Special Issue "Recent Advances in Satellite Derived Global Land Product Validation"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Biogeosciences Remote Sensing".

Deadline for manuscript submissions: 31 December 2020.

Special Issue Editors

Dr. Fernando Camacho
Website
Guest Editor
Earth Observation Laboratory (EOLAB), Parc Cientific University of Valencia, C/ Catedràtic Agustín Escardino, 9, 46980 Paterna, Valencia, Spain
Interests: retrieval of biophysical variables from satellite data; validation of satellite-derived global land products; fiducial reference measurements; cal/val field campaigns; climate data records of terrestrial ECVs; agriculture monitoring; climate change awareness
Prof. Dr. Jadu Dash
Website
Guest Editor
Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
Interests: land surface phenology; Earth observation; biophysical variables; agriculture
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

The retrieval of global land properties from space has entered into an operational phase with a multiplicity of Earth Observation services and space agencies delivering bio-geophysical variables over land at global scale and from a wide range of spaceborne sensors at different spatial and temporal resolutions. In particular, climate data records (CDR) of terrestrial Essential Climate Variables (ECVs) are being produced in support of Global Climate Observing System (GCOS) exploiting past and current satellite observations. The quality of these global land products and CDR of ECVs must be assessed by independent means to inform users on the uncertainties attached to these satellite derived land products. Global validation of land products is however a challenging task due to the variety of conditions encountered at global scale and by the spatial and temporal mismatch between ground references and the satellite products, which requires well-established methodologies for the collection of fiducial ground measurements, and for performing the validation over global conditions. Due to nature of these applications information on uncertainty and traceability are crucial.
This Special Issue aims at collecting recent developments, methodologies, and best practices for global land product validation and ground data collection, as well as the latest results on validation of global land products.

• Satellite-derived land products validation methodologies and best practices
• Methods to estimate accuracy, uncertainty and traceability of bio-geophysical variables
• Recent results on validation of global satellite derived land products and CDR of ECVs
• Protocols and best practice for in-situ data collection of bio-geophysical variables
• New tools and techniques for in-situ data collection of bio-geophysical variables
• Fiducial reference measurements in support of satellite-derived land products validation
• Upscaling methodologies, from point measurements to satellite resolution
• Networks of sites and supersites for global satellite-derived land products validation
• Benchmarking exercises between existing global satellite-derived land products

Dr. Fernando Camacho
Dr. Jadu Dash
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Land products
  • Accuracy
  • Uncertainty
  • Stability
  • Validation
  • Ground measurements
  • Upscaling
  • Intercomparison

Published Papers (7 papers)

