Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran.
Department of Irrigation and Drainage, Tarbiat Modares University, Tehran 14115-336, Iran.
Sci Total Environ. 2021 Feb 25;757:143755. doi: 10.1016/j.scitotenv.2020.143755. Epub 2020 Nov 25.
A set of factors cause the Surface Ecological Status (SES) of urban areas to become largely different from the surrounding rural areas. Hence, the degree of poorness of SES in urban areas versus surrounding rural areas forms a zone, which is named Urban Surface Ecological Poorness Zone (USEPZ). The main objective of this study was to propose a new method to quantify USEPZ Intensity (USEPZI). To this end, Landsat-8 satellite images, water vapor products, and High Resolution Imperviousness Layer (HRIL) datasets of Budapest, Bucharest, Ciechanow, Hamburg, Lyon, Madrid, Porto, and Rome cities were used. Firstly, Single Channel (SC) algorithm, Tasseled cap transformation, and spectral indices were used to model the surface biophysical characteristics including Land Surface Temperature (LST), Wetness, Normalized Difference Vegetation Index (NDVI), and Normalized Difference Soil Index (NDSI). Then, SES was modeled based on the combination of surface biophysical characteristics using Remote Sensing-based Ecological Index (RSEI). Finally, the USEPZI was modeled based on the linear regression function obtained from RSEI-Impervious Surface Percentage (ISP) feature space. The spatial variability of the ISP, LST, NDVI, NDSI and Wetness of the selected cities was found to be heterogeneous. The coefficient of determination (R) between RSEI and ISP values for Budapest, Bucharest, Ciechanow, Hamburg, Lyon, Madrid, Porto, and Rome cities were obtained to be 0.99, 0.97, 0.98, 0.99, 0.98, 0.99, 0.99, and 0.94, respectively. Also, the USEPZI values of these cities were 0.14, 0.31, 0.41, 0.26, 0.40, 0.81, 0.44 and 0.46, respectively. Our findings show that the significant differences in their SES and USEPZI are due to the surface biophysical characteristics. The USEPZI in the selected cities with humid climate conditions was higher than the selected cities in dry climate conditions. Also, the use of the RSEI-ISP feature space is quite useful in modeling USEPZI of cities in different conditions.
一组因素导致城市地区的地表生态状况（SES）与周围农村地区有很大的不同。因此，城市地区 SES 的贫困程度与周围农村地区形成了一个地带，被命名为城市地表生态贫困带（USEPZ）。本研究的主要目的是提出一种量化 USEPZ 强度（USEPZI）的新方法。为此，使用了布达佩斯、布加勒斯特、切哈努夫、汉堡、里昂、马德里、波尔图和罗马城市的 Landsat-8 卫星图像、水汽产品和高分辨率不透水面层（HRIL）数据集。首先，使用单通道（SC）算法、缨帽变换和光谱指数来模拟包括地表温度（LST）、湿度、归一化植被指数（NDVI）和归一化差分土壤指数（NDSI）在内的地表生物物理特征。然后，基于地表生物物理特征的组合，利用基于遥感的生态指数（RSEI）来模拟 SES。最后，基于 RSEI-不透水面百分比（ISP）特征空间中获得的线性回归函数来模拟 USEPZI。发现所选城市的 ISP、LST、NDVI、NDSI 和湿度的空间变异性是不均匀的。布达佩斯、布加勒斯特、切哈努夫、汉堡、里昂、马德里、波尔图和罗马城市的 RSEI 与 ISP 值之间的决定系数（R）分别为 0.99、0.97、0.98、0.99、0.98、0.99、0.99 和 0.94。此外，这些城市的 USEPZI 值分别为 0.14、0.31、0.41、0.26、0.40、0.81、0.44 和 0.46。我们的研究结果表明，它们的 SES 和 USEPZI 存在显著差异，这是由于地表生物物理特征造成的。在湿润气候条件下的所选城市的 USEPZI 高于在干燥气候条件下的所选城市。此外，在不同条件下建模城市 USEPZI 时，使用 RSEI-ISP 特征空间非常有用。
