Our Company

MEEO, born in 2004 with the aim to develop and commercialize products and services within the Earth Observation, is a privately-held company devoted to the development and implementation of products and services based on remote sensing of the Earth-Atmosphere system. 
MEEO is able to provide a wide range of services and products “ready” (off the shelf) based on analysis of multispectral, multisensor and multitemporal satellite data for environmental monitoring, land management and agriculture .
MEEO also aims to develop dedicated services for different applications in remote sensing, in the propagation of electromagnetic waves, data mining and data fusion.
MEEO is an ESA value added partner, working on more than 20 ESA projects and several National and European projects.
SISTEMA GmbH is a privately-held company founded in 2009 as R & D branch of MEEO and it is focused on development of new data processing tools. It works mainly on ESA project and on Austrian National projects.

What's new?

The eodataservice technology is getting more and more used in various domains to provide fast and reliable access to a large volume and variety of geospatial data, mainly from satellite platforms. In a joint effort to bring Earth Observation (EO) services to a new level, e-GEOS and MEEO has started a partnership to exploit at the …
It has been a busy week at EGU 2018 in Vienna, Austria. Our booth has been visited from Monday to Friday by many very interested scientists, decision makers, private users, teachers and students. Our real datacubes have made the difference: thousands of stickers distributed and many "hands on" real data sessions performed. Thanks to all those (more …

OUR PROJECTS

The native attitude for science, innovation and advance technologies of the company combined with technical expertise and scientific background of the team are well represented by the following projects list:

Our partners

Products and services

The specific skill on Earth Observation and the experience gained in 10 years of academic and private activities determine and mark the innovative services and products offered.

Initially focused on the development of meteorological and climatological applications, MEEO currently provide specific Earth Observation products and services: SOIL MAPPER®, original spectral classification system for automatic detection of soil categories, PM MAPPER®, innovative particulate matter monitoring system, and SOMAFID a new system for active fire detection.

In order to sustain the internal growing process to improve the quality of its products and services MEEO adopts tools for internal process management and web access to services and products through internet.

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ADAM (Advanced geospatial Data Management platform) implements the Digital Earth concept: ADAM allows accessing to large variety of multi-year global environmental data (e.g. temperature, precipitation, vegetation status, …) enabling visualization, combination, processing and download
>> Start your ADAM experience <<

MEA-PM is an evolution of MEA system, developed for the PM10 and PM2.5 pollution monitoring.
MEA technology made possible the implementation of another innovative system, MEA-PM (MEA for Particulate Matter), for air quality monitoring measuring PM10 and PM2.5 in the atmosphere by using satellite data and ground data.
The system provides maps with PM concentration value with a spatial resolution of 1 square kilometer on Europe, but focused on Emilia Romagna Region, so far, with ground data.
PM is an automated, centralized system that collects and manages the following data:

  • PM ground data measurements since 2000;
  • Satellite PM measurements since 2007;
  • Integrated maps with satellite and ground data fusion (by using numerical Modeling maps);

MEA-PM is the result of the SENSORER project, that was created in 2008, as MEEO company answer to a public tender of Emilia Romagna region, supported by regional development european funds.
SENSORER is a collaborative research project involving, together with MEEO, high level scientific partners like Telecommunication Engineering department of UNIFE and the regional laboratory for infomobility named LASIM.
Then MEA-PM system is compliant with an European air quality directives as possible integration monitoring technique together with ground pollution measurements system.
MEA-PM has been developed by using other than MEA, PM MAPPER® technology and the and Regional broadband Lepida Network.
MEA-PM is innovative for air quality monitoring, and suitable to be used as analysis tool or decision support system for the evaluation of environmental pollution conditions.
On youtube the video done by MEEO with an overview of MEA-PM prototype developed during SENSORER project.
If you want to access MEA-PM release 1.0 interface:
http://mea-pm.services.meeo.it/ or, from Lepida Network: http://meeo.cner-supplier.it/spa-alcs/evat
Select “MEA-PM access request” to request for credentials or send an email to info@meeo.it.

