首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >SUBTYPE COASTLINE DETERMINATION IN URBAN COAST BASED ON MULTISCALE FEATURES: A CASE STUDY IN TIANJIN, CHINA
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SUBTYPE COASTLINE DETERMINATION IN URBAN COAST BASED ON MULTISCALE FEATURES: A CASE STUDY IN TIANJIN, CHINA

机译:基于多尺度特征的城市海岸亚型海岸线确定-以天津市为例

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In urban coast, coastline is a direct factor to reflect human activities. It is of crucial importance to the understanding of urban growth, resource development and ecological environment. Due to complexity and uncertainty in this type of coast, it is difficult to detect accurate coastline position and determine the subtypes of the coastline. In this paper, we present a multiscale feature-based subtype coastline determination (MFBSCD) method to extract coastline and determine the subtypes. In this method, uncertainty-considering coastline detection (UCCD) method is proposed to separate water and land for more accurate coastline position. The MFBSCD method can well integrate scale-invariant features of coastline in geometry and spatial structure to determine coastline in subtype scale, and can make subtypes verify with each other during processing to ensure the accuracy of final results. It was applied to Landsat Thematic Mapper (TM) and Operational Land Imager (OLI) images of Tianjin, China, and the accuracy of the extracted coastlines was assessed with the manually delineated coastline. The mean ME (misclassification error) and mean LM (Line Matching) are 0.0012 and 24.54?m respectively. The method provides an inexpensive and automated means of coastline mapping with subtype scale in coastal city sectors with intense human interference, which can be significant for coast resource management and evaluation of urban development.
机译:在城市海岸,海岸线是反映人类活动的直接因素。这对于理解城市增长,资源开发和生态环境至关重要。由于这类海岸的复杂性和不确定性,很难检测到准确的海岸线位置并确定海岸线的子类型。在本文中,我们提出了一种基于多尺度特征的亚型海岸线确定(MFBSCD)方法,以提取海岸线并确定亚型。在这种方法中,提出了考虑不确定性的海岸线检测(UCCD)方法,以将水和土地分开,以实现更准确的海岸线位置。 MFBSCD方法可以很好地整合海岸线在几何形状和空间结构上的尺度不变特征,从而确定亚型尺度上的海岸线,并可以使子类型在处理过程中相互验证,以确保最终结果的准确性。将其应用于中国天津的Landsat Thematic Mapper(TM)和Operational Land Imager(OLI)图像,并使用人工绘制的海岸线评估了提取的海岸线的准确性。平均ME(误分类误差)和平均LM(线匹配)分别为0.0012和24.54?m。该方法提供了一种廉价且自动化的海岸线地图,该地图可以在人为干扰严重的沿海城市地区以亚型比例绘制海岸线,这对于海岸资源管理和城市发展评估具有重要意义。

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