The spatial and temporal distribution of atmospheric pollutants (especially PM2.5), which may cause adverse effects on human health and the environment, are affected by urban vegetation through deposition and dispersion processes. Although lots of studies have been conducted to investigate this effect, we still lack the knowledge of how urban vegetation reduces PM2.5 and other air pollutions quantitatively. In this study, Landsat 8 data are used to retrieve the urban surface parameters (including Leaf Area Index and Normalized Difference Impervious Surface Index). Meanwhile, hourly PM 2.5 and other air pollutions concentrations over a period of one year (from Jan. 1, 2016 to Dec. 31, 2016) were obtained at a real-time air quality monitoring system in Shenzhen, P.R. China. It is found that, urban vegetation has little effect on air pollutants. Meanwhile, the results show that, a strong relationship between impervious surface and air pollutants are found.
In the past three decades, the Shenzhen city, which is located in south of China, has experienced a rapid urbanization process characterized by sharp decrease in farmland and increases in urban area. This rapid urbanization is one of the main causes of many environmental and ecological problems including urban heat island (UHI). Therefore, the monitoring of rapid urbanization regions and the environment is of critical importance for their sustainable development. In this study, Landsat-8 OLI and TIR images, which were acquired on 2013, are used to monitor urban heat island. After radiometric calibration and atmospheric correction with a simplified method for the atmospheric correction (SMAC) are applied to OLI image, an index-based build-up index (IBI), which is based on the soil adjusted vegetation index (SAVI), the modified normalized difference water index (MNDWI) and the normalized difference built-up index (NDBI), is employed to extract the build-up land features with a given thresholds. A single-channel algorithm is used to retrieve land surface temperature while the land surface emissivity is derived from a normalized differential vegetation index (NDVI) thresholds method. Surface urban heat island index (SUHII) and urban heat island ratio index (URI) are computed for ten districts of Shenzhen based on build-up land distribution and land surface temperature data. A correlation analysis is conducted between heat island index (including SUHII and URI) and socio-economic statistics (including total population and population density) also are included in this analysis. The results show that, a weak relationship between urban heat island and socio-economic statistics are found.
China, the most populous country on Earth, has experienced rapid urbanization which is one of the main causes of many environmental and ecological problems. Therefore, the monitoring of rapid urbanization regions and the environment is of critical importance for their sustainable development. In this study, the object-based classification is employed to detect the change of land cover in Shenzhen, which is located in South China and has been urbanized rapidly in recent three decades. First, four Landsat TM images, which were acquired on 1990, 2000 and 2010, respectively, are selected from the image database. Atmospheric corrections are conducted on these images with improved dark-object subtraction technique and surface meteorological observations. Geometric correction is processed with ground control points derived from topographic maps. Second, a region growing multi-resolution segmentation and a soft nearest neighbour classifier are used to finish object-based classification.
After analyzing the fraction of difference classes over time series, we conclude that the comparison of derived land cover classes with socio-economic statistics demonstrates the strong positive correlation between built-up classes and urban population as well as gross GDP and GDPs in second and tertiary industries. Two different mechanisms of urbanization, namely new land development and redevelopment, are revealed. Consequently, we found that, the districts of Shenzhen were urbanized through different mechanisms.
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