空间

Alberto Amore
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引用次数: 0

摘要

本研究的重点是加利福尼亚州圣巴巴拉和戈莱塔的城市地区,该地区的特点是城市土地覆盖类型和表面材料的多样化组合,包括各种类型的屋顶和不同的道路类型和条件。2000年6月9日,NASA-JPL机载可见光/红外成像光谱仪(AVIRIS)获得了高光谱遥感数据。AVIRIS传感器记录了224个波段,每个波段的带宽约为10 nm,覆盖了350至2500 nm的光谱范围。该数据集的空间分辨率约为4米,可与IKONOS等当前高分辨率星载传感器系统相媲美。这些数据满足一般提出的用于详细城市区域制图的小于5米的空间分辨率标准(Welch 1982, Jensen和Cowen 1999),并且高光谱分辨率非常适合用于比较土地覆盖制图。这些数据由位于帕萨迪纳的喷气推进实验室(JPL)和加州大学圣巴巴拉分校(UCSB)进行了密集处理,用于运动补偿和减少几何扭曲。使用改进的Modtran辐射传输模型将AVIRIS数据处理为表观表面反射率(Green等,1993;Roberts et al. 1997),并使用地面反射率目标进行调整(Clark et al. 1993)。AVIRIS城市光谱库的开发基于地面观测和制图的综合训练数据集,该数据集是为土地覆盖分类制图而开发的(见Herold et al. 2003)。光谱库包括26种不同的覆盖类型,包含956个单独的光谱。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Space
This study focuses on the urban area of Santa Barbara and Goleta, California that is characterized by a versatile mix of urban land cover types and surface materials including various categories of roofs and different road types and conditions. The hyperspectral remote sensing data from NASA-JPL’s Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) were acquired on June 9 th , 2000. The AVIRIS sensor records 224 spectral bands with a bandwidth of ~ 10 nm each, covering a spectral range from 350 to 2500 nm. The data set was acquired at a spatial resolution of approximately 4 meters, comparable to current high-resolution space-borne sensor systems like IKONOS. The data meet the generally proposed spatial resolution standard of less than 5 m for detailed urban area mapping (Welch 1982, Jensen and Cowen 1999), and the high spectral resolution lends itself well to comparative land cover mapping. The data were intensely processed by the Jet Propulsion Laboratory (JPL) in Pasadena and the University of California, Santa Barbara (UCSB) for motion compensation and reduction of geometric distortions. The AVIRIS data were processed to apparent surface reflectance using a modified Modtran radiative transfer model (Green et al. 1993; Roberts et al. 1997) and adjusted using a ground reflectance target (Clark et al. 1993). The development of the AVIRIS urban spectral library was based on a comprehensive training dataset from ground observations and mapping that was developed for land cover classification mapping purposes (see Herold et al. 2003). The spectral library includes 26 different cover types and contains 956 individual spectra.
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