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Mid-resolution multi-temporal mapping of urban areas through a hybrid approach A case study for Milan province, Italy

机译:通过混合方法对城市区域进行中分辨率多时相制图-以意大利米兰省为例

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Remotely sensed data and related processing techniques have proven an effective tool for urban areas study, so that the integration of such products with other cartographic and thematic mapping products can help the management of the urban environment and ease the work of policy makers in city planning and administration. The focus of this work is on the topic of urban areas mapping over province administrative unit of Milan, Italy, using mid-resolution remote sensing data covering the last 20 years. In detail, for years 2008 and 1998 SPOT4 HRVIR data were used, while for 1989 Landsta5 TM data were used. The methodology applied consisted of three main steps; the first step exploits a pixel-based binary cascade thresholding of spectral bands and spectral indexes, which resulted in a 10 classes land cover map comprising both urban and non urban features. The second step filters the pixel-based urban maps using an object-base approach to map agricultural cover features as vegetated and bare fields, better distinguished as objects for their spatial texture and homogeneity. The third step involves the joining of land cover classes into two main classes: urbanized and non urbanized surfaces, and a final polishing of results made with expert knowledge visual interpretation of both satellite images and ancillary vector data. Final derived urban maps have been validated and demonstrated to provide good accuracy, with Overall Accuracy higher than 87% for automatically derived products and higher than 93% for expert refined products.
机译:事实证明,遥感数据和相关处理技术是进行城市地区研究的有效工具,因此,将此类产品与其他制图和专题制图产品集成在一起可以帮助管理城市环境,并简化政策制定者在城市规划和规划中的工作。行政。这项工作的重点是使用覆盖过去20年的中分辨率遥感数据,对意大利米兰省行政区的城市区域进行制图。详细地说,使用了2008年和1998年的SPOT4 HRVIR数据,而使用了1989年的Landsta5 TM数据。所采用的方法包括三个主要步骤;第一步采用了基于像素的光谱带和光谱指数的二进制级联阈值,从而生成了包括城市和非城市特征的10类土地覆盖图。第二步,使用基于对象的方法对基于像素的城市地图进行过滤,以将农业植被特征映射为植被和裸露的田野,由于其空间纹理和同质性,可以更好地区分为对象。第三步涉及将土地覆盖类别分为两个主要类别:城市化和非城市化表面,以及对专家知识的卫星图像和辅助矢量数据的视觉解释最终得出的结果。最终衍生的城市地图已经过验证和演示,可提供良好的准确性,自动衍生产品的总体准确度高于87%,专家精制产品的总体准确度高于93%。

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