An Earth System Digital Twin (ESDT) is a dynamic, interactive, digital replica of the state and temporal evolution of Earth systems. It integrates multiple models along with observations, and connecting them with analysis, AI, and visualization tools. Together, these enable users to explore the current state of the Earth system, predict future conditions, and run hypothetical scenarios to understand how the system would evolve under various assumptions.Since 2021, NASA’s Advanced Information Systems Technology (AIST) program has invested in two ESDT efforts to tackle the impacts of our changing climate. The establishment of ESDT for flood and air quality enabled our teams to formalize the software framework. The open-source framework is called the Integrated Digital Earth Analysis System (IDEAS). By working with the Apache Science Data Analytics Platform (SDAP) community, IDEAS is now a subproject of SDAP. The paper presents the ongoing development of IDEAS and its current applications.

An Earth System Digital Twin (ESDT) is a dynamic, interactive, digital replica of the state and temporal evolution of Earth systems. It integrates multiple models along with observation data, and connecting them with analysis, AI, and visualization tools. Together, these enable users to explore the current state of the Earth system, predict future conditions, and run hypothetical scenarios to understand how the system would evolve under various assumptions. The NASA's Advanced Information Systems Technology (AIST)'s Integrated Digital Earth Analysis System (IDEAS) project is to establish an extensible architectural solution to develop digital twins of our physical environment for Earth Science. IDEAS delivers a formal system architecture with mechanisms for the outputs of one model to feed into others; for driving models with observation data; and for harmonizing observation data and model outputs for analysis. To validate and demonstrate the IDEAS architecture, this project collaborates with the Space Climate Observatory (SCO)'s FloodDAM project and the Centre National d'Etudes Spatiales (CNES) to focus on floods detection, prediction and their impacts.

3D Geospatial information plays a key role in many soaring sectors such as sustainable and smart cities, climate monitoring, ecological mobility, and economic intelligence. The availability of huge volumes of satellite, airborne and insitu data now makes this production feasible at large scale. It needs nonetheless a certain level of manual intervention to secure the level of quality, which prevents mass production. This paper presents the AI4GEO program that aims at developing an end to end solution to produce automatically qualified 3D Digital model at scale together with multiple layers of information.

Floods are the most common natural disasters all over the world. The space climate observatory (SCO)-FloodDAM project aims at utilizing the capabilities of new observing strategies in order to better alert, detect and map flood events globally. Leveraging from both aerial- and satellite-based platforms (Sentinel, TerraSar-X, SWOT) as well as in-situ based sensors, the main objective of the project is to develop an automatic system to better prevent flood events and assess their consequences. In this paper, we will demonstrate the strategy deployed for the selected test-sites in France.

Through various initiatives, CNES, the French space agency, has been involved in major disaster and environment monitoring from Space for many years and in particular in the International Charter which delivers satellite data to nations affected by major disasters and in the THEIA organization which promotes the use of satellite data to monitor human and climate impacts on environment.Thus, CNES developed in 2014 a reference framework to generate value-added products from satellite data. Since 2017, considering the increase of data and processing requests, CNES has decided to move to a new framework based on big data and cloud technologies and extended to data analytics.This paper will first introduce THEIA and Charter initiatives. It will present the current framework in operation and its limitations. It will then focus on the innovative approach to handle big data and analytics needs and finally presents the first results and perspectives.

In the context of the Spot World Heritage (SWH) initiative, the long term archive of Spot 1 to 5 satellite data will be reprocessed. This initiative gives the opportunity to increase Spot data quality and production efficiency with the introduction of new state-of-the-art processing methods. In this context, we consider the Spot 5 Supermode processing chain and the introduction of a new denoising method. Our objective is to propose the best denoising method in terms of efficiency and accuracy for the Spot 5 Supermode data production. We report two experimentations that lead to the choice of the Non Local Bayes (NLB) denoising method; it is fast, accurate and remains stable in terms of efficiency and quality for different landscapes and image sizes. We also introduce two optimized versions of the NLB algorithm that increase the computation efficiency by a factor up to 4.

