CUP4SOIL - HIGH RESOLUTION SOIL QUALITY INDICATORS MAPS FOR EUROPE
Heiden, Uta; d'Angelo, Pablo; Poggio, Laura; Karlshoefer, Paul; van Egmond, Fenny; van der Woude, Thaisa
- Publisher
- Zenodo
- Language
- en
Abstract
High-resolution reliable and quality-controlled soil information products are fundamental for a range of applications related to climate change and sustainable management. Integration of remote sensing information is a key strategy to obtain more accurate and relevant products. Digital soil mapping (DSM) uses a statistical model to integrate products derived from Copernicus satellites Sentinel-1 and 2, environmental covariates such as digital elevation models, ERA-5 products and soil ground truth information from the LUCAS survey and other available sources. Several data products are derived from the Sentinel-2 time series using the Soil Composite Mapping Processor (SCMaP). It comprises mean reflectance composites as well as specific soil reflectance composites that contain undisturbed and bare soils. Additionally, the bare soil frequency is a measure for the visibility of the bare soil within the whole observed time period in percent. EO based soil products were generated for primary soil properties (SOC, pH, texture), derived soil properties and some basic soil health indicators. These properties were selected as a short list by scanning the current policy framework, existing projects and initiatives. In the second phase, users are approached by a survey and webinar to prioritise and specify the user needs for the shortlist, and to check for additional user needs and specifications. In total, 150 potential users have been reached so far. The soil observations were split in 10 equally sized folds for cross-validation. Random Forest models were obtained with the ranger package, with the option to build Quantile Random Forests (QRF) to obtain pixel-based uncertainty. This contribution will discuss where to go from the generation of high resolution products with a sparse point data sampling such as LUCAS, to their evaluation (including landscape patterns), to their relevance of use for stakeholders. The results of a user requirement survey dedicated to future soil products within the Copernicus Land Monitoring Service will be taken into account into the discussion of the products and their fitness for use. Keywords: digital soil mapping, remote sensing, copernicus, soil quality
Full text
CUP4SOIL HIGH RESOLUTION SOIL QUALITY INDICATORS MAPS FOR EUROPE Uta Heiden1, Pablo d'Angelo1, Laura Poggio2, Paul Karlshöfer1, Fenny van Egmond2, Thaïsa van der Woude2 1DLR 2ISRIC Centennial Celebration and Congress of the International Union of Soil Sciences May 19-21, 2024 DLR.de • Chart 1
Introduction CUP4SOIL general objective Objectives •Prepare a potential Copernicus downstream service to support national and European agencies for reporting on soil health/quality. •Generate European-wide example data products characterising soil health/quality •Develop a user community that tests and validates data products for soil health/quality information •Ensure close cooperation with the ESA WorldSoils project activities and other related projects/initiatives such as the EJP SOIL projects and others etc. … •Intermediate SCMaP soil products •Current possibility of EO-based soil parameter •Deviations from user requirements •Data package to “play around” •Develop show cases
Methodology General overview SCMaP Compositing MEAN + STD Bare surface reflectance composite Mean + STD reflectance composite Index calc. + thresholding Bare surface detection Averaging Averaging + Statistics Cloud and haze filter Input data Sentinel-2 Reflectances + Cloud Masks European Threshold Database ESA WorldCover Bare surface mask Bare surface pixel count Bare surface frequency Valid pixel count SCMaP Output •All Sentinel–2 images in L2A format -> processed with MAJA from 2018 –2022 •Larger Europe including Ukraine •Spectral Index based (e.g. Diek et al. 2017, Rogge et al. 2018, Demattê et al., 2018) •Used index: PV+IR2 (Heiden et al. 2022, Möller, M. et al. 2022, Dvorakova, K., et al., 2023) •Regionalised thresholds (Karlshöfer et al., in preparation) •5-years composite products
Methodology General overview SCMaP Compositing MEAN + STD Bare surface reflectance composite Mean + STD reflectance composite Index calc. + thresholding Bare surface detection Averaging Averaging + Statistics Cloud and haze filter Input data Sentinel-2 Reflectances + Cloud Masks European Threshold Database ESA WorldCover Bare surface mask Bare surface pixel count Bare surface frequency Valid pixel count SCMaP Output Digital Soil Mapping