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Research

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Open AccessFeature PaperArticle
Quality Assessment of PROBA-V Surface Albedo V1 for the Continuity of the Copernicus Climate Change Service
Remote Sens. 2020, 12(16), 2596; https://doi.org/10.3390/rs12162596 - 12 Aug 2020
Abstract
The Copernicus Climate Change Service (C3S) includes estimates of Essential Climate Variables (ECVs) as a series of Climate Data Records (CDRs) derived from satellite data. The C3S Surface Albedo (SA) v1.0 CDR is composed of observations from National Oceanic and Atmospheric Administration (NOAA) [...] Read more.
The Copernicus Climate Change Service (C3S) includes estimates of Essential Climate Variables (ECVs) as a series of Climate Data Records (CDRs) derived from satellite data. The C3S Surface Albedo (SA) v1.0 CDR is composed of observations from National Oceanic and Atmospheric Administration (NOAA) Very High Resolution Radiometers (AVHRR) (1981–2005), and VEGETATION sensors onboard Satellites for the Observation of the Earth (SPOT/VGT) (1998–2014) and Project for Onboard Autonomy satellite (PROBA-V) (2014–2020), and will continue with Sentinel-3 (from 2020 onwards). The goal of this study is to assess the uncertainties associated with the C3S PROBA-V SA v1.0 product, with a focus on the transition from SPOT/VGT to PROBA-V. The methodology followed the good practices recommended by the Land Product Validation sub-group (LPV) of the Working Group on Calibration and Validation (WGCV) of the Committee on Earth Observing Satellites (CEOS) for the validation of satellite-derived global albedo products. Several performance criteria were evaluated, including an intercomparison with National Aeronautics and Space Agency (NASA) MCD43A3 C6 products. C3S PROBA-V SA v1.0 and MCD43A3 C6 showed similar completeness but had higher fractions of missing data than C3S SPOT/VGT SA v1.0. C3S PROBA-V SA v1.0 showed similar precision (~1%) to MCD43A3 C6, improving the results of SPOT/VGT SA v1.0 (2–3%), but C3S PROBA-V SA v1.0 provided residual noise in the near-infrared (NIR). Good spatio-temporal continuity between C3S PROBA-V and SPOT/VGT SA v1.0 products was found with a mean bias between ±2%. The comparison with MCD43A3 C6 showed positive mean biases (5%, 8%, and 12% for visible, NIR and total shortwave, respectively). The accuracy assessment with ground measurements showed a median error of 18.4% with systematic overestimation (positive bias of 11.5%). The percentage of PROBA-V retrievals complying with the C3S target requirements was 28.6%. Full article
(This article belongs to the Special Issue Recent Advances in Satellite Derived Global Land Product Validation)
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Open AccessFeature PaperArticle
Evaluation of Two Global Land Surface Albedo Datasets Distributed by the Copernicus Climate Change Service and the EUMETSAT LSA-SAF
Remote Sens. 2020, 12(11), 1888; https://doi.org/10.3390/rs12111888 - 10 Jun 2020
Abstract
The present paper is devoted to the quality assessment of two global land surface albedo products developed by Meteo France in the frame of the Copernicus Climate Change Service (C3S) and the LSA-SAF (Satellite Application Facility on Land Surface Analysis), herein called, respectively, [...] Read more.
The present paper is devoted to the quality assessment of two global land surface albedo products developed by Meteo France in the frame of the Copernicus Climate Change Service (C3S) and the LSA-SAF (Satellite Application Facility on Land Surface Analysis), herein called, respectively, VGT (VeGeTation) (the C3Sv1 dataset, derived from VGT sensors onboard Satellites for the Observation of the Earth, also called SPOT) and ETAL (European polar system Ten-day surface ALbedo, derived from Advanced Very High Resolution Radiometers (AVHRR) onboard METeorological OPerational (METOP) satellites). The evaluation study inter-compared these products with measurements at 33 ground stations and two independent operational products, MTAL-R/NRT (Meteosat second generation Ten-day ALbedo Reprocessed/Near Real-Time) and MODIS (MODerate resolution Imaging Spectroradiometer), over two distinct four-year periods. In accordance with the prescription from the Land Product Validation group of the joint Committee on Earth Observation Satellites (LPV/CEOS), the evaluation was addressed per land cover; furthermore, two albedo regimes were considered throughout the evaluation to distinguish between high (over 0.15) and low (below 0.15) surface albedo behaviors. First, we show that both VGT and ETAL products agree well with the measurements and the other satellite products at the ground stations. Second, when inter-compared with MODIS, the results are noteworthy for ETAL as opposed to VGT, with 11 out of 13 land cover types passing the Global Climate Observing System (GCOS) requirements for more than 80% of the sites for albedo values less than 0.15 (compared with none for VGT) and 10 out of 14 land cover types passing the GCOS requirements for more than 50% of the sites for albedo values greater than 0.15 (compared with 5 for VGT). Finally, a pixel-by-pixel analysis reveals that VGT overestimates the surface albedo as compared with MODIS by about 0.02 in absolute value for albedo values less than 0.15 and by about 22% in relative value for albedo values greater than 0.15. The root-mean-square-deviation (RMSD) in absolute value is about 0.015 for albedo values less than 0.15 and 51.5% in relative value for albedo values greater than 0.15. In contrast, the bias for ETAL when compared with MODIS remains very small. Over the four-year period, ETAL overestimates the surface albedo as compared with MODIS by 0.001 in absolute value for the regime of surface albedo less than 0.15 and by about 5.8% in relative value for albedo values greater than 0.15. The RMSD in absolute value is about 0.014 for albedo values less than 0.15 and 19.4% in relative value for albedo values greater than 0.15. Assuming that the MODIS product is a good reference, a relative bias of around 6% can be judged satisfactory for ETAL surface albedo. The lower performance of the VGT (C3Sv1) product is currently the subject of investigation. Work is ongoing to upgrade it further towards the final C3S product. Full article
(This article belongs to the Special Issue Recent Advances in Satellite Derived Global Land Product Validation)
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Open AccessArticle
Quality Assessment of PROBA-V LAI, fAPAR and fCOVER Collection 300 m Products of Copernicus Global Land Service
Remote Sens. 2020, 12(6), 1017; https://doi.org/10.3390/rs12061017 - 22 Mar 2020
Cited by 5
Abstract
The Copernicus Global Land Service (CGLS) provides global time series of leaf area index (LAI), fraction of absorbed photosynthetically active radiation (fAPAR) and fraction of vegetation cover (fCOVER) data at a resolution of 300 m and a frequency of 10 days. We performed [...] Read more.
The Copernicus Global Land Service (CGLS) provides global time series of leaf area index (LAI), fraction of absorbed photosynthetically active radiation (fAPAR) and fraction of vegetation cover (fCOVER) data at a resolution of 300 m and a frequency of 10 days. We performed a quality assessment and validation of Version 1 Collection 300 m products that were consistent with the guidelines of the Land Product Validation (LPV) subgroup of the Committee on Earth Observation System (CEOS) Working Group on Calibration and Validation (WGCV). The spatiotemporal patterns of Collection 300 m V1 LAI, fAPAR and fCOVER products are consistent with CGLS Collection 1 km V1, Collection 1 km V2 and Moderate Resolution Imagery Spectroradiometer Collection 6 (MODIS C6) products. The Collection 300 m V1 products have good precision and smooth temporal profiles, and the interannual variations are consistent with similar satellite products. The accuracy assessment using ground measurements mainly over crops shows an overall root mean square deviation of 1.01 (44.3%) for LAI, 0.12 (22.2%) for fAPAR and 0.21 (42.6%) for fCOVER, with positive mean biases of 0.36 (15.5%), 0.05 (10.3%) and 0.16 (32.2%), respectively. The products meet the CGLS user accuracy requirements in 69.1%, 62.5% and 29.7% of the cases for LAI, fAPAR and fCOVER, respectively. The CGLS will continue the production of Collection 300 m V1 LAI, fAPAR and fCOVER beyond the end of the PROBA-V mission by using Sentinel-3 OLCI as input data. Full article
(This article belongs to the Special Issue Recent Advances in Satellite Derived Global Land Product Validation)
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Open AccessArticle
Operational Soil Moisture from ASCAT in Support of Water Resources Management
Remote Sens. 2019, 11(5), 579; https://doi.org/10.3390/rs11050579 - 09 Mar 2019
Cited by 5
Abstract
This study provides the results of an extensive investigation of the Advanced Scaterometter (ASCAT) surface soil moisture global operational product accuracy across three continents (United States of America (USA), Europe, and Australia). ASCAT predictions of surface soil moisture were compared against near concurrent [...] Read more.
This study provides the results of an extensive investigation of the Advanced Scaterometter (ASCAT) surface soil moisture global operational product accuracy across three continents (United States of America (USA), Europe, and Australia). ASCAT predictions of surface soil moisture were compared against near concurrent in situ measurements from the FLUXNET observational network. A total of nine experimental sites were used to assess the accuracy of ASCAT Surface Soil Moisture (ASCAT SSM) predictions for two complete years of observations (2010, 2011). Results showed a generally reasonable agreement between the ASCAT product and the in situ soil moisture measurements in the 0–5 cm soil moisture layer. The Root Mean Square Error (RMSE) was below 0.135 m3 m−3 at all of the sites. With a few exceptions, Pearson’s correlation coefficient was above 45%. Grassland, shrublands, and woody savanna land cover types exhibited satisfactory agreement in all the sites analyzed (RMSE ranging from 0.05 to 0.13 m3 m−3). Seasonal performance was tested, but no definite conclusion can be made with statistical significance at this time, as the seasonal results varied from continent to continent and from year to year. However, the satellite and in situ measurements for Needleleaf forests were practically uncorrelated (R = −0.11 and −0.04). ASCAT predictions overestimated the observed values at all of the sites in Australia. A positive bias of approximately 0.05 m3 m−3 was found with respect to the observed values that were in the range 0–0.3 m3 m−3. Better agreement was observed for the grassland sites in most cases (RMSE ranging from 0.09 to 0.10 m3 m−3 and R from 0.46 to 0.90). Our results provide supportive evidence regarding the potential value of the ASCAT global operational product for meso-scale studies and the relevant practical applications. A key contribution of this study is a comprehensive evaluation of ASCAT product soil moisture estimates at different sites around the globe. These sites represent a variety of climatic, environmental, biome, and topographical conditions. Full article
(This article belongs to the Special Issue Recent Advances in Satellite Derived Global Land Product Validation)
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Open AccessArticle
Spatial Consistency Assessments for Global Land-Cover Datasets: A Comparison among GLC2000, CCI LC, MCD12, GLOBCOVER and GLCNMO
Remote Sens. 2018, 10(11), 1846; https://doi.org/10.3390/rs10111846 - 21 Nov 2018
Cited by 10
Abstract
Numerous global-scale land-cover datasets have greatly contributed to the study of global environmental change and the sustainable management of natural resources. However, land-cover datasets inevitably experience information loss because of the nature of the uncertainty in the interpretation of remote-sensing images. Therefore, analyzing [...] Read more.
Numerous global-scale land-cover datasets have greatly contributed to the study of global environmental change and the sustainable management of natural resources. However, land-cover datasets inevitably experience information loss because of the nature of the uncertainty in the interpretation of remote-sensing images. Therefore, analyzing the spatial consistency of multi-source land-cover datasets on the global scale is important to maintain the consistency of time and consider the effects of land-cover changes on spatial consistency. In this study, we assess the spatial consistency of five land-cover datasets, namely, GLC2000, CCI LC, MCD12, GLOBCOVER and GLCNMO, at the global and continental scales through climate and elevation partitions. The influencing factors of surface conditions and data producers on the spatial inconsistency are discussed. The results show that the global overall consistency of the five datasets ranges from 49.2% to 67.63%. The spatial consistency of Europe is high, and the multi-year value is 66.57%. In addition, the overall consistency in the EF climatic zone is very high, around 95%. The surface conditions and data producers affect the spatial consistency of land-cover datasets to different degrees. CCI LC and GLCNMO (2013) have the highest overall consistencies on the global scale, reaching 67.63%. Generally, the consistency of these five global land-cover datasets is relatively low, increasing the difficulty of satisfying the needs of high-precision land-surface-process simulations. Full article
(This article belongs to the Special Issue Recent Advances in Satellite Derived Global Land Product Validation)
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Review

