In the context of Long Term Data Preservation, ESA, with the support of the Instrument Data Evaluation and Quality Analysis Service (IDEAS+) team, reprocessed over 600’000 Landsat 1-5 Multi-Spectral Scanner (MSS) products acquired in the period 1975 - 2001 from the European Ground Stations complementing the existing 1 million Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) Level 1 products, with a geographical coverage from Greenland to Continental Europe and North Africa. The reprocessing software and quality control tool developed for the reprocessing present new features aimed at improving the radiometric and geometric accuracy, image data recovery and including additional quality assurance information. An accurate geometric and radiometric accuracy evaluation across the over 40-years long operative life of Landsat is vital for the exploitation of long time series analysis and for the future development of multi-mission Analysis Ready Data (ARD). This paper proposes to evaluate the geometric accuracy and the radiometric calibration accuracy of the Landsat Level 1 products delivered by ESA. It is obvious that across Landsat historical mission the accuracy is not the same; data are acquired with the MSS, the TM and the ETM+ sensors with improved characteristics for the most recent ones. All these differences between remote sensing systems, did not preclude to engineer processing algorithms with one main objective to harmonize physical measurement and ensure interoperability with the ongoing missions such as Landsat 8 - OLI / Sentinel 2 – MSI. This approach is a key aspect for the future development of multi mission ARD. The geometric quality assurance parameters are exposed in the Level 1 products. These scene based parameters allows to filter out and select, for a given region, if needed the most accurate products. Also, to demonstrate that these parameters are consistent is fundamental. Because of the ageing of missions, specifically for MSS missions, the processing cannot solely rely on information coming from telemetry. It is mandatory to apply ground model and to estimate both external and internal orientation parameters for what concerned the geometric model. Furthermore, for some parameters, the use of single scene for calibration of geo referencing model is not sufficient and the estimate of parameters becomes more robust when considering, instead of one scene, all data recorded in the acquisition period and downlinked to the receiving station. Also, the proposed methodology herein validates the stability of geometric accuracy for a long period of time within the orbit. The product quality assurance parameters are compared with the same ones but inferred from an image matching methods comparing disparity between two geometric grids; the input ESA image and geometric reference image (Global Land Survey data). A comparison with relative USGS products is also performed.
KEYWORDS: Data archive systems, Image processing, Sensors, Image quality, Modulation transfer functions, Data acquisition, Clouds, Data modeling, Deconvolution
The Advanced Land Observing Satellite (ALOS) was launched on January 24, 2006, by a Japan Aerospace Exploration Agency (JAXA) H-IIA launcher. It carries three remote sensing sensors: the Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2), the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM), and the Phased Array type L-band Synthetic Aperture Radar (PALSAR).
Within the framework of ALOS Data European Node (ADEN), as part of the European Space Agency (ESA), has collected 5 years of data observed in Arctic, in Europe and in Africa through the ground stations of Tromsoe (Norway) and Matera (Italy).
Some data has been repatriated directly from JAXA from the on-board recorder (in particular over Africa, outside the visibility of the stations). The data were available to the scientific users via on-request ordering from the stations through the ESA ordering system. In ordering to provide a better and easier access to the data in the framework of the ESA Third Party Missions, in 2015 ESA started a project aimed to repatriate the data from the stations, consolidate them, harmonise the format to the ESA standards.
For the PALSAR data, view the different processing levels available to the users, ESA decided to setup a dissemination system, able to process automatically at the user demand the data to the requested level (on-the-fly processing). For the optical data, instead, the decision was to systematically process the PRISM and AVNIR-2 as orthorectified products (so to a higher level in respect of what available before) with a systematic quality control.
This paper presents the functionalities of the new Level 1 orthorectified products and details the block adjustment algorithms used for refinement of geometric accuracy. A specific quality control strategy has been laid down in order to re-analyse the entire archive. Also, validation methods are explained and the final product accuracy specification are given.
