ABSTRACT:Earth observation is entering a new era where the increasing availability of free and open global satellite data sets combined with the computing power offered by modern information technologies opens up the possibility to process high-resolution data sets at global scale and short repeat intervals in a fully automatic fashion. This will not only boost the availability of higher level earth observation data in purely quantitative terms, but can also be expected to trigger a step change in the quality and usability of earth observation data. However, the technical, scientific, and organisational challenges that need to be overcome to arrive at this point are significant. First of all, Petabyte-scale data centres are needed for storing and processing complete satellite data records. Second, innovative processing chains that allow fully automatic processing of the satellite data from the raw sensor records to higher-level geophysical products need to be developed. Last but not least, new models of cooperation between public and private actors need to be found in order to live up to the first two challenges. This paper offers a discussion of how the Earth Observation Data Centre for Water Resources Monitoring (EODC) -a catalyser for an open and international cooperation of public and private organisations -will address these three grand challenges with the aim to foster the use of earth observation for monitoring of global water resources.
<p>To this day, in situ soil moisture data is viewed as ground truth by the satellite soil moisture (SSM) community. In general, little is still commonly known regarding the traceability of ground measurement uncertainty and their overall in uncertainty budget, which can impact satellite SSM product quality assessments.</p> <p>Within ESA&#8217;s &#8220;Fiducial Reference Measurement for Soil Moisture (FRM4SM, May 2021 - May 2023)&#8221; project, objectives are set towards building fully characterized and traceable (i.e., fiducial) in situ measurements following community-agreed guidelines from the GEOS/CEOS Quality Assurance for Soil Moisture (QA4EO) framework. These so called &#8220;fiducial reference data&#8221; (FRM) should have associated Quality Indicators (QI) attached to evaluate their fitness for purpose building upon agreed reference standards (SI if possible). Moreover, such data should be easily and openly accessible, validation case studies should demonstrate their utility and reliability, and protocols and procedures should be established for the usage of such FRM datasets to make scientific studies intercomparable and reproducible.</p> <p>As part of the FRM4SM project, the following questions were addressed using the International Soil Moisture Network (ISMN) as a ground reference database and the Soil Moisture and Ocean Salinity (SMOS) mission as an example satellite product:</p> <p>(1) What makes &#8220;fiducial reference data&#8221; fiducial?</p> <p>(2) Is the creation of a globally-representative FRM subset already feasible for SSM?</p> <p>(3) What are the current limitations of in situ observations that limit fiduciality?</p> <p>(4) What is needed to create a full traceability chain from in situ point measurements to the satellite footprint scale?</p> <p>In this presentation, we will discuss these questions in detail and report on related findings of the FRM4SM project.</p>
<p>The Quality Assurance for Soil Moisture (QA4SM) service is an online validation tool to evaluate and intercompare the performance of state-of-the-art open-access satellite soil moisture data records (https://qa4sm.eodc.eu). QA4SM implements routines to preprocess, intercompare, store and visualise validation results based on community best practices and requirements set by the Global Climate Observing System and the Committee on Earth Observation Satellite. The focus on traceability in terms of input data, software and validation results improves reproducibility and sets the basis for a community wide standard for future validation studies.</p><p>Within the validation framework a number of up-to-date soil moisture datasets are provided. Satellite data include multi-sensor records such as the European Space Agency&#8217;s Climate Change Initiative (ESA CCI) and the Copernicus Climate Changes Services (C3S) Soil Moisture datasets and single sensor products e.g. from SMAP, SMOS or Metop ASCAT. Reference data within the service include the full in-situ data archive of the the International Soil Moisture Network (ISMN; https://ismn.geo.tuwien.ac.at/) and land surface model/reanalysis products, e.g. from the European Centre for Medium-Range Weather Forecasts (ECMWF). General validation metrics between dataset pairs (such as correlation or RMSD amongst others) and triples (Triple Collocation) are part of the service. QA4SM allows users to select from a number of input parameters to specify temporal or spatial subsets of data to evaluate and provides options for data filtering, validation of anomalies and the use of different scaling methods.</p><p>Within this study we show the current status of the service, present its scope of operation and give an outlook on future developments such as the integration of high resolution data.</p><p>This work was supported by the QA4SM project, funded by the Austrian Space Applications Programme (FFG).</p>
