Pierre-Philippe Mathieu's research while affiliated with European Space Agency and other places

Publications (39)

Article
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This paper provides a short summary of the outcomes of the workshop on Machine Learning (ML) for Earth System Observation and Prediction (ESOP / ML4ESOP) organised by the European Space Agency (ESA) and the European Centre for Medium-Range Weather Forecasts (ECMWF) between 15 and 18 November 2021. The 4-days workshop had more than 30 speakers and 3...
Article
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Machine learning, satellites or local sensors are key factors for a sustainable and resource-saving optimisation of agriculture and proved its values for the management of agricultural land. Up to now, the main focus was on the enlargement of data which were evaluated by means of supervised learning methods. Nevertheless, the need for labels is als...
Preprint
Full-text available
Machine learning, satellites or local sensors are key factors for a sustainable and resource-saving optimisation of agriculture and proved its values for the management of agricultural land. Up to now, the main focus was on the enlargement of data which were evaluated by means of supervised learning methods. Nevertheless, the need for labels is als...
Article
Full-text available
This paper deals with the analysis and detection of wildfires by using PRISMA imagery. Precursore IperSpettrale della Mis­sione Applicativa (Hyperspectral Precursor of the Application Mission, PRISMA) is a new hyperspectral mission by ASI (Agenzia Spaziale Italiana, Italian Space Agency) launched in 2019. This mission provides hyperspectral images...
Conference Paper
Dengue fever is one of the most common and rapidly spreading arboviral diseases in the world, with major public health and economic consequences in tropical and sub-tropical regions. Countries such as Peru, 17.143 cases of dengue were reported in 2019, where 81.4% of cases concentrated in five of the 25 departments. When predicting infectious disea...
Article
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The Observations for Model Intercomparison Project (Obs4MIPs) was initiated in 2010 to facilitate the use of observations in climate model evaluation and research, with a particular target being the Coupled Model Intercomparison Project (CMIP), a major initiative of the World Climate Research Programme (WCRP). To this end, Obs4MIPs (1) targets obse...
Preprint
Full-text available
Abstract. The Observations for Model Intercomparison Projects (Obs4MIPs) was initiated in 2010 to facilitate the use of observations in climate model evaluation and research, with a particular target being the Coupled Model Intercomparison Project (CMIP), a major initiative of the World Climate Research Programme (WCRP). To this end, Obs4MIPs: 1) t...
Conference Paper
Full-text available
In this work, we present a new architecture for the analysis multitemporal SAR data combining classic synthetic aperture radar processing and geographical object-based image analysis. The architecture exploits the characteristics of the recently introduced RGB products of the Level-1α and Level-1β families, employing self-organizing map clustering...
Conference Paper
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This communication describes the optical processing chain to use Sentinel-3 OLCI and MODIS data as part of the ESA funded Synergy project of the Scientific Exploitation of Sentinel Missions (SEOM) component of the EO Envelope programme. One of the goals of the project is to use Data Assimilation techniques to produce land surface products combining...
Article
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We introduce a new architecture for feature extraction from multitemporal synthetic aperture radar (SAR) data. Its the purpose is to combine classic SAR processing and geographical object-based image analysis to provide a robust unsupervised tool for information extraction from time series images. The architecture takes advantage from the character...
Article
For over a decade, several research groups have been developing air-sea heat flux information over the global ocean, including latent (LHF) and sensible (SHF) heat fluxes over the global ocean. This paper aims to provide new insight into the quality and error characteristics of turbulent heat flux estimates at various spatial and temporal scales (f...
Article
Full-text available
For over a decade, several research groups have been developing air-sea heat flux information over the global ocean, including latent (LHF) and sensible (SHF) heat fluxes over the global ocean. This paper aims to provide new insight into the quality and error characteristics of turbulent heat flux estimates at various spatial and temporal scales (f...
Article
The world of Earth observation (EO) data is rapidly changing, driven by exponential advances in sensor and digital technologies. Recent decades have seen the development of extraordinary new ways of collecting, storing, manipulating, and transmitting data that are radically transforming the way we conduct and organize science. This convergence of t...
Conference Paper
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Earth observation technologies can provide a significant contribution to the monitoring urban areas and critical infrastructures. In this paper, we show how to exploit the recently introduced multitemporal SAR RGB images of the Level-1α and Level-1β family in these applications. Simple, ad hoc algorithms are discussed to adapt these generalist prod...
Article
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In this paper, we present a new framework for the fusion, representation, and analysis of multitemporal synthetic aperture radar (SAR) data. It leads to the definition of a new class of products representing an intermediate level between the classic Level-1 and Level-2 products. The proposed Level-1 β products are particularly oriented toward nonex...