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Open AccessEditor’s ChoiceReview
Validation of Earth Observation Time-Series: A Review for Large-Area and Temporally Dense Land Surface Products
Remote Sens. 2019, 11(22), 2616; https://doi.org/10.3390/rs11222616 - 08 Nov 2019
Cited by 2
Abstract
Large-area remote sensing time-series offer unique features for the extensive investigation of our environment. Since various error sources in the acquisition chain of datasets exist, only properly validated results can be of value for research and downstream decision processes. This review presents an [...] Read more.
Large-area remote sensing time-series offer unique features for the extensive investigation of our environment. Since various error sources in the acquisition chain of datasets exist, only properly validated results can be of value for research and downstream decision processes. This review presents an overview of validation approaches concerning temporally dense time-series of land surface geo-information products that cover the continental to global scale. Categorization according to utilized validation data revealed that product intercomparisons and comparison to reference data are the conventional validation methods. The reviewed studies are mainly based on optical sensors and orientated towards global coverage, with vegetation-related variables as the focus. Trends indicate an increase in remote sensing-based studies that feature long-term datasets of land surface variables. The hereby corresponding validation efforts show only minor methodological diversification in the past two decades. To sustain comprehensive and standardized validation efforts, the provision of spatiotemporally dense validation data in order to estimate actual differences between measurement and the true state has to be maintained. The promotion of novel approaches can, on the other hand, prove beneficial for various downstream applications, although typically only theoretical uncertainties are provided. Full article
(This article belongs to the Special Issue Recent Advances in Satellite Derived Global Land Product Validation)
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Other

