Authors:
Thi Nhat Thanh Nguyen
1
;
Simone Mantovani
2
;
Piero Campalani
1
and
Gian Piero Limone
1
Affiliations:
1
University of Ferrara, Italy
;
2
MEEO S.r.l. and SISTEMA GmbH, Italy
Keyword(s):
Aerosol optical thickness, Downscaling, 1 km2 spatial resolution, Support vector regression, MODIS, Local monitoring, Air pollution, Remote sensing.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Geometry and Modeling
;
Image Understanding
;
Image-Based Modeling
;
Pattern Recognition
;
Sensors and Early Vision
;
Software Engineering
Abstract:
Processing of data recorded by MODIS sensors on board the polar orbiting satellite Terra and Aqua usually
provides Aerosol Optical Thickness maps at a coarse spatial resolution. It is appropriate for applications of
air pollution monitoring at the global scale but not adequate enough for monitoring at local scales. Different
from the traditional approach based on physical algorithms to downscale the spatial resolution, in this article,
we propose a methodology to derive AOT maps over land at 1 km2 of spatial resolution from MODIS data
using support vector regression relied on domain knowledge. Experiments carried out on data recorded in
three years over Europe areas show promising results on limited areas located around ground measurement
sites where data are collected to make empirical data models as well as on large areas over satellite maps.