Methodology Digital Soil Mapping –some notes Digital Soil Mapping •Input data from LUCAS (and other sources in WoSIS if relevant) •Covariates: oData prepared by DLR oData available from Copernicus (DEM, land cover) oGeology/parent material (JRC) oSimple radar products from Sentinel1 •Model: quantile random forest (robust approach allowing pixel-based uncertainty assessment) •Outputs: oPrimary soil properties oUncertainty index oOther uncertainty measures (to be further developed)
Example Data France
Mean Surface Reflectance •Sentinel-2 •L2A reflectance (MAJA processed) •2018 – 2022 Example France SCMaP products Paris Nancy
Mean Surface Reflectance •Sentinel-2 •L2A reflectance (MAJA processed) •2018 – 2022 Example France SCMaP products Paris Nancy
Bare Soil/Surface Reflectance – •Sentinel-2 •L2A reflectance (MAJA processed) •2018 – 2022 •PV+IR2 •Regionalised thresholds Example France SCMaP products Paris Nancy
Intermediate products Cross-validation - SOC Used covariates at the X-Axes: Groups (x -axes) Description no_dlr All covariates excluding DLR/ SCMaP products no_dlr_src All covariates excluding DLR/ SCMaP covariate: Soil Reflectance Composite no_dlr_src_mos All covariates excluding DL/SCMaP covariates using the mosaic of MREF and SRC and SRC itself
Intermediate products Cross-validation –pH (water) Groups (x -axes) Description no_dlr All covariates excluding DLR/ SCMaP products no_dlr_src All covariates excluding DLR/ SCMaP covariate: Soil Reflectance Composite no_dlr_src_mos All covariates excluding DL/SCMaP covariates using the mosaic of MREF and SRC and SRC itself Used covariates at the X-Axes:
Intermediate products Cross-validation –bulk density (oven dry) Groups (x -axes) Description no_dlr All covariates excluding DLR/ SCMaP products no_dlr_src All covariates excluding DLR/ SCMaP covariate: Soil Reflectance Composite no_dlr_src_mos All covariates excluding DL/SCMaP covariates using the mosaic of MREF and SRC and SRC itself Used covariates at the X-Axes:
Iterative process: •Reviewing existing projects and initiatives •User requirement survey •User requirement meeting - 7th December 2023 - online •Feedback from case study results CUP4SOIL –User Requirement Study User requirements Review of current projects and initiatives List of soil health indicators (SHI) Selection of SHI by EO capabilities (shortlist) UR survey question development User requirement consolidation UR virtual meeting/ workshops Online survey gathering user needs Definition of the Copernicus user list
CUP4SOIL –User Requirement Study User Survey –Workshop Which soil-related spatial information would be helpful for your work (basic soil properties)? Same prioritisation
CUP4SOIL –User Requirement Study User Survey –Workshop Which soil-related spatial information would be helpful for your work (derived/complex properties)? Same top three
CUP4SOIL –User Requirement Study User Survey –Resolution What is your preferred spatial resolution you are working on (in pixel sizes)? Finer resolutions are always desirable, but what are the coarsest reslutions that would still work for your use? (with accuracy matching resolution) Correct quantitative values necessary What accuracy level is still useful/required for your application given the specifications above? Spatial pattern should make sense, no absolute accuracy necessary
CUP4SOIL –User Requirement Study User Survey –Update frequency If it is not feasible or meaningful to make yearly or near-real time updates to the products, is a longer (5/10 years) update period still useful? How regularly would you like to get updates on the soil service products?
Data access Users Engagement Purpose: •Provide a set of data products for stakeholders to „play around“ and get first experiences •Development of show cases •Special emphasis on validation / accuracy / uncertainty of the products (more products in progress) •Explore the pros and cons of SOC maps from WorldSoils and CUP4SOIL and other sources (SoilGrids, Holisoils, EJP, JRC, ...)
Outlook Summary and future developments •Summary: •Innovative covariates produced from SCMaP intermediate products •Initial Soil parameters produced including the SCMaP covariates •Test about the best choice of covariates •Future developments: •Use of refined SCMap products •Uncertainty assessment for the soil properties •Evaluation of the products „spatial pattern agreement“ („How well does digital soil mapping represent soil geography “) •Comparison of the products with other products covering the same regional extent (Europe)
