文章基本信息

标题：IMPROVING AADT AND VDT ESTIMATION WITH HIGH-RESOLUTION SATELLITE IMAGERY
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作者：Mark McCord ; Prem Goel ; Zhuojun Jiang 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2002
卷号：XXXIV Part 1
出版社：Copernicus Publications
摘要：State departments of transportation (DOTs), as well as national agencies in many countries, invest heavily in personnel and equipment to collect the data supporting the estimation of Average Annual Daily Traffic (AADT) and Vehicle Distance Traveled (VDT). Satellite- and air-based imagery can provide additional data for estimation and offers certain advantages over traditional ground-based sensors. Vehicles are evident in high-resolution satellite imagery, and we are developing algorithms that can automatically identify vehicles in 1-m resolution panchromatic imagery. However, the imagery only provides very short duration observation, whereas traditional estimation methods are based on traffic volumes measured over extended intervals of time. We revie w and present additional empirical comparisons between image-based AADT estimates and traditionally produced estimates that lead to an estimate of the error involved with expanding an image to an AADT estimate. The error appears unbiased with a relatively low standard deviation. Real value would likely only be produced when using the image-based estimates on a large-scale, regular basis. We therefore developed software to simulate AADT and VDT estimation errors when using traditional ground- based samples only and when adding satellite-based data to the ground-based samples. We review and present additional simulation results indicating that DOTs could markedly decrease labor-intensive ground-based sampling efforts while improving AADT and VDT estimation