Ceyhan Engineering Faculty, Department of Geomatics Engineering, Cukurova University, 01950, Ceyhan, Adana, Turkey.
Engineering Faculty, Department of Geomatics Engineering, Bulent Ecevit University, 67100, Zonguldak, Turkey.
Environ Monit Assess. 2018 Jun 7;190(7):381. doi: 10.1007/s10661-018-6767-3.
Rapid and irregular urbanization is an essential issue in terms of environmental assessment and management. The dynamics of landscape patterns should be observed and analyzed by local authorities for a sustainable environment. The aim of this study is to determine which spectral urban index, originated from old Landsat missions, represents impervious area better when new generation Earth observation satellite Landsat 8 data are used. Two datasets of Landsat 8, acquired on 2 September 2013 and 10 September 2016, were utilized to investigate the consistency of the results. In this study, commonly used urban indices namely normalized difference built-up index (NDBI), index-based built-up index (IBI), urban index (UI), and enhanced built-up and bareness index (EBBI) were utilized to extract impervious areas. The accuracy assessment of urban indices was conducted by comparing the results with pan-sharpened images, which were classified using maximum likelihood classification (MLC) method. The kappa values of MLC, IBI, NDBI, EBBI, and UI for 2013 dataset were 0.89, 0.79, 0.71, 0.59, and 0.49, respectively, and the kappa values of MLC, IBI, NDBI, EBBI, and UI for 2016 dataset were 0.90, 0.78, 0.70, 0.56, and 0.47, respectively. In addition, area information was extracted from indices and classified images, and the obtained outcomes showed that IBI presented better results than the other urban indices, and UI extracted impervious areas worse than the other indices in both selected cases. Consequently, Landsat 8 satellite data can be considered as an important source to extract and monitor impervious surfaces for the sustainable development of cities.
快速和不规则的城市化是环境评估和管理方面的一个重要问题。地方当局应该观察和分析景观格局的动态，以实现环境的可持续性。本研究的目的是确定哪些光谱城市指数，源于旧的 Landsat 任务，当使用新一代地球观测卫星 Landsat 8 数据时，能更好地代表不透水面。利用 2013 年 9 月 2 日和 2016 年 9 月 10 日获取的两个 Landsat 8 数据集来研究结果的一致性。在这项研究中，利用了常用的城市指数，即归一化差异建筑指数（NDBI）、基于指数的建筑指数（IBI）、城市指数（UI）和增强的建筑和裸土指数（EBBI）来提取不透水面。通过将结果与使用最大似然分类（MLC）方法分类的锐化图像进行比较，对城市指数的精度进行了评估。2013 年数据集的 MLC、IBI、NDBI、EBBI 和 UI 的 kappa 值分别为 0.89、0.79、0.71、0.59 和 0.49，而 2016 年数据集的 MLC、IBI、NDBI、EBBI 和 UI 的 kappa 值分别为 0.90、0.78、0.70、0.56 和 0.47。此外，从指数和分类图像中提取了面积信息，结果表明，在两个选定案例中，IBI 比其他城市指数表现更好，而 UI 提取的不透水面比其他指数差。因此，Landsat 8 卫星数据可以被视为提取和监测城市可持续发展中不透水面的重要来源。