Conference Paper
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The aim of the paper is to introduce the Lazio Pulse initiative as an example of a successful partnership and cooperation among University, Research Centres and Industry. The Lazio Pulse initiative aims to develop a dynamic ecosystem of public and private actors for improving Research and Innovation, based on the value and knowledge generated by cr...
Conference Paper
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In this paper, we present a new framework for the generation of two new classes of RGB products derived from multitemporal SAR data. The aim of our processing chain is to provide products characterized by a high degree of interpretability (thanks to a consistent rendering of the underlying electromagnetic scattering mechanisms) and by the possibili...
Article
Citizens are providing vast amounts of georeferenced data in the form of in situ data collections as well as interpretations and digitization of Earth-observation (EO) data sets. These new data streams have considerable potential for supporting the calibration and validation of current and future products derived from EO. We provide a general intro...
Article
The Jakarta province proposed the Jakarta Giant Sea Wall as the waterfront city for the new urban settlement zone and the deep seaport for the new economic zone along the coastal areas at northern Jakarta. This letter investigated land deformation at 11 watersheds of the West Java Mega Urban Region using the persistent scatterer interferometry tech...
Article
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In this paper, we present a technique for improving the representation of built-up features in modelbased multitemporal SAR RGB composites. The proposed technique exploits the MAP3 framework to generate an a priori information which is used to implement an adaptive selection of the coherence window size. Image texture is used to support the coheren...
Article
Land Surface Temperature (LST) is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all surface-atmosphere interactions and energy fluxes between the surface and the atmosphere. With the advent of the ESA's Sentinel 3 (S3) satellite, accurate LST retrieval methodologies exploi...
Conference Paper
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In this paper, we present an innovative framework for RGB composition of multitemporal SAR data. The proposed products improve users' experience with data enhancing interpretability and allowing for information extraction using simple techniques. The characteristics of the RGB products are illustrated through examples in which their suitability wit...
Article
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The current Earth's energy imbalance (EEI) is mostly caused by human activity, and is driving global warming. The absolute value of EEI represents the most fundamental metric defining the status of global climate change, and will be more useful than using global surface temperature. EEI can best be estimated from changes in ocean heat content, comp...
Conference Paper
In this research, we held study on land deformation at eleven watersheds that influence the sedimentation around Jakarta strait using PSI technique of ALOS PALSAR images. The result shows that land deformation at Jawa Barat province, especially Bandung city area gives significant impact to sedimentation velocity along eastern Jakarta strait, especi...
Chapter
This chapter briefly describes how Earth Observation (EO) from space—in particular from satellite missions of the European Space Agency (ESA)—can support the energy sector by delivering accurate, consistent, and timely information on the state of the environment and natural resources. Some examples are presented of EO demonstration pilot projects p...
Conference Paper
LeanEO! is a 2-year Earth Observation education project funded by the European Space Agency (ESA) and developed by different European Institutions. Its main aim is to increase the understanding and knowledge of satellite data obtained from ESA missions and demonstrate how these can be used when faced with environmental problems in the real world. T...
Article
For society to benefit fully from its investment in Earth observation, EO data must be accessible and familiar to a global community of users who have the skills, knowledge and understanding to use the observations appropriately in their work. Achieving this requires considerable education effort. LearnEO! (www.learn-eo.org) is a new ESA education...
Article
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The growing body of knowledge and experience in weather and climate risk management in the energy industry has driven a rapidly growing research interest in establishing links between weather, climate, and energy. Weather and climate information is also critical to managing the energy supply from other energy sectors along with better understanding...
Conference Paper
Full-text available
ESA's strong involvement in Education, Training and Capacity Building for Remote Sensing from Space, includes a plethora of activities, ranging from training courses, workshops and other events addressed to schools, universities and professionals, to special publications (e.g. atlases and teacher's packs), on-line material and educational software...
Article
Data assimilation – the set of techniques whereby information from observing systems and models is combined optimally – is rapidly becoming prominent in endeavours to exploit Earth Observation for Earth sciences, including climate prediction. This paper explains the broad principles of data assimilation, outlining different approaches (optimal inte...
Article
In this review paper, state-of-the-art observational and numerical modeling methods for small scale turbulence and mixing with applications to coastal oceans are presented in one context. Unresolved dynamics and remaining problems of field observations and numerical simulations are reviewed on the basis of the approach that modern process-oriented...
