GBOV (Ground-Based Observation for Validation): A Copernicus service for validation of Land Products

2020 ◽  
Author(s):  
Gabriele Bai ◽  
Christophe Lerebourg ◽  
Marco Clerici ◽  
Nadine Gobron ◽  
Jan-Peter Muller ◽  
...  
Keyword(s):  
Land Surface ◽  
Data Access ◽  
Earth Observation ◽  
Free Access ◽  
In Situ Observation ◽  
Area Index ◽  
First Case ◽  
New Instrumentation ◽  
Reference Measurements

<p>Copernicus is a European Union Earth Observation program, dedicated to monitor our planet and its environment, giving free access to remote sensing data and derived Earth Observation products. For proper use in environmental monitoring and scientific applications, it is fundamental to guarantee high quality and consistency of these satellite derived products. One of the possibilities to ensure product quality is to perform quantitative comparisons of satellite derived products with the corresponding in situ observation. Two options can then be considered for ground data sources: through intensive field campaigns or making use of permanent ground stations deployed and maintained on the long term. In the first case, a large variety of variable can be assessed, but logistical challenges and financial resources limit in time and space the products validation. More over meteorological constrains often limit the number of data that can actually be used for Earth Observation products. The second option is from far the most cost effective although it is not yet possible to cover all ground variables with permanent field deployment.</p><p>To achieve these objectives of systematic and long-term data validation, the <strong>Ground-Based Observations for Validation</strong> (GBOV) service has been implemented, facilitating the use of observations from operational ground-based monitoring networks and their comparison to EO products. The service is guaranteed through 3 different components:</p><ul><li>Collection of multi-year ground-based observations (<strong>Reference Measurements</strong> - RMs) of high relevance for the understanding of land surface processes from more than 50 existing sites. These RMs are then upscaled to generate <strong>Land Products</strong> (LPs), in order to validate the Copernicus products. In particular, the LPs distributed through the GBOV portal are: Top of Canopy Reflectance (ToC-R), surface albedo, Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Available Radiation (FAPAR), Fraction of Covered ground (FCover), Surface Soil Moisture (SSM) and Land Surface Temperature (LST).</li> <li>Upgrade of existing sites with new instrumentation or establishing entirely new monitoring sites to close thematic or geographical gaps. In 2019 new instrumentation has been installed in three different sites: Hainich (Germany), Valencia (Spain) and Tumbarumba (Australia). Litchfield (Australia), Dahra (Senegal) and Skukuza (South Africa) will be equipped with new instrumentation in the course of 2020.</li> <li>Implementation and maintenance of a database for the distribution of the Reference Measurements and the corresponding Land Products, available through the website https://land.copernicus.eu/global/gbov. GBOV data access is completely free, after registration and acceptation of the terms of use and the data policy.</li> </ul>

scholarly journals Comparison of LAI Estimates from High Resolution Satellite Observations Using Different Biophysical Processors

2021 ◽  
Vol 3 (1) ◽  
pp. 5
Author(s):  
Federico Filipponi
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Agricultural Land ◽  
Spectral Characteristics ◽  
Earth Observation ◽  
Estimation Accuracy ◽  
Landsat 8 ◽  
Biophysical Parameters ◽  
Area Index ◽  
Satellite Sensors

Earth observation provides timely and spatially explicit information about crop phenology and vegetation dynamics that can support decision making and sustainable agricultural land management. Vegetation spectral indices calculated from optical multispectral satellite sensors have been largely used to monitor vegetation status. In addition, techniques to retrieve biophysical parameters from satellite acquisitions, such as the Leaf Area Index (LAI), have allowed to assimilate Earth observation time series in numerical modeling for the analysis of several land surface processes related to agroecosystem dynamics. More recently, biophysical processors used to estimate biophysical parameters from satellite acquisitions have been calibrated for retrieval from sensors with different high spatial resolution and spectral characteristics. Virtual constellations of satellite sensors allow the generation of denser LAI time series, contributing to improve vegetation phenology estimation accuracy and, consequently, enhancing agroecosystems monitoring capacity. This research study compares LAI estimates over croplands using different biophysical processors from Sentinel-2 MSI and Landsat-8 OLI satellite sensors. The results are used to demonstrate the capacity of virtual satellite constellation to strengthen LAI time series to derive important cropland use information over large areas.

scholarly journals Climate Data Records of Vegetation Variables from Geostationary SEVIRI/MSG Data: Products, Algorithms and Applications

