Estimation of surface visibility over Hong Kong using remote sensing

Pao Yue-kong Library Electronic Theses Database

Estimation of surface visibility over Hong Kong using remote sensing

 

Author: Shahzad, Muhammad Imran
Title: Estimation of surface visibility over Hong Kong using remote sensing
Degree: Ph.D.
Year: 2014
Subject: Remote sensing.
Visibility -- China -- Hong Kong.
Hong Kong Polytechnic University -- Dissertations
Department: Dept. of Land Surveying and Geo-Informatics
Pages: xv, 88 leaves : ill. (some col.) ; 30 cm.
Language: English
InnoPac Record: http://library.polyu.edu.hk/record=b2696087
URI: http://theses.lib.polyu.edu.hk/handle/200/7420
Abstract: The effects of deteriorating atmospheric visibility are more profound in rapidly growing and densely populated urban areas like Hong Kong. Existing methods to measure atmospheric visibility using ground based instruments have proven ineffective to depict regional visibility scenarios because a dense ground based network involving large cost and time is required. Previous efforts for satellite remote sensing of surface level visual range have mainly focused on stratified layers of fog, and all lack appropriate validation measurements for very clear and highly polluted days. In addition, their application in a highly polluted region like Hong Kong is untested. This study was designed to develop a remote sensing based methodology for measuring at-or-near ground level visual range (VR). The relationship between the surface extinction coefficient and columnar Aerosol Optical Depth (AOD) from four space borne sensors (MODIS, MISR, CALIPSO and OMI) was examined at two visibility recording stations; the Hong Kong Observatory (HKO) and the Hong Kong International Airport (HKIA). The highest correlation is for MISR AOD followed by MODIS AOD. MODIS AOD along with climatic data Relative Humidity (RH), Mixing Layer Height, Wind Speed (WS), Wind Direction (WD), Temperature (T), Pressure (P), V and U component of wind, advection terms VT and UT, mixing ratio (Q) and temporal change in T and P were subjected to regression analysis. A regression model using MODIS AOD, RH, VT and Q explained 84.0 % of the variance in VR with high accuracy demonstrated by a low RMSE of 0.27 km. The results of this study suggest that Q alone can explain the combined effect of P, T and RH on VR, whereas VT is sufficient to explain the effects of WS and WD on dispersion of aerosols and hence on VR. This study also proposes a new methodology to estimate VR using column-integrated aerosol physical properties from MODIS, ground-based LIDAR and AERONET sun photometer measurements of AOD. Results suggest that models utilizing satellite observations together with the near surface extinction coefficient from a visibility meter and LIDAR deployed at the Hong Kong Polytechnic University could reliably to estimate VR 35 km away at HKIA. VR estimates from the proposed models were found to be within 20 % of ground values which is consistent with requirements of the International Civil Aviation Organization. The models did not overestimate or underestimate VR for clean and/or polluted days, as exhibited by previous studies. Results demonstrate the potential for applying passive satellite depictions of broad-scale aerosol optical properties, and suggest that passive remote sensing exhibits the potential for enhancing the performance of pre-existing ground level visibility networks.

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