Pleiades-HR is a high resolution remote sensing system developed by the French Space Agency (CNES) for civil and military users. The constellation is composed of two identical satellites PHR1A launched on 2011, December 17th and PHR1B launched one year after, on 2012, December 2nd. More than 600 images can be daily acquired by each satellite in various viewing angles conditions: the satellites are able to target images with viewing angles greater than 47°. Since the launch of the first satellite, major improvements have been integrated in the ground processing to enhance the quality of products and offer new options. Starting from a Pleiades-HR system overview, this paper offers a description of the ground processing and presents an assessment of the different products available now, including image quality performances.

In partnership with the European Commission and in the frame of the Global Monitoring for Environment and Security (GMES) program, the European Space Agency (ESA) is developing the Sentinel-2 optical imaging mission devoted to the operational monitoring of land and coastal areas. The Sentinel-2 mission is based on a satellites constellation deployed in polar sun-synchronous orbit. Sentinel-2 will offer wide improvements such as a unique combination of global coverage with a wide field of view (290km), a high revisit (5 days with two satellites), a high resolution (10m, 20m and 60m) and multi-spectral imagery (13 spectral bands in visible and shortwave infra-red domains). In this context, the Centre National d'Etudes Spatiales (CNES) supports ESA to define the system image products and to prototype the relevant image processing techniques.

The CNES (the French Space Agency) has specified and developed a fully automatic mosaicing processing unit, in order to generate satellite image mosaics under operational conditions. This tool, called SIGMA, can automatically put each input image in a common geometry, homogenize the radiometry, and generate orthomosaics using stitching lines.

Pleiades-HR is the highest resolution civilian earth observing system ever developed in Europe. This optical imaging project is conducted by the French National Space Agency, CNES. It will operate two satellites designed to provide optical images to civilian and military users. The first satellite will be ready for launch by April 2010, the second 18 months later. It will allow, in Nadir acquisition conditions, to deliver image products 20 km wide, false or natural coloured scenes with a 50 cm ground sampling distance. Imaging capabilities have been highly optimized in order to acquire, in the same pass, along-track mosaics, stereo pairs and triplets, and multi-targets. To fulfil the operational requirements and ensure quick access to information, ground processing has to automatically perform the radiometnc and geometric corrections. Since ground processing capabilities have been taken into account very early in the mission development, it has been possible to relax some costly on-board components requirements, in order to achieve a cost effective on-board/ground compromise. Starting from a Pleiades-HR system overview, this paper gives a quick description of the ground segment functional breakdown and focuses more precisely on the image processing and associated products. The geometric accuracy is evaluated and the excellent results obtained are presented. Finally the paper presents the ground segment architecture that will handle this "heavy" processing in the different operational Centres.

Today, new earth observation missions are designed from satellite to ground segment to best fit the end-user needs while reducing the overall costs and complexity. Furthermore, an efficient use of high resolution image data is only possible if its location is accurate enough. The accuracy of the image location model depends on the knowledge of platform and orbital parameters (instruments calibration, satellite orbit and pointing) and also of the ground elevation (Digital Elevation Model). Good accuracy can be ensured by stringent requirements on onboard equipments (GPS, gyro, ...) but also by appropriate ground processing which is easier and less expensive to setup. This paper describes and evaluates an automatic method to improve location models during ground processing. This method has been implemented and tested at CNES for current and new missions (such as SPOT/FORMOSAT image ortho-rectification, Pleiades-HR images mosaicking or Venmus images time-series generation). These results must be considered for future missions designing.