2019 ◽  
Vol 11 (18) ◽  
pp. 2103 ◽  
Author(s):  
Francisco Javier García-Haro ◽  
Fernando Camacho ◽  
Beatriz Martínez ◽  
Manuel Campos-Taberner ◽  
Beatriz Fuster ◽  
...  
Keyword(s):  
Land Surface ◽  
Expert Knowledge ◽  
Terrestrial Ecosystems ◽  
Environmental Applications ◽  
Climate Data ◽  
Area Index ◽  
Infrared Imager ◽  
Statistical Relationships ◽  
Spectral Mixture

The scientific community requires long-term data records with well-characterized uncertainty and suitable for modeling terrestrial ecosystems and energy cycles at regional and global scales. This paper presents the methodology currently developed in EUMETSAT within its Satellite Application Facility for Land Surface Analysis (LSA SAF) to generate biophysical variables from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board MSG 1-4 (Meteosat 8-11) geostationary satellites. Using this methodology, the LSA SAF generates and disseminates at a time a suite of vegetation products, such as the leaf area index (LAI), the fraction of the photosynthetically active radiation absorbed by vegetation (FAPAR) and the fractional vegetation cover (FVC), for the whole Meteosat disk at two temporal frequencies, daily and 10-days. The FVC algorithm relies on a novel stochastic spectral mixture model which addresses the variability of soils and vegetation types using statistical distributions whereas the LAI and FAPAR algorithms use statistical relationships general enough for global applications. An overview of the LSA SAF SEVIRI/MSG vegetation products, including expert knowledge and quality assessment of its internal consistency is provided. The climate data record (CDR) is freely available in the LSA SAF, offering more than fifteen years (2004-present) of homogeneous time series required for climate and environmental applications. The high frequency and good temporal continuity of SEVIRI products addresses the needs of near-real-time users and are also suitable for long-term monitoring of land surface variables. The study also evaluates the potential of the SEVIRI/MSG vegetation products for environmental applications, spanning from accurate monitoring of vegetation cycles to resolving long-term changes of vegetation.

Potential natural vegetation dynamics driven by future long-term climate change and its hydrological impacts in the Hanjiang River basin, China

2012 ◽  
Vol 43 (1-2) ◽  
pp. 73-90 ◽  
Author(s):  
Fei Yuan ◽  
Liliang Ren ◽  
Zhongbo Yu ◽  
Yonghua Zhu ◽  
Jing Xu ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
21St Century ◽  
Land Surface ◽  
Natural Vegetation ◽  
Potential Natural Vegetation ◽  
Area Index ◽  
Hanjiang River ◽  
Ipcc Sres

Vegetation and land-surface hydrology are intrinsically linked under long-term climate change. This paper aims to evaluate the dynamics of potential natural vegetation arising from 21st century climate change and its possible impact on the water budget of the Hanjiang River basin in China. Based on predictions of the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC-SRES) A1 scenario from the PRECIS (Providing Regional Climates for Impact Studies) regional climate model, changes in plant functional types (PFTs) and leaf area index (LAI) were simulated via the Lund-Potsdam-Jena dynamic global vegetation model. Subsequently, predicted PFTs and LAIs were employed in the Xinanjiang vegetation-hydrology model for rainfall–runoff simulations. Results reveal that future long-term changes in precipitation, air temperature and atmospheric CO2 concentration would remarkably affect the spatiotemporal distribution of PFTs and LAIs. These climate-driven vegetation changes would further influence regional water balance. With the decrease in forest cover in the 21st century, plant transpiration and evaporative loss of intercepted canopy water will tend to fall while soil evaporation may rise considerably. As a result, total evapotranspiration may increase moderately with a slight increase in annual runoff depth. This indicates that, for long-term hydrological prediction, climate-induced changes in terrestrial vegetation cannot be neglected as the terrestrial biosphere plays an important role in land-surface hydrological responses.

