Estimation of PM10 Distribution using Landsat5 and Landsat8 Remote Sensing

  1. Fernández-Pacheco, V. M. 1
  2. López-Sánchez, C. A. 1
  3. Álvarez-Álvarez, E. 1
  4. López, M. J. Suárez 1
  5. García-Expósito, L.
  6. Yudego, E. Antuña
  7. Carús-Candás, J. L.
  1. 1 Universidad de Oviedo
    info

    Universidad de Oviedo

    Oviedo, España

    ROR https://ror.org/006gksa02

Actas:
The 2nd International Research Conference on Sustainable Energy, Engineering, Materials and Environment

Año de publicación: 2018

Tipo: Aportación congreso

DOI: 10.3390/PROCEEDINGS2231430 GOOGLE SCHOLAR lock_openAcceso abierto editor

Resumen

Air pollution is one of the major environmental problems, especially in industrial and highly populated areas. Remote sensing image is a rich source of information with many uses. This paper is focused on estimation of air pollutants using Landsat-5 TM and Landsat-8 OLI satellite images. Particulate Matter with particle size less than 10 microns (PM10) is estimated for the study area of Principado de Asturias (Spain). When a satellite records the radiance of the surface received at sensor, does not represent the true radiance of the surface. A noise caused by Aerosol and Particulate Matters attenuate that radiance. In many applications of remote sensing, that noise called path radiance is removed during pre-processing. Instead, path radiance was used to estimate the PM10 concentration in the air. A relationship between the path radiance and PM10 measurements from ground stations has been established using Random Forest (RF) algorithm and a PM10 map was generated for the study area. The results show that PM10 estimation through satellite image is an efficient technique and it is suitable for local and regional studies.