自然科学学报》2024年第2期218-224,共7页Journal of Natural Science of Heilongjiang University
基 金:国家自然科学基金资助项目(61871150);国家重点研发计划项目(2016YFB0502502)。
摘 要:利用卫星遥感技术对哈尔滨市群力外滩生态湿地进行了信息提取和分析,评估了该湿地近几年水体和绿地面积的变化情况,探讨了开展绿色金融对该湿地生态保护发展的影响。通过目视解译与实地考察获取训练样本和验证点,采用最小距离法(Minimum distance,MD)、最大似然法(Maximum likelihood,ML)和支持向量机(Support vector machine,SVM)进行监督分类并对比其精度,选择更适合北方湿地信息提取的支持向量机的方法进行湿地分类。结合该湿地的生态特征,分析了绿色金融对该湿地的发展潜力和影响因素,并提出了具体的绿色金融策略和建议。研究结果表明,群力外滩生态湿地的水体和绿地面积在近几年稳步增长,说明该湿地保护和修复工作效果显著。By using satellite remote sensing technology,the information of the ecological wetland of Qunli Bund in Harbin has been extracted and analyzed.It evaluates the changes of water and green area of the wetland in recent years,and discusses the impact of green finance on the ecological protection and development of the wetland.The training samples and verification points are obtained through visual interpretation and field investigation,and the Minimum distance(MD)method,Maximum likelihood(ML)method and Support vector machine(SVM)are used for supervised classification and comparison of their accuracy,so as to select the support vector machine method that is more suitable for the information extraction of northern wetlands for wetland classification.Combined with the ecological characteristics of the wetland,the development potential and influencing factors of green finance on the wetland are analyzed,and specific green finance strategies and suggestions are put forward.The results show that the water and green area of the Qunli Bund ecological wetland have increased steadily in recent years,which indicates that the wetland protection and restoration work have a remarkable effect.
关 键 词:遥感图像处理 Sentinel-2 湿地分类 支持向量机 绿色金融
分 类 号:TP751[自动化与计算机技术—检测技术与自动化装置]
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