Evaluating the Simulated Seasonality of Soil Moisture with Earth Observation Data

2009 ◽  
Vol 10 (6) ◽  
pp. 1548-1560 ◽  
Author(s):  
Richard J. Ellis ◽  
Christopher M. Taylor ◽  
Graham P. Weedon ◽  
Nicola Gedney ◽  
Douglas B. Clark ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Leaf Area Index ◽  
Land Surface ◽  
Hydraulic Properties ◽  
Moisture Stress ◽  
Earth Observation ◽  
Soil Hydraulic Properties ◽  
Soil Moisture Stress ◽  
Area Index ◽  
Surface Scheme

Abstract A critical function of a land surface scheme, used in climate and weather prediction models, is to partition the energy from insolation into sensible and latent heat fluxes. Many use a soil moisture function to control the surface moisture fluxes through the transpiration. The validity and global distribution of the parameters used to calculate this soil moisture stress function are difficult to assess. This work presents a method to map soil moisture stress globally from an earth observation vegetation index and precipitation data, and it compares the resulting distributions with output from the Joint U.K. Land Environment Simulator (JULES) land surface scheme. A number of model runs with different soil and vegetation parameters are compared. These examine the sensitivity of the seasonality of soil moisture stress, within the model, to the parameterization of soil hydraulic properties and the seasonality of leaf area index in the vegetation. It is found that the seasonality of soil moisture within the model is more sensitive to the soil hydraulic properties than the leaf area index. The partitioning of throughfall into evaporation and runoff, in the model, is the dominant factor in determining the timing of soil moisture stress.

Assessment of different indices from Landsat time series in burned area mapping

2020 ◽  
Author(s):  
Jinxiu Liu
Keyword(s):  
Time Series ◽  
Burkina Faso ◽  
Land Surface ◽  
Vegetation Index ◽  
Landsat Imagery ◽  
Burned Area ◽  
Free Access ◽  
Landsat Images ◽  
Area Index ◽  
Burned Area Mapping

<p>Fire is recognized as an important land surface disturbance, as it influences terrestrial carbon cycle, climate and biodiversity. Accurate and efficient mapping of burned area is beneficial for social and environmental applications. Remote sensing plays a key role in detecting burned areas and active fires from reginal to global scales. Due to the free access to the Landsat archive, studies using dense time series of Landsat imagery for burned area mapping are appearing and increasing. However, the performance of Landsat time series when using different indices for burned area mapping has not been assessed. In this study, the objective was to identify which indices can detect burned area better when using Landsat time series in savanna area of southern Burkina Faso. We selected Burned Area Index (BAI), Normalized Burned Ratio (NBR), Normalized Difference Vegetation Index (NDVI), Global Environmental Monitoring Index (GEMI) for comparison as they are commonly used indices for burned area detection. The algorithm was based on breakpoint identification and burned pixel detection using harmonic model fitting with different indices Landsat time series. It was tested in savanna area in southern Burkina Faso over 16 years with 281 Landsat images ranging from October 2000 to April 2016.The same reference data was used to evaluate the performance of burned area detection with different indices Landsat time series. The result demonstrated that BAI was the most accurate in burned area detection from Landsat time series, followed by NBR, GEMI and NDVI.</p>

scholarly journals Comprehensive Assessment of Performances of Long Time-Series LAI, FVC and GPP Products over Mountainous Areas: A Case Study in the Three-River Source Region, China

2021 ◽  
Vol 14 (1) ◽  
pp. 61
Author(s):  
Wenqi Zhang ◽  
Huaan Jin ◽  
Ainong Li ◽  
Huaiyong Shao ◽  
Xinyao Xie ◽  
...  
Keyword(s):  
Time Series ◽  
Global Change ◽  
Land Surface ◽  
Gross Primary Production ◽  
Source Region ◽  
Mountainous Areas ◽  
Area Index ◽  
Vegetation Activity ◽  
Long Time

Vegetation biophysical products offer unique opportunities to examine long-term vegetation dynamics and land surface phenology (LSP). It is important to understand the time-series performances of various global biophysical products for global change research. However, few endeavors have been dedicated to assessing the performances of long-term change characteristics or LSP extraction derived from different satellite products, especially in mountainous areas with highly fragmented and rugged surfaces. In this paper, we assessed the time-series characteristics and LSP detections of Global LAnd Surface Satellite (GLASS) leaf area index (LAI), fractional vegetation cover (FVC), and gross primary production (GPP) products across the Three-River Source Region (TRSR). The performances of products’ temporal agreements and their statistical relationship as a function of topographic indices and heterogeneous pixels, respectively, were investigated through intercomparison among three products during the period 2000 to 2018. The results show that the phenological differences between FVC and two other products are beyond 10 days over more than 35% of the pixels in TRSR. The long-term trend of FVC diverges significantly from GPP and LAI for 13.96% of the total pixels, and the percentages of mismatched pixels between FVC and two other products are 33.24% in the correlation comparison. Moreover, good agreements are observed between GPP and LAI, both in terms of LSP and interannual variations. Finally, the LSP and long-term dynamics of the three products exhibit poor performances on heterogeneous surfaces and complex topographic areas, which reflects the potential impacts of environmental factors and algorithmic imperfections on the quality and performances of different products. Our study highlights the spatiotemporal disparities in detections of surface vegetation activity in mountainous areas by using different biophysical products. Future global change studies may require multiple high-quality satellite products with long-term stability as data support.