<p>Quality assessment is an integral part of creating climate data records. Producers of satellite based records want to evaluate whether their products fulfill certain quality requirements, such as the ones set by the Global Climate Observing System (GCOS) of the World Meteorological Organization (WMO) or by the Committee on Earth Observation Satellites (CEOS). Users of these data, on the other hand, are usually interested in their fitness-for-purpose in terms of specific applications, temporal/spatial subsets, and how different data sets of the same variable compare to each other.<br />Quality Assurance for Soil Moisture (QA4SM) is an online validation service for (inter)comparing soil moisture records and assessing their quality, incorporating best practices, in a standardized, traceable way via an easy-to-use graphical user interface. The processing chain includes automatic preprocessing (filtering, temporal/spatial matching, scaling) of input data and computation of a set of quality metrics (e.g., correlation, bias, signal-to-noise-ratio). It provides an open and flexible framework in which users can upload their own data for comparison to state-of-the-art records that are already integrated in the service. These include reference data from the International Soil Moisture Network (ISMN), reanalysis data from ERA5 and GLDAS Noah, and various satellite based records such as SMOS, SMAP, Sentinel-1, ESA CCI, and C3S.&#160;<br />In this presentation we give insight into the scientific and technical background of developing a cloud-based validation service and its current capabilities. We explain the advantages a service like this has, and how it can benefit users of climate data records with minimal effort.</p> <p>The service was launched as part of the Quality Assurance for High Spatial and Temporal Resolution Soil Moisture Data (QA4SM-HR) project through the Austrian Research Promotion Agency (FFG) and is currently developed within the framework of the European Space Agency&#8217;s Fiducial Reference Measurement for Soil Moisture (FRM4SM) project. It can be accessed at: https://qa4sm.eu</p>
<p class="western" lang="en-US" align="justify"><span lang="fr-FR">The aim of this presentation is to report on recent advances concerning the satellite based soil moisture validation done through t</span>he ESA project &#8220;Fiducial Reference Measurement for Soil Moisture (FRM4SM)&#8221;<span lang="fr-FR">. T</span>he main objective<span lang="fr-FR"> of this </span>two years project (May 2021 - May 2023) <span lang="fr-FR">is </span>to study the means to inform on the confidence in soil moisture data products for the whole duration of a satellite mission. Composed of three international partners (AWST, CESBIO and TU WIEN), <span lang="fr-FR">it </span>aims at the identification and creation of standards for independent, fully characterized, accurate and traceable (i.e., fiducial) in situ soil moisture reference measurements with corresponding independent validation methods and uncertainty estimations for a satellite mission. The ground reference data is drawn from the International Soil Moisture Network (<span id="OBJ_PREFIX_DWT19829_com_zimbra_url" class="Object" role="link"><span id="OBJ_PREFIX_DWT19832_com_zimbra_url" class="Object" role="link">ISMN</span></span>). New quality indicators are created to better characterize the aptness of ISMN measurements for satellite soil moisture validation, and protocols provided to identify a select set of fiducial reference data. The satellite part, in charge of independent validation methods, focuses efforts towards the Soil Moisture Ocean Salinity (<span id="OBJ_PREFIX_DWT19830_com_zimbra_url" class="Object" role="link"><span id="OBJ_PREFIX_DWT19833_com_zimbra_url" class="Object" role="link">SMOS</span></span>) mission from ESA. Finally, the easy-to-use interface for the comparison of satellite soil moisture data against land surface models and in situ data, the Quality Assurance for Soil Moisture (<span id="OBJ_PREFIX_DWT19831_com_zimbra_url" class="Object" role="link"><span id="OBJ_PREFIX_DWT19834_com_zimbra_url" class="Object" role="link">QA4SM</span></span>), targets to implement all created FRM protocols from ground measurement to validation methods created within the FRM4SM project.</p> <p class="western" lang="en-US" align="justify">&#160;</p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.