Remote Sensing – Kamyar Fuladlu

Background
Urban air pollution is a dynamic mixture of Land Surface Temperature (LST), gases, particulate matter with daily and seasonal changes due to anthropogenic activities, Land-use Land-cover (LULC) transformations, and climatic conditions. The relationship between urban biophysical and thermal conditions, and LULC is generally known; however, the absence of a dense network of land-based meteorological stations is an obstacle to the comparison of LST to Major Air Pollutants (MAP).

Method
This research proposes investigation of the relationships between LST derived by Sentinel-3 SLSTR, MAP derived by Sentinel-5 Precursor, and air pollution monitoring system stations in Tehran province, Iran. The method is designed in a moving average model with the use of a Python application programming interface, geographical information system, and remote sensing.

Result
The mean concentration of the Particulate Matter (PM), Sulfur Dioxide (SO₂), and Nitrogen Dioxide (NO₂) are mainly in the Tehran metropolis and the core urban area. A negative correlation was noted between the PM₂.₅, SO₂, NO₂, and altitude. Additionally, increased altitude negatively affects LST, Carbon Monoxide (CO), and Ozone (O₃) values; whereas, CO and O₃ have positive correlations with LST, representing the mutual impacts of LST, CO, and O₃ values in Tehran province.

Monitoring urban sprawl is a controversial topic among scholars. Many studies have tried to employ various methods for monitoring urban sprawl in cases of North American and Northern and Western European cities. Although numerous methods have been applied with great success in various developed countries, they are predominantly impractical for cases of developing Mediterranean European cities that lack reliable census data. Besides, the complexity of the methods made them difficult to perform in underfunded situations. Therefore, this study aims to develop a new multidimensional method that researchers and planners can apply readily in developing Mediterranean European cities. The new method was tested in the Famagusta region of Northern Cyprus, which has been experiencing unplanned growth for the past half-century. In support of this proposal, a detailed review of the existing literature is presented with an emphasis on urban sprawl characteristics. Four characteristics were chosen to monitor urban sprawl’s development in the Famagusta region. The method was structured based on a time-series (2001, 2006, 2011, and 2016) dataset that used remote sensing data and geographical information systems to monitor the urban sprawl. Based on the findings, the Famagusta region experienced rapid growth during the last 15 years. The lack of a masterplan resulted in the uncontrolled expansion of the city in the exurban areas. The development configuration was polycentric and linear in form with single-use composition. Together, the expansion and configuration manifested as more built-up area, scattered development, and increased automobile dependency.

Category: Remote Sensing

Examining land surface temperature and relations with the major air pollutants: A remote sensing research in case of Tehran

Monitoring urban Sprawl using time-series data: Famagusta region of Northern Cyprus