scholarly journals Quality Assurance Framework Development Based on Six New ECV Data Products to Enhance User Confidence for Climate Applications

2018 ◽  
Author(s):  
Joanne Nightingale ◽  
Folkert Boersma ◽  
Jan-Peter Muller ◽  
Steven Compernolle ◽  
Jean-Christopher Lambert ◽  
...  
Keyword(s):  
Climate Change ◽  
Quality Assurance ◽  
Climate Model ◽  
Earth Observation ◽  
Evidence Based ◽  
The European Union ◽  
Climate Data ◽  
Area Index ◽  
Data Products ◽  
Reference Measurements

Data from Earth Observation (EO) satellites are increasingly used to monitor the environment, understand variability and change, inform evaluations of climate model forecasts and manage natural resources. Policy makers are progressively relying on the information derived from these datasets to make decisions on mitigating and adapting to climate change. These decisions should be evidence based, which requires confidence in derived products as well as the reference measurements used to calibrate, validate or inform product development. In support of the European Union’s Earth Observation Programmes Copernicus Climate Change Service, the Quality Assurance for Essential Climate Variables (QA4ECV) project fulfilled a gap in the delivery of climate quality satellite derived datasets by prototyping a robust, generic system for the implementation and evaluation of Quality Assurance (QA) measures for satellite-derived ECV climate data record products. The project demonstrated the QA system on six new long-term, climate quality ECV data records for surface Albedo, Leaf Area Index, FAPAR, NO2, HCHO and CO. Provision of standardized QA information provides data users with evidence-based confidence in the products and enables judgement on the fitness-for-purpose of various ECV data products their specific applications.

scholarly journals Quality Assurance Framework Development Based on Six New ECV Data Products to Enhance User Confidence for Climate Applications

2018 ◽  
Vol 10 (8) ◽  
pp. 1254 ◽  
Author(s):  
Joanne Nightingale ◽  
Klaas Boersma ◽  
Jan-Peter Muller ◽  
Steven Compernolle ◽  
Jean-Christopher Lambert ◽  
...  
Keyword(s):  
Climate Change ◽  
Quality Assurance ◽  
Climate Model ◽  
Earth Observation ◽  
Evidence Based ◽  
Climate Data ◽  
Area Index ◽  
Data Products ◽  
Reference Measurements ◽  
Framework Development

Data from Earth observation (EO) satellites are increasingly used to monitor the environment, understand variability and change, inform evaluations of climate model forecasts, and manage natural resources. Policymakers are progressively relying on the information derived from these datasets to make decisions on mitigating and adapting to climate change. These decisions should be evidence based, which requires confidence in derived products, as well as the reference measurements used to calibrate, validate, or inform product development. In support of the European Union’s Earth Observation Programmes Copernicus Climate Change Service (C3S), the Quality Assurance for Essential Climate Variables (QA4ECV) project fulfilled a gap in the delivery of climate quality satellite-derived datasets, by prototyping a generic system for the implementation and evaluation of quality assurance (QA) measures for satellite-derived ECV climate data record products. The project demonstrated the QA system on six new long-term, climate quality ECV data records for surface albedo, leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), nitrogen dioxide (NO2), formaldehyde (HCHO), and carbon monoxide (CO). The provision of standardised QA information provides data users with evidence-based confidence in the products and enables judgement on the fitness-for-purpose of various ECV data products and their specific applications.

scholarly journals Evaluation of Six Directional Canopy Emissivity Models in the Thermal Infrared Using Emissivity Measurements

2019 ◽  
Vol 11 (24) ◽  
pp. 3011
Author(s):  
Lluís Pérez-Planells ◽  
Enric Valor ◽  
Raquel Niclòs ◽  
César Coll ◽  
Jesús Puchades ◽  
...  
Keyword(s):  
Land Surface ◽  
Thermal Infrared ◽  
Organic Soil ◽  
Area Index ◽  
Directional Emissivity ◽  
Reference Measurements ◽  
Emissivity Measurements ◽  
Single Set ◽  
Different Soils

