Abstract
Numerous studies employed remote sensing techniques on regional air quality in terms of aerosols, in particular, the observations from polar-orbiting satellites offer more detail on spatial distribution. Since the air pollutants/aerosols dramatically vary in location with time, diurnal observations on a timescale are restricted by the temporal resolution of the polar-orbiting satellite. To address this issue, this research proposes a spatially and temporally adaptive reflectance fusion model for measuring atmospheric properties to synthesize high-spatial–temporal resolution images from polar and geostationary satellite imagery for air quality monitoring. The reflectivity from short-wave infrared is employed to preserve the atmospheric effect within the fused image in the green band for further aerosol optical depth (AOD) retrieval. Taking the Landsat-8 Operational Land Imager as the reference, the spatial resolution of the Himawari-8 Advanced Himawari Imager (in kilometers) can thus be resampled into 30 m every 10 min during the daytime, by considering the surface bidirectional reflectivity from the variation of the solar zenith angle. The AOD retrieved with fused images containing atmospheric effect could have a better performance after comparison with in situ measurements, and therefore, be suggested for high-spatial–temporal aerosol monitoring.
Highlights
Remote sensing imaging from satellites is widely applied to environmental monitoring, such as land cover analysis,[1,2] weather analysis,[3] and crop phenology monitoring.[4]
The fusion results from the spatial and temporal adaptive reflectance fusion model (STARFM) and STARFM-AP models are shown in Fig. 6, where the reference images are on November 16, 2015
The high-spatiotemporal resolution image of TOA reflectance is successfully fused with the proposed STARFM-AP approach from Himawari-8 AHI and Landsat-8 Operational Land Imager (OLI) images
Summary
Remote sensing imaging from satellites is widely applied to environmental monitoring, such as land cover analysis,[1,2] weather analysis,[3] and crop phenology monitoring.[4]. The monitoring of air pollutants is essential to understand and eliminate the effect and threat of suspended particles (atmospheric aerosols). Ground stations are widely used to monitor the air quality in particulate matter (PM) concentrations near the surface They can examine air quality effectively, the spatial resolution of ground stations is usually too coarse to support local phenomena.[9] With the advantage of wide coverage in regional or global scales, satellite observation becomes a better choice, with higher spatial information on air quality monitoring in Journal of Applied Remote Sensing
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