Remote Sensing of Lower Tropospheric Aerosols and Clouds over Islamabad Region Using a Self-Engineered Mie Scattering Lidar

Raza, Ghulam; Ashraf, Muhammad Aqueel; Qureshi, Shakir H.; Yasmin, Naila; Sarwar, N.

doi:10.1134/s1024856018060222

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…The average of angstrom exponent for recorded data is 1.42, this implies moderately polluted urban atmosphere of area under study. Similar trends about aerosol accumulations in lower tropshere have also been reported by few Mie Lidar based studies of región under study [33]. It is essential to realize that larger values of α, when the τ value for the larger wavelength is much smaller than the τ value for the smaller wavelength, implying a relatively high ratio of small particles to large (r > 0.5 µ) particles.…”

Section: B Measurement Of Aot By Locally Constructed Handheld Sunpsupporting

confidence: 80%

Aerosol Optical Thickness (AOT) mapping of Islamabad region using indigenously fabricated, locally-calibrated, economical sunphotometer and GLOBE sunphotometer

Raza¹,

Ashraf²,

Qureshi³

et al. 2019

Opt. Pura Apl.

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This study aims at ground based atmosphere monitoring for Islamabad region (33.7167°N and 73.667°E, 508 m altitude) using locally designed dual channels, (Green (550nm) and red (625nm)) LED based handheld sunphotometer. Calibration was done by using improvised transfer of calibration method employing pre-calibrated GLOBE (Global Learning and Observation to Benefit Environment) sunphotometer. Aerosol optical thickness (AOT) of said region for the month of July, August 2017 was calculated using acquired data for red and green channels. Matching trends (correlation up to 95%) were observed for AOT obtained with GLOBE and local sunphotometer. AOT of Islamabad region generated by satellitebased Moderate Resolution Imaging Spectro-radiometer (MODIS) instrument board on AQUA and Terra satellites has also been presented for calibration period (Oct 2016-Feb 2017) to qualify our findings. The inter-comparison of data with MODIS instrument AQUA and Terra from Oct 2016 to Feb. 2017 with the local sunphotometer green channel yielded a correlation coefficients in range of 0.51-0.55 approaching the previously reported range values of (∼0.55-0.60) for similar comparison. Along with AOT, in this study, the average daily Angstrom exponent α, and angstrom turbidity constant , have also been reported. The average of angstrom exponent for recorded data is 1.42, this implies moderately polluted urban atmosphere of area under study, while the 19 th and 20 th July are clearest day for monitoring period with = 0.07 and = 0.083 respectively.

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Section: B Measurement Of Aot By Locally Constructed Handheld Sunpsupporting

confidence: 80%

Aerosol Optical Thickness (AOT) mapping of Islamabad region using indigenously fabricated, locally-calibrated, economical sunphotometer and GLOBE sunphotometer

Raza¹,

Ashraf²,

Qureshi³

et al. 2019

Opt. Pura Apl.

Self Cite

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“…Mie scattering lidar is an effective and reliable detection remote sensing tool and can detect the optical and micro-physical properties of aerosol particles and clouds in the atmosphere accurately. 16 By using the scattering and attenuation generated by the interactions between particles or molecules in the atmosphere and the laser beam, the lidar equation can determine the detection distance for the energy backscatter signal, which is described as follows: 17…”

Section: Methodology a Mie Scattering Lidar Equationmentioning

confidence: 99%

A novel lidar signal denoising method based on variational mode decomposition optimized using whale algorithm

Zhao,

Mao

2024

Journal of Applied Physics

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Original lidar return signals are covered by high levels of noise that seriously affect the accuracy of subsequent data processing and inversion. Therefore, it is important to separate the effective signal from the returned signal with noise interference. In this paper, an efficient denoising method based on the variational mode decomposition (VMD) algorithm optimized using the global search strategy-based whale algorithm and the total variational stationary wavelet transform (GSWOA-VMD-SWTTV) is proposed, and this method is applied to denoising of lidar return signals. First, the global search strategy-based whale optimization algorithm (GSWOA) is used to acquire the optimal parameters of the VMD algorithm adaptively, and the lidar return signal is then decomposed by global search strategy-based whale optimization algorithm (GSWOA)-VMD. The effective modal components are then determined using the cross-correlation coefficient method from the decomposed modal components, and total variation stationary wavelet denoising is performed on each effective mode. Finally, the effective modes are reconstructed to obtain a clean lidar return signal. Moreover, to provide further verification of the effectiveness of the proposed method, it is compared with the ensemble empirical mode decomposition (EEMD) method, the complete EEMD with adaptive noise (CEEMDAN) method, the singular value decomposition (SVD) method, and the wavelet threshold method under sunny, cloudy, and dusty weather conditions. The experimental results demonstrate the superior noise reduction performance of the proposed algorithm, which can filter out strong noise from the signal while retaining the complete signal details without distortion; additionally, the proposed method has the highest signal-to-noise ratio and lowest mean square error.

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Remote Sensing of Lower Tropospheric Aerosols and Clouds over Islamabad Region Using a Self-Engineered Mie Scattering Lidar

Cited by 2 publications

References 12 publications

Aerosol Optical Thickness (AOT) mapping of Islamabad region using indigenously fabricated, locally-calibrated, economical sunphotometer and GLOBE sunphotometer

Aerosol Optical Thickness (AOT) mapping of Islamabad region using indigenously fabricated, locally-calibrated, economical sunphotometer and GLOBE sunphotometer

A novel lidar signal denoising method based on variational mode decomposition optimized using whale algorithm

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