Land surface temperature (LST) is a fundamental physical quantity in a range of different studies, for example in climatological analyses and surface–atmosphere heat flux assessments, especially in heterogeneous and complex surfaces such as vegetated canopies. To obtain accurate LST values, it is important to measure accurately the land surface emissivity (LSE) in the thermal infrared spectrum. In the past decades, different directional emissivity canopy models have been proposed. This paper evaluates six radiative transfer models (FR97, Mod3, Rmod3, 4SAIL, REN15, and CE-P models) through a comparison with in situ emissivity measurements performed using the temperature-emissivity separation (TES) method. The evaluation is done using a single set of rose plants over two different soils with very different spectral behavior. First, using an organic soil, the measurements were done for seven different observation angles, from 0° to 60° in steps of 10°, and for six different values of leaf area index (LAI). Taking into account all LAIs, the bias (and root mean square error, RMSE) obtained were 0.003 (±0.006), −0.004 (±0.005), −0.009 (±0.011), 0.005 (±0.007), 0.004 (±0.007), and 0.005 (±0.007) for FR97, Mod3, Rmod3, 4SAIL, REN 15, and CE-P models, respectively. Second, using an inorganic soil, the measurements were done for six different LAIs but for two different observation angles: 0° and 55°. The bias (and RMSE) obtained were 0.012 (±0.014), 0.004 (±0.007), −0.020 (±0.035), 0.016 (±0.017), 0.013 (±0.015), 0.013 (±0.015) and for FR97, Mod3, Rmod3, 4SAIL, REN15, and CE-P models, respectively. Overall, the Mod3 model appears as the best model in comparison to the TES emissivity reference measurements.

scholarly journals Heterogeneous access and processing of EO-Data on a Cloud based Infrastructure delivering operational Products

2015 ◽  
Vol XL-7/W3 ◽  
pp. 663-667
Author(s):  
F. Niggemann ◽  
F. Appel ◽  
H. Bach ◽  
J. de la Mar ◽  
B. Schirpke ◽  
...  
Keyword(s):  
Land Surface ◽  
Atmospheric Correction ◽  
Data Access ◽  
Scientific Data ◽  
Earth Observation ◽  
Landsat 8 ◽  
Cloud Environment ◽  
Cloud Infrastructure ◽  
And Performance ◽  
High Flexibility

To address the challenges of effective data handling faced by Small and Medium Sized Enterprises (SMEs) a cloud-based infrastructure for accessing and processing of Earth Observation(EO)-data has been developed within the project APPS4GMES(www.apps4gmes.de). To gain homogenous multi mission data access an Input Data Portal (IDP) been implemented on this infrastructure. The IDP consists of an Open Geospatial Consortium (OGC) conformant catalogue, a consolidation module for format conversion and an OGC-conformant ordering framework. Metadata of various EO-sources and with different standards is harvested and transferred to an OGC conformant Earth Observation Product standard and inserted into the catalogue by a Metadata Harvester. The IDP can be accessed for search and ordering of the harvested datasets by the services implemented on the cloud infrastructure. Different land-surface services have been realised by the project partners, using the implemented IDP and cloud infrastructure. Results of these are customer ready products, as well as pre-products (e.g. atmospheric corrected EO data), serving as a basis for other services. Within the IDP an automated access to ESA’s Sentinel-1 Scientific Data Hub has been implemented. Searching and downloading of the SAR data can be performed in an automated way. With the implementation of the Sentinel-1 Toolbox and own software, for processing of the datasets for further use, for example for Vista’s snow monitoring, delivering input for the flood forecast services, can also be performed in an automated way. For performance tests of the cloud environment a sophisticated model based atmospheric correction and pre-classification service has been implemented. Tests conducted an automated synchronised processing of one entire Landsat 8 (LS-8) coverage for Germany and performance comparisons to standard desktop systems. Results of these tests, showing a performance improvement by the factor of six, proved the high flexibility and computing power of the cloud environment. To make full use of the cloud capabilities a possibility for automated upscaling of the hardware resources has been implemented. Together with the IDP infrastructure fast and automated processing of various satellite sources to deliver market ready products can be realised, thus increasing customer needs and numbers can be satisfied without loss of accuracy and quality.

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