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8/12/2019 GeoHR Poster Mantovani

http://slidepdf.com/reader/full/geohr-poster-mantovani 1/1

Second Level Processing Tools for Environmental Parameters Monitoring

for HR Geostationary SensorsSimone MANTOVANI1,2, Maurizio BOTTONI2, and Stefano NATALI1,2

1 Meteorological and Environmental Earth Observation, MEEO S.r.l., Via Saragat 9, I-44122 Ferrara, Italy2 SISTEMA GmbH, Währingerstraße 61, A-1090 Vienna, Austria

PM MAPPER (MEEO S.r.l., 2009) is an air quality monitoring system elaborating data

collected from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The

system retrieves Aerosol Optical Thickness (AOT) map, Particulate Matter PM2.5 and

PM10 maps and Air Quality Index (AQI) map.

Visible (VIS) to Near Infra Red (NIR) spectral bands are mandatory to extend the

applicability of the system to other satellite sensors; Thermal Infra Red (TIR) spectral

bands are necessary to increase the accuracy of the cloud screening procedures.

PM MAPPER fine spatial resolution product (see Figure 2 with respect to Figure 1) and

integrated surface information have been recently presented at the Hyperspectral

Workshop (Nguyen et al., 2010).

The feasibility study to retrieve AOT maps up to 1x1km2 spatial resolution is showing

promising results (see Figure 3).

Introduction

• MEEO S.r.l., 2009. PM MAPPER System Description, Issue 1.1. Internal Report, unpublished.

• Nguyen T.N.T., Bottoni M., Mantovani S., 2010. PM MAPPER: An Air Quality Monitoring System with Fine Spatial Resolution Product and Integrated Surface Information,

Hyperspectral Workshop 2010, ESA ESRIN, Frascati (Rome), Italy, March 17-19, 2010.

References

Portability to HR GEO algorithms

Final products to be transferred from MR-LEO system to HR-GEO system consist of:

OPERATIONAL APPLICATIONS, based on methodologies already established for MR-LEO systems:

1. Map distribution of AOT, PM and AQI. Frequency of data collection would

enable identification of contaminant sources in urban or industrialised areas.

2. Detection of sources of dust or sand from desert or sub-desert areas,

their tropospheric transport and deposition upon mid-latitude regions.

EXPERIMENTAL APPLICATIONS, based on methodologies to be envisaged

but not immediately achievable on the basis of past experience.

It includes (see for reference: Hyperspectral Workshop 2010,

ESA ESRIN, Frascati (Rome), Italy, March 17-19, 2010.):

• Construct maps of vegetation areas at risk of fire by detecting EWT

(Equivalent Water Thickness). Detect inception of natural or man-made fires

and spreading of burning areas. Map vegetation recover after fires.

• Detect pollution of inland waters due to phytoplankton algae, by measuring

water surface reflectance. Use visible and infrared spectrometers in the

spectral range 400 - 900 nm with ground resolution of a few dozen meters.

• In benthonic habitats detect pollution of costal waters by suspended inorganic

or organic particles and by phytoplankton species (cyanobacterial algae).

Monitor bottom reflectance corrected for depth of water and influence of atmosphere.

MODIS HR GEO

Band [µm] Resolution [m] Band Resolution [m]

0.646 250 10 -100

0.855 250 10 - 100

0.466 500 10 - 100

0.553 500 10 - 100

1.243 500 10 - 100

1.632 500

2.119 500

MWIR 1000

TIR 1000

Characheristic MODIS HR GEO

Temporal frequency 1 img / day Every 5 min to 1 hour  

Processing time < 10 minutes / img

Input file HDF

Input size 500MB

Figure 2. General view and detailed Italy areas

monitored at 3x3km2 resolution.

Figure 1. General and detailed view of Italy

areas monitored at 10x10 km2 resolution.

Table 1. Wavelength bands used in the elaboration of

MODIS data and directly applicable or of uncertain

application (marked with ?) in the frame of a GEO system.

Table 2. PM MAPPER characteristics and performances.

 Applications of Low Resolution (LR) data from Geostationary (GEO) and of High-to-Very

High Resolution (HR-VHR) optical data from Low Earth Orbit (LEO) satellites have been

thus far almost completely disjointed. GEO satellites were used mainly for regional-to-

global scale meteorological analysis (4D data retrieval), and early warning systems. HR-

VHR LEO data were used to monitor land surface characteristics.

Besides, GEO data are processed by software at high level of automation while HR-VHR

LEO data are seldom processed automatically but require in most cases dedicated

software packages and human interaction.

 Application of existing HR-VHR software to GEO processing systems may be difficult,

whilst could be more profitable to analyze the portability of Mid-Resolution (MR) LEO

applications with larger degree of automation, moving from multi-temporal applications

(few images per week or month) to hyper-temporal applications (many images per day)

also increasing the spatial scale of the output.

PM MAPPER portability

Figure 3. Detailed view and zoom areas monitored

at 1x1km2 resolution.

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