Article
Established in 2000, ESA's Earth Observation Market Development (EOMD) activity is designed to foster the use of Earth Observation (EO) based geo-information services within various market sectors. Working in close cooperation with European and Canadian EO service companies, EOMD supports these firms in growing business by attracting new clients an...
Article
Renewable Energy has limitless resources, but harnessing its full potential requires careful planning. Earth Observation from space can assist with this process by quantifying available energy resources in a timely and accurate manner, and by providing relevant geophysical parameters for modelling. This short article describes the benefits and use...

Citations

... As a result, models have been evaluated in different settings and under different conditions [28] -hardly reproducible and comparable. These persistent challenges, akin to a lack of standardized and consistent validation and evaluation of novel approaches, have also been identified by the community [29]. Citing the lack of available documentation on the design and evaluation of the employed machine learning approaches, the community highlights the urgent need for standardized benchmarks, that will not only enable proper and fair modelcomparison across datasets and similar tasks, but will also facilitate faster progress in designing better and more accurate modeling approaches. ...
... This approach was influenced by complex factors such as housing density, drug sales, and employment levels. Furthermore, Schneider et al. (2021) proposed a machine learning method for predicting dengue fever based on climatic factors in addition to geographical data, which enhanced the infectious disease transmission model and made it more realistic. ...
... Machine Learning (ML) models can be used in many areas in the workflow of weather forecasting such as observations, data assimilation, numerical weather forecasting, and post-processing and dissemination [12,13]. Machine Learning has the potential to address the challenges of complexity and volume when dealing with meteorological data while using less computing power. ...
... When the remote sensing data products are used in a wide range of downstream analyses, these quality flags are usually treated in a dichotomous way: Data flagged as unreliable are removed, while the remaining data, no matter how they may be flagged differently (e.g., good or acceptable), are combined directly (e.g., Zhu et al., 2015;Ma and Kang, 2020b;Tian et al., 2020;Waliser et al., 2020). This practice ignores the delicate quality difference between observations with different quality flags. ...
... Standardization of model output in a common format (Juckes et al., 2020) and publication of the CMIP model output on the Earth System Grid Federation (ESGF) facilitates multi-model evaluation and analysis (Balaji et al., 2018;Eyring et al., 2016a;Taylor et al., 2012). This effort is additionally supported by observations for the Model Intercomparison Project (obs4MIPs) which provides the community with access to CMIP-like datasets (in terms of variable definitions, temporal and spatial coordinates, time frequencies, and coverages) of satellite data (Ferraro et al., 2015;Teixeira et al., 2014;Waliser et al., 2019). The availability of observations and models in the same format strongly facilitates model evaluation and analysis. ...
... Increasingly, methodological approaches from image classification are used. First, object-based approaches for geometric feature detection and semantic cluster detection with segmentation [33,34]. Often, AI networks are used for feature-based approaches using statistical methods such as fuzzy logic. ...
... Sea Surface Temperature is a vital variable used for many climatology and ecology applications. Being at the oceanatmosphere boundary, SST is essential for interchange of heat, moisture, momentum, and gases between the ocean and atmosphere [101,102]. Measurement results indicate that SST in all the oceans has been rising in the last 5 decades, which is similar to the near-surface air temperature. The regional inconsistency of SST is connected with that of other climate variables, like rainfall. ...
... In November 2017, the Copernicus Climate Change Service promoted the International Conference on Reanalysis (Buizza et al, 2018) to bring together reanalysis producers and observation providers. The conference gave the opportunity to the user community to assess the status of available products and discuss future developments. ...
... Moreover, in the last seven years, the InSAR community was primarily focused on adapting the available MT-InSAR codes to process large sequences of SAR data collected by the new constellations of SAR satellites. In particular, a significant role was played by the Sentinel-1A/B (S-1) twin satellites of the European Union Copernicus initiative [48]. The free and open access policy of the S-1 data and the weekly repetition frequency of the observations contributed to InSAR technology's evolution to afford the challenges of the present-day, big-data era. ...
... They can search all locations in an image rather than a specific latitude band, and they can be applied to different data sets and locations without modification; moreover, the MRA makes it unnecessary to define a feature using preset quantitative criteria. Levy [46], Geiss et al. [47], and Levy et al. [48] applied those methods to 30-year record of daily TOA observations and other satellite ancillary data, including different satellite data analyzed by Kumar et al. [49] and latent and sensible heat flux over the global oceans retrieved from remote sensors and evaluated by Bentamy et al. [50], showing some skills in predicting breaks in the monsoon associated with intra-seasonal drought conditions, as defined by a monsoon break index developed from precipitation data by Kumar and Dessai [51]. ...