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Monitoring Annual Urban Changes in a Rapidly Growing Portion of Northwest Arkansas with a 20-Year Landsat Record

机译:监测具有20年Landsat记录的西北阿肯色州快速增长地区的年度城市变化

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Northwest Arkansas has undergone a significant urban transformation in the past several decades and is considered to be one of the fastest growing regions in the United States. The urban area expansion and the associated demographic increases bring unprecedented pressure to the environment and natural resources. To better understand the consequences of urbanization, accurate and long-term depiction on urban dynamics is critical. Although urban mapping activities using remote sensing have been widely conducted, long-term urban growth mapping at an annual pace is rare and the low accuracy of change detection remains a challenge. In this study, a time series Landsat stack covering the period from 1995 to 2015 was employed to detect the urban dynamics in Northwest Arkansas via a two-stage classification approach. A set of spectral indices that have been proven to be useful in urban area extraction together with the original Landsat spectral bands were used in the maximum likelihood classifier and random forest classifier to distinguish urban from non-urban pixels for each year. A temporal trajectory polishing method, involving temporal filtering and heuristic reasoning, was then applied to the sequence of classified urban maps for further improvement. Based on a set of validation samples selected for five distinct years, the average overall accuracy of the final polished maps was 91%, which improved the preliminary classifications by over 10%. Moreover, results from this study also indicated that the temporal trajectory polishing method was most effective with initial low accuracy classifications. The resulting urban dynamic map is expected to provide unprecedented details about the area, spatial configuration, and growing trends of urban land-cover in Northwest Arkansas.
机译:西北阿肯色州在过去的几十年中经历了重大的城市转型,被认为是美国发展最快的地区之一。城市面积的扩大以及相关的人口增长给环境和自然资源带来了前所未有的压力。为了更好地理解城市化的后果,对城市动态进行准确,长期的描述至关重要。尽管已经广泛进行了使用遥感的城市制图活动,但以每年的速度进行长期城市增长制图的情况很少,而且变化检测的低准确性仍然是一个挑战。在这项研究中,采用涵盖1995年至2015年的时间序列Landsat堆栈,通过两阶段分类方法来检测阿肯色州西北部的城市动态。最大似然分类器和随机森林分类器中使用了一组已证明对市区提取有用的光谱指数以及原始的Landsat光谱带,以每年区分市区和非市区像素。然后将涉及时间过滤和启发式推理的时间轨迹抛光方法应用于分类的城市地图序列,以进行进一步改进。基于五个不同年份的一组验证样本,最终抛光图的平均总体准确度为91%,从而将初步分类提高了10%以上。此外,这项研究的结果还表明,时间轨迹抛光方法对于最初的低精度分类最有效。预期由此产生的城市动态图将提供有关阿肯色州西北部城市土地面积,空间配置和增长趋势的空前细节。

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