Multi-sensor Evolution Analysis (MEA) an Earth Observation and geospatial data analysis tool empowered with OGC standard interfaces. MEA started as an innovative web application to identify land cover change and it is based on satellite images with global coverage. Dynamic phenomena may have relevant effects on environment and therefore on mankind and can leave traces on land cover and climate changes detectable from earth observation data. In order to boost automation in the identification of features with dynamic behaviour, MEEO has implemented a prototype of a multi-temporal analysis solution, called MEA. Its aim is to permit the definition and use of Evolution Models, which describe how to detect a specific feature from related land cover changes over time. In order to reach this objective, it is necessary to create a common classification system and an Earth Fixed Geo-spatial reference, also applicable across different missions. MEA was studied to help the user to:
  • Define time Evolution Models of features
  • Apply Evolution Models across 13 years of (A)ATSR data
  • Obtain in a few seconds the results of related spatio-temporal and semantic queries.
MEA has been implemented within the Image Information Mining projects of European Space Agency. An instance of the MEA application can be reached at this address: http://eodataservice.org/.
The content of fine and ultra-fine particulate matter in the air is becoming more and more important as a field of study in the health sciences. PM MAPPER® allows monitoring fine particulate matter as PM2.5 from space. Using specific satellite-borne sensors, daily Earth coverage is possible with spatial resolution of 1km x 1 km. The computational process involves three main phases:
  • Multispectral satellite data loading, cloud masking and soil coverage parameters computation;
  • Particulate Matter calculation and map generation;
  • Particulate Matter map classification and health risk map generation; during this phase the US EPA 2006 health quality criteria are used to simply and effectively identify the impact of air quality on different categories of people (Air Quality Index – AQI concept).
The latest MEEO technology, Multi-sensor Evolution Analisys (MEA), allowed the development of a new air quality platform, called MEA-PM, to automatically monitor particulate matter concentration over several years by using satellite and ground data.
soil mapper® is a fully automatic software that permits to generate land cover classification maps through the analysis of multispectral satellite data in the optical domain. As input it requires multispectral remotely sensed (RS) images calibrated on Top of Atmosphere (TOA) physical values: TOA Reflectance values for Visible (VIS), Near Infrared (NIR), Short Wave Infrared (SWIR), Mid-Wave Infrared (MIR) bands and brightness temperature (BT) for Thermal Infrared (TIR) bands. As output, it generates a preliminary classification map where each pixel is associated with one label belonging to a discrete set of spectral categories. In the last version soil mapper® has been extended on its satellite sensors applicability and has been improved in the system performance through the implementation of spectral classification system and the upgrading of cloud detection technique. Another focal soil mapper® improvement is the classification outputs standardization among the different supported satellite sensors, allowing the land classification comparison between different satellite sensors images. To run, soil mapper® requires neither user supervision nor ground truth data sample, i.e., it is fully automatic (unsupervised). Spectral classes detected by soil mapper® have a semantic meaning belonging to the following categories:
  • Vegetation,
  • Bare soil / Built-up,
  • Snow / Ice,
  • Clouds,
  • Water / Shadows,
  • Outliers.
soil mapper® output can be directly used as soil classification map, or can be considered as Baseline Map for further analyses within following fields:
  • specific analyses focused on defined stratus or group of strata
  • advanced semantic-geographic based query
  • multitemporal applications
  • other soil analysis applications
In general, a classification map is suitable for driving further second-stage (e.g., supervised, hierarchical) image analysis algorithms (e.g., segmentation, classification, clustering, topographic correction, etc.) on a stratified image basis. soil mapper®has been improved to support most common satellite optical sensors (from medium to high and very high resolution), like: MODIS, AVHRR, AATSR, MERIS, Landsat 5 TM/7 ETM+, ASTER, SPOT-4 HRVIR, SPOT-5 HRG, IRS 1-C/-D, IRS-P6, IKONOS, ALOS/AVNIR-2, QuickBird, WorldView-2. Further ingestion modules related to existing and future missions (e.g. MSG/SEVIRI, CBERS, RapidEye, Pleiades, GeoEye-1) or specific sensors (i.e. airborne multispectral sensors like AVIRIS) can be implemented. In its current version,soil mapper®, automatically generates three output classification maps of three different classification level sets (each classification set has the same classes number for all the supported satellite sensors):
  • “Complete classification set”, identifying the largest possible set of output spectral categories, consisting of 56 land cover classes
  • “Intermediate classification set”, identifying a reduced set of spectral categories, consisting of 26 land cover classes
  • “Corine land Cover – Like classification set”, identifying a minimal set of spectral categories, consisting of a semantic classification with 12 classes in accordance with the classification system
Besides the three-level classification maps, the last version of soil mapper®generates a series of masks and spectral indexes (Value Added Products) to enrich the software package output and to provide continuous spectral indexes potentially useful for further application-dependent image analysis, like:
  • Vegetation index
  • Normalized difference vegetation index
  • Normalized difference snow index
  • Cloud mask
  • Water mask
  • Vegetation mask
Moreover a series of masked indexes (a combination of the indexes and masks: VI*MVEGETATION, NDVI*MVEGETATION, NDSI*MWATER), can also be generated. soil mapper® takes inspiration from a paper recently published in RS literature (Baraldi, et al., 2006 “Automatic Spectral Rule-Based Preliminary Mapping of Calibrated Landsat TM and ETM+ Images”, IEEE TGRS, 44 (9) 2563-2586).
SOMAFID (SOIL MAPPER Fire Detection) is the new system developed by MEEO to detect active fires in a MODIS and MSG-2 SEVIRI scene.
The SOMAFID algorithm improves the MODIS Fire Detection (MOFID) algorithm, developed by the MODIS Science Team as a Level 2 product (MOD14).
The following improvements have been introduced:
  1. Reduction of the number of false alarms due to clouds and water bodies by means of SOIL MAPPER classification-based masking.
  2. Definition of 3 different background conditions of active fires:
    • High biomass vegetation (for example, forests)
    • Low biomass vegetation (for example, low humidity biomass like tree bark)
    • No-vegetation (for example, bare soil and buildings)
  3. Fire pixel recognition of 3 distinct fire stages, characterized by different fire intensity, temperature, combustion efficiency and emission ratios:
    • flaming fire
    • smoldering fire
    • mixed stage

