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Hyperspectral Sensor Data Capability for Retrieving Complex Urban Land Cover in Comparison with Multispectral Data: Venice City Case Study (Italy)

机译:与多光谱数据相比用于提取复杂城市土地覆盖物的高光谱传感器数据功能:威尼斯市区案例研究(意大利)

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摘要

This study aims at comparing the capability of different sensors to detect land cover materials within an historical urban center. The main objective is to evaluate the added value of hyperspectral sensors in mapping a complex urban context. In this study we used: (a) the ALI and Hyperion satellite data, (b) the LANDSAT ETM+ satellite data, (c) MIVIS airborne data and (d) the high spatial resolution IKONOS imagery as reference. The Venice city center shows a complex urban land cover and therefore was chosen for testing the spectral and spatial characteristics of different sensors in mapping the urban tissue. For this purpose, an object-oriented approach and different common classification methods were used. Moreover, spectra of the main anthropogenic surfaces (i.e. roofing and paving materials) were collected during the field campaigns conducted on the study area. They were exploited for applying band-depth and sub-pixel analyses to subsets of Hyperion and MIVIS hyperspectral imagery. The results show that satellite data with a 30m spatial resolution (ALI, LANDSAT ETM+ and HYPERION) are able to identify only the main urban land cover materials.
机译:这项研究旨在比较不同传感器检测历史城市中心内土地覆盖物的能力。主要目标是评估高光谱传感器在绘制复杂城市环境中的附加值。在这项研究中,我们使用:(a)ALI和Hyperion卫星数据,(b)LANDSAT ETM +卫星数据,(c)MIVIS机载数据,以及(d)高空间分辨率IKONOS图像作为参考。威尼斯市中心显示出复杂的城市土地覆盖,因此被选为测试在绘制城市组织时不同传感器的光谱和空间特征。为此,使用了一种面向对象的方法和不同的通用分类方法。而且,在研究区域进行的野外活动期间,收集了主要的人为表面(即屋顶和铺路材料)的光谱。它们被用于将波段深度和亚像素分析应用于Hyperion和MIVIS高光谱图像的子集。结果表明,空间分辨率为30m的卫星数据(ALI,LANDSAT ETM +和HYPERION)仅能识别主要的城市土地覆盖材料。

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