Abstract
Air pollution continues to attract more and more public attention. Space-based infrared sensors provide a measure to monitor air quality in large areas. In this paper, a band selection procedure of space-based infrared sensors is proposed for urban air pollutant detection, in which observation geometry, ground and atmosphere radiant characteristics, and sensor system noise are integrated. The physics-based atmospheric radiative transfer model is reviewed and used to calculate total spectral radiance at the sensor aperture. Spectral filters with different central wavelength and bandwidth are designed to calculate contrasts in various bands, which can be presented as a two-dimensional matrix. Minimal available bandwidth and signal-to-noise ratio threshold are set to characterize the impacts of the sensor system. In this way, the band with higher contrast is assumed to have better detection performance. The proposed procedure is implemented to analyze an optimal band for detecting four types of gaseous pollutants and discriminating aerosol particle pollution to demonstrate usefulness. Simulation results show that narrower bands tend to achieve better performance while the optimal band is related to the available minimal bandwidth and pollutant density. In addition, the bands that are near optimal can achieve similar performance.
Highlights
Air pollution, a byproduct of industrialization, urbanization, and economic development, is drawing more and more public attention, since different levels of air pollutant concentration have various adverse impacts on public health [1,2]
We propose a band selection procedure of space-based infrared sensors for urban air pollutant urban aerosol to the total radiance through rural aerosol
The discussion demonstrates the importance of considering Signal-to-Noise Ratios (SNRs) in optimal band polluted area to the unpolluted area is calculated in various bands to characterize the sensitivity of selection
Summary
A byproduct of industrialization, urbanization, and economic development, is drawing more and more public attention, since different levels of air pollutant concentration have various adverse impacts on public health [1,2]. An atmospheric radiative transfer model was built and upgraded at high spectral resolution [52,53] while an infrared sensor system model was developed for detection performance analysis [54] These models have been used to simulate radiant images [55] and analyze an optimal band for dim target detection [56]. A band selection procedure of space-based infrared sensors is proposed for urban air pollutant detection, in which observation geometry, ground and atmosphere radiant characteristics, and sensor system noise are integrated. The calculation model for atmospheric radiative transfer characteristic is introduced, where the theoretical relevance between the pollutant density and the spectral radiance at the aperture of the space-based infrared sensor is detailed.
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