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Open AccessLetter
Mapping Fragmented Impervious Surface Areas Overlooked by Global Land-Cover Products in the Liping County, Guizhou Province, China
Remote Sens. 2020, 12(9), 1527; https://doi.org/10.3390/rs12091527 - 11 May 2020
Abstract
Imperviousness is an important indicator for monitoring urbanization and environmental changes, and is evaluated widely in urban areas, but not in rural areas. An accurate impervious surface area (ISA) map in rural areas is essential to achieve environmental conservation and sustainable rural development. [...] Read more.
Imperviousness is an important indicator for monitoring urbanization and environmental changes, and is evaluated widely in urban areas, but not in rural areas. An accurate impervious surface area (ISA) map in rural areas is essential to achieve environmental conservation and sustainable rural development. Global land-cover products such as MODIS MCD12Q1, ESA CCI-LC, and Global Urban Land are common resources for environmental practitioners to collect land-cover information including ISAs. However, global products tend to focus on large ISA agglomerations and may not identify fragmented ISA extents in less populated regions. Land-use planners and practitioners have to map ISAs if it is difficult to obtain such spatially explicit information from local governments. A common and consistent approach for rural ISA mapping is yet to be established. A case study of the Liping County, a typical rural region in southwest China, was undertaken with the objectives of assessing the global land-cover products in the context of rural ISA mapping and proposing a simple and feasible approach for the mapping. This approach was developed using Landsat 8 imagery and by applying a random forests classifier. An appropriate number of training samples were distributed to towns or villages across all townships in the study area for classification. The results demonstrate that the global land-cover products identified major ISA agglomerations, specifically at the county seat; however, other fragmented ISAs over the study area were overlooked. In contrast, the map created using the developed approach inferred ISAs across all townships with an overall accuracy of 91%. A large amount of training samples together with geographic information of towns or villages is the key suggestion to identify and map ISAs in rural areas. Full article
(This article belongs to the Special Issue Recent Advances in Satellite Derived Global Land Product Validation)
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