Whilst recent years have witnessed the development and exploitation of operational Earth Observation (EO) satellite constellation data, the valorisation of historical archives has been a challenge. The European Space Agency (ESA) Landsat Multi Spectral Scanner (MSS) products cover Greenland, Iceland, Continental Europe and North Africa represent an archive of over 600,000 processed Level 1 (L1) scenes that will accompany around 1 million ESA Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) products already available. ESA began acquiring MSS data in 1975 and it is well known that this dataset can be degraded due to missing data and a loss in accuracy. For these reasons, the content of the product format has been reviewed and the ESA Landsat processing baseline significantly updated to ensure products are fit for user purposes. This paper presents the new MSS product format including the updated metadata parameters for error traceability, and the specification of the Quality Assurance Band (BQA) engineered to allow the best pixel selection and also the application of image restoration techniques. This paper also discusses major improvements applied to the radiometric and geometric processing. For the benefits of the community, ESA is now able to maximize the number of L1 MSS products that can potentially be generated from the raw Level 0 (L0) data and ensure the highest possible data quality is reached. Also, by improving product format, processing and adding a pixel based quality band, the MSS archive becomes interoperable with recently reprocessed Landsat data and that from live missions by way of assuring product quality on a pixel basis.
Landsat is a joint USGS and NASA space program for Earth Observation (EO), which represents the world’s longest running system of satellites for moderate-resolution. The European Space Agency (ESA) has acquired Landsat data over Europe, Northern Africa and the Middle East during the last 40 years.
A new ESA Landsat Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) processor has been developed. This enhanced processor aligns historical Landsat products to the highest quality standards that can be achieved with the current knowledge of the instruments. The updated processor is mainly based on the USGS algorithm; however it has some different features that are detailed in this paper.
Current achievements include the processing and availability of approximately 860,000 new TM/ETM+ high-quality products between 1983 and 2011 from the Kiruna (S), Maspalomas (E) and Matera (I) archives; Matera includes data from the Fucino (I), Neustrelitz (D), O’Higgins (Antarctica), Malindi (Kenya), Libreville (Gabon) and Bishkek (Kyrgyzstan) ground stations.
The products are freely available for immediate download to the users through a very fast and simple dissemination service (at: https://landsat-ds.eo.esa.int/app/) and through ESA’s browsing system, EOLI. The remaining MSS data, dating back more than 40 years, will gradually become available during 2015 and 2016.
The ESA Landsat processor algorithm enhancement, together with the results of the ESA archive bulk-processing data regarding production, quality control and data validation are herein presented.
F. Gascon, R. Biasutti, R. Ferrara, P. Fischer, L. Galli, B. Hoersch, S. Hopkins, J. Jackson, S. Lavender, S. Mica, A. Northrop, A. Paciucci, F. Paul, S. Pinori, S. Saunier
The Landsat program is a joint United States Geological Survey (USGS) and National Aeronautics and Space Administration (NASA) enterprise for Earth Observation (EO), that represents the world’s longest running system of satellites for moderate-resolution optical remote sensing. The European Space Agency (ESA) has acquired Landsat data over Europe through the ESA ground stations over the last 40 years, in co-operation with USGS and NASA. A new ESA Landsat Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) processor has been developed. This enhanced processor aligns the historical Landsat products to the highest quality standards that can be achieved with the current knowledge of the instruments. The updated processor is mainly based on the USGS algorithm; however the ESA processor has some different features that are detailed in this paper. Using this upgraded processor, ESA is currently performing for the first time a bulk-processing of its entire Landsat series MSS/TM/ETM+ historical archive to make all products available to users. Current achievements include the processing and online distribution of approximately 290 000 new Landsat 5 TM high-quality products acquired at the Kiruna ground station between 1983 and 2011. The Landsat 5 TM bulk-processed products are made available for direct download after registration at: https://earth.esa.int/web/guest/pi-community/apply for-data/fast-registration. The remainder of the ESA’s Landsat data, dating back more than 40 years, will gradually become available for all users during the course of 2014. The ESA Landsat processor algorithm enhancement, together with the results of the ESA archive bulk-processing, and an overview on the data quality on a subset of the Landsat 5 TM data are herein presented.
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