A Spectral Transfer Function to Harmonize Existing Soil Spectral Libraries Generated by Different Protocols
Soil spectral libraries (SSLs) are important big-data archives (spectra associated with soil properties) that are analyzed via machine-learning algorithms to estimate soil attributes. Since different spectral measurement protocols are applied when constructing SSLs, it is necessary to examine