Estimating Particulate Matter Concentration over Arid Region Using Satellite Remote Sensing: A Case Study in Makkah, Saudi Arabia
- Nadzri Othman
- Mohd Mat Jafri
- Lim San
Abstract
The air quality indicator approximated by satellite measurements is known as an atmospheric particulate loading, which is evaluated in terms of the columnar optical thickness of aerosol scattering. The effect brought by particulate pollution has gained interest among researchers to study aerosol and particulate matter. In this study we presents the potentiality of retrieving concentrations of particulate matter with diameters less than ten micrometer (PM10) in the atmosphere using the Landsat 7 ETM+ slc-off satellite images over Makkah, Mina and Arafah. A multispectral algorithm is developed by assuming that surface condition of study area are lambertian and homogeneous. In situ PM10 measurements were collected using DustTrak aerosol monitor 8520 and their locations were determined by a handheld global positioning system (GPS). The multispectral algorithm model shows that PM10 high during Hajj season compared to other season. The retrieval dataset gives the accuracy > 0.8 of R coefficient value over Makkah, Mina and Arafah. These results provide confidence that the multispectral algorithm PM10 models can make accurate predictions of the concentrations of PM10.
- Full Text: PDF
- DOI:10.5539/mas.v4n11p131
Journal Metrics
(The data was calculated based on Google Scholar Citations)
h5-index (July 2022): N/A
h5-median(July 2022): N/A
Index
- Aerospace Database
- American International Standards Institute (AISI)
- BASE (Bielefeld Academic Search Engine)
- CAB Abstracts
- CiteFactor
- CNKI Scholar
- Elektronische Zeitschriftenbibliothek (EZB)
- Excellence in Research for Australia (ERA)
- JournalGuide
- JournalSeek
- LOCKSS
- MIAR
- NewJour
- Norwegian Centre for Research Data (NSD)
- Open J-Gate
- Polska Bibliografia Naukowa
- ResearchGate
- SHERPA/RoMEO
- Standard Periodical Directory
- Ulrich's
- Universe Digital Library
- WorldCat
- ZbMATH
Contact
- Sunny LeeEditorial Assistant
- mas@ccsenet.org