摘要
随着城市化进程加快,城市绿色空间在改善城市生态环境、提升居民生活质量、调节城市气候等方面的重要性日益凸显。然而,在城市快速扩张和土地资源高强度利用的背景下,城市绿色空间面临着面积减少、布局不合理和质量下降等问题。因此,如何实现对城市绿色空间资源的动态、精准监测,已成为城市规划与生态管理中的关键课题。提出一种融合遥感影像的城市绿色空间资源动态监测方法,通过分析绿色空间资源的动态变化信息,可为城市规划和管理提供及时、准确的数据支持。提出的方法为:首先建立遥感影像降质模型,以预测并校正影像中分辨率低、模糊、几何形变及噪声等因素;随后,通过对多帧影像的超分辨率参数进行重构,恢复遥感影像的高分辨率细节;接着,对遥感影像实施雾噪处理,并将处理后的影像数据进行拼接与配准,生成数字正射影像图(DOM)和数字表面模型(DSM);最后,通过比对不同时间点的城市绿色空间DSM,识别出城市绿色空间资源的变化规律和趋势,从而实现城市绿色空间资源的动态监测。试验结果表明:该方法监测出城市绿地面积变化,并且该方法处理后的影像更加清晰,保留了影像的边缘轮廓信息。
With the continuous acceleration of urbanization,the importance of urban green space in improving the urban ecological environment,improving residents'life quality and regulating urban climate is becoming increasingly prominent.However,in the context of rapid urban expansion and high-intensity utilization of land resources,urban green spaces face such problems as reduced area,unreasonable layout and quality decline.Therefore,how to achieve dynamic and precise monitoring for urban green space resources has become a key issue in urban planning and ecological management.So a dynamic monitoring method for urban green space resources integrating remote sensing images is proposed in this paper.By analyzing the dynamic change information of green space resources,timely and accurate data support can be provided for urban planning and management.The proposed method here is to firstly establish a remote sensing image degradation model so as to predict and correct factors such as low resolution,blur,geometric deformation and noise in the image.Subsequently,the high-resolution details of the remote sensing image are restored by reconstructing the super-resolution parameters of the multi-frame image.Next,the remote sensing image is subjected to fog noise processing,and the processed image data is spliced and registered to generate a digital orthophotograph(DOM)and a digital surface model(DSM).Finally,by comparing urban green space DSM at different time points,the change patterns and trends of urban green space resources are identified,thereby realizing dynamic monitoring of urban green space resources.The experimental results show that this method can monitor the changes in urban green space and the image processed by this method is clearer,retaining the edge profile information of the image.
作者
李鹏
张彬彬
LI Peng;ZHANG Binbin(Chongqing Institute of Surveying and Mapping,Chongqing 401121,China;Smart City Spatio-temporal Information and Equipment Technology Innovation Center of the Ministry of Natural Resources,Chongqing 401121,China;Fujian Academy of Building Research Co.,Ltd.,Fujian Key Laboratory of Green Building Technology,Fuzhou 350100,China)
出处
《经纬天地》
2025年第4期59-63,共5页
Survey World
关键词
遥感影像
降质模型
城市绿色空间
资源动态监测
remote sensing image
degradation model
urban green space
dynamic resource monitoring