Pleiades-HR is a high-resolution optical Earth observation system developed by CNES, for civilian and military users. The launch of the first Pleiades satellite is scheduled in 2008, the second, 18 months later. The Pleiades-HR program is the French part of the French-Italian ORFEO program which also comprises COSMO-SkyMed, an Italian high-resolution radar system. The Pleiades-HR products will be distributed by Spotlmage and will complete the existing SPOT product line. In such a multi-sensors and multi-users context, CNES has decided to design the new Pleiades-HR ground segment pointing the stress on systems interoperability in order to ease the data access from the end user point of view. After a synthetic presentation of the Pleiades HR ground segment and image products, this paper focuses on PLEIADES HR image product definition and cataloguing services, two major points for the image ground segment interoperability. Among all possible solutions, the image product and catalog services have been defined taking into account the PLEIADES-HR system characteristics, its performance requirements and the international standards (ISO-TC211, OGC, image standards, JPEG2000 ...) use and evolution capabilities. The results presented in the paper are also part of a European initiative of ground segment harmonisation studied in the frame of the HMA project with other European Space Agencies.

Remote sensing optical images are often cloudy and then partially unusable. Thus, cloud detection can optimize the image acquisition loop and the end-user image selection. The current pre-processing of SPOT images includes an automatic cloud and snow detection algorithm based on neural networks and fuzzy logic, which globally provides correct cloud masks but with a perfectible confidence. This process must be improved in order to avoid systematic manual re-notation. For Ple/spl acute/iades high resolution (HR) satellite, CNES experiments an innovative cloud detection method based on correlation and stereoscopic effect (B/H ratio) between images. Thanks to the quasi-simultaneous acquisition of the five spectral bands (panchromatic, red, blue, green and near infrared), this new method can be systematically applied, in addition to a radiometric one. This paper focuses on the new detection algorithm for high resolution images, which includes six main steps: (1) generation of 20 m resolution preview images in both multispectral and panchromatic bands, (2) estimation of the misregistration between panchromatic and multispectral previews using a geometric model, a global DTM and an image matching algorithm, (3) computation of the residual parallax consisting in the difference between prediction model and image matching, (4) cloud detection through high parallax value thresholding (5) radiometric analysis for snow and low altitude clouds detection, (6) masks fusion and confidence status computation. This method, still under assessment over various SPOT5 and Quickbird images, seems to be very promising. The results, presented in the paper, show that the method is efficient even for Quickbird images, in spite of the very low B/H ratio value (0.002) close to Ple/spl acute/iades one.

Following SPOT5 launch, Spotlmage and French National Geographic Institute (IGN) have decided to design a worldwide accurate database called Reference3D/sup TM/ using data from the High Resolution Stereoscopic SPOT5 instrument (HRS). Spotlmage and IGN have also decided to develop and commercialize a system called ANDORRE to produce orthorectifled images thanks to Reference3D/sup TM/ data. ANDORRE has been designed to take advantage of Reference3D/sup TM/ planimetric and altimetric accuracy to automatically register and rectify any image from SPOT satellites. In this framework, CNES is acting as prime contractor to realize and industrialize the algorithms following a preliminary study undertaken by IGN. This paper focuses on the validation of the geometric performances of the algorithms. A special attention is also paid to the processing time in order to achieve the rectification of a 24000/spl times/24000 image in less than one hour.

SPOT5, the fifth satellite of the SPOT remote sensing satellite family was successfully launched on the 4th of May 2002. SPOT5 is designed to ensure continuity of data acquisition and space image services but also to provide users with advanced products. It flies two identical cameras named HRG (High Resolution Geometry) providing a 2.5 m and a 5 m resolution in a panchromatic mode and a 10 m resolution in a multi-spectral mode, still keeping a 60-km ground field. Stereo application complements SPOT5 mission; the satellite flies a specific High Resolution Stereo Instrument (HRS) made up of two telescopes allowing a 20/spl deg/ fore view and a 20/spl deg/ aft view over a 120-km swath, sampling the landscape every 5 m. To be consistent with this new space segment, the image ground segment has been fully redesigned in order to allow worldwide SPOT family reception and products dissemination. The paper presents the mission, the image ground segment architecture and introduces the SPOT products.