Estimation of PM10 Distribution using Landsat5 and Landsat8 Remote Sensing

Proceedings

López, M. J. Suárez¹  López-Sánchez, C. A.²  Fernández-Pacheco, V. M.³  García-Expósito, L.⁴  Álvarez-Álvarez, E.⁵ 

[1] Author to whom correspondence should be addressed.;Biology of Organisms and Systems Department, University of Oviedo, 33600 Oviedo, Spain;Energy Department, University of Oviedo, 33600 Oviedo, Spain;Presented at the 2nd International Research Conference on Sustainable Energy, Engineering, Materials and Environment (IRCSEEME), Mieres, Spain, 25–27 July 2018;TSK Company, Gijón 33203, Spain

关键词: L;    sat;    PM10;    remote sensing;    air quality;    atmospheric pollution;   

DOI  :  10.3390/proceedings2231430

学科分类：社会科学、人文和艺术（综合）

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY