NIT Andhra Pradesh, Tadepalligudem, India.
Maturi Venkata Subba Rao Engineering College, Hyderabad, India.
Environ Monit Assess. 2022 Mar 7;194(4):258. doi: 10.1007/s10661-022-09901-0.
Urbanization affects the local wind and water cycle by changing the natural surface and atmospheric conditions, which further changes the local climate and climate system. Assessment of built-up-area changes in a rapidly growing urban area within a short time is a prime factor for administrators for better environmental assessment and sustainable development of urban areas. Traditional survey approaches, on the other hand, are unable to meet the demand for rapid urban land management development, and there is a pressing need to develop new methods to address the limitations of existing ones. This study compares various urban spectral indices to other existing approaches in order to determine which index provides a better representation of the impervious area in the urban watershed. Landsat 8 OLI (Operational Land Imager) satellite images acquired on 15 March 2014 and 31 March 2020 are used in the present study. Indices, namely Modified Built-up Index (MBUI), SwiRed Index (SwiRed), and Enhanced Built-up and Bareness Index (EBBI), were utilized to extract impervious areas. Thresholding of indices is done by comparing them with 1000 reference points taken from Google Earth imagery of the respective years. The accuracy of the urban indices is assessed by comparing the results with high-resolution Google Earth Satellite Images. The impervious area is extracted from spectral indices and other remote sensing techniques such as maximum likelihood classification and support vector machine classification techniques. The overall accuracy of SVM, MLC, MBUI, EBBI, and SwiRed for the 2014 dataset was found to be 95.1%, 90.8%, 83.9%, 78.9%, and 87.3%, respectively, and the overall accuracy of SVM, MLC, MBUI, EBBI, and SwiRed was found to be 96%, 89.2%, 89.1%, 85.5%, and 92.6%, respectively. Impervious areas in the heterogeneous urban environment can be monitored in a better way and within lesser time by using spectral indices generated using Landsat 8 OLI (Operational Land Imager) satellite data.
城市化通过改变自然表面和大气条件来影响当地的风和水的循环，从而进一步改变当地的气候和气候系统。在短时间内评估快速增长的城市地区的建成区变化，是管理者更好地评估环境和实现城市可持续发展的首要因素。另一方面，传统的调查方法无法满足快速城市土地管理发展的需求，迫切需要开发新的方法来解决现有方法的局限性。本研究比较了各种城市光谱指数与其他现有方法，以确定哪个指数能更好地代表城市流域的不透水面。本研究使用了 2014 年 3 月 15 日和 2020 年 3 月 31 日获取的 Landsat 8 OLI（陆地成像仪）卫星图像。利用修正的建筑指数（MBUI）、SwiRed 指数（SwiRed）和增强的建筑和裸土指数（EBBI）等指数来提取不透水面。通过将这些指数与来自各自年份的谷歌地球图像的 1000 个参考点进行比较，对这些指数进行阈值处理。通过将结果与高分辨率谷歌地球卫星图像进行比较，来评估城市指数的精度。通过光谱指数以及最大似然分类和支持向量机分类等其他遥感技术提取不透水面。SVM、MLC、MBUI、EBBI 和 SwiRed 对 2014 年数据集的总体精度分别为 95.1%、90.8%、83.9%、78.9%和 87.3%，SVM、MLC、MBUI、EBBI 和 SwiRed 的总体精度分别为 96%、89.2%、89.1%、85.5%和 92.6%。通过使用 Landsat 8 OLI（陆地成像仪）卫星数据生成的光谱指数，可以更好地监测异质城市环境中的不透水面，并在更短的时间内进行监测。
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