    The SOMAFID system identifies active fires and generates nine different output classes, three for each background type.

Weather

It all has begun with the weather. Weather monitoring from space and from local weather stations has always been the fil rouge of the history and the present of MEEO. Hence this section “weather” is a little tribute to the scientific background of MEEO founders, showing a daily image of the weather channel from NOAA satellite platform and a chart with the meteorological parameters measured by a weather station located in neighborhood of Ferrara, at the ” Prati Vecchi di Aguscello” airport ( ICAO CODE: LIDV).

How to get to MEEO

Meteorological and Environmental Earth Observation – MEEO S.r.l.
Viale Volano 195/A Int.2
I-44123, Ferrara (FE), ITALY

Phone: +39 0532 1861501
Fax: +39 0532 1861637
e-mail: info@meeo.it

For detailed information, please contact our personnel directly at:

Technical Manager:  technical@meeo.it
Research and Development:  resdev@meeo.it
Sales Manager:  sales@meeo.it

Job Opportunities

MEEO has had much success in the integration of innovative applications for environmental Earth Observation. If you think that your skills and your experience could be useful to our company, and if you think that MEEO could give you a professional qualifying opportunity, send us your CV.

Business ethic

MEEO pursues sustainable policies and environmental protection, thanks to its research, the use of which involves a low environmental impact.
MEEO operates in compliance with applicable laws, professional ethics and regulations.
The pursuit of the interests of the Company can not justify a contrary conduct to the principles of lawfulness, fairness and honesty.
Relationships with stakeholders of the Company are based on criteria and behaviors of honesty, cooperation, loyalty and mutual respect.
MEEO ensures adopting procedures to ensure the confidentiality of information in its possession, the observance of legislation on personal data and shall refrain from seeking confidential data through illegal means.
MEEO undertakes to avoid discrimination based on age, sex, sexual preference, health status, race, nationality, political opinions or religious beliefs, in all decisions that affect the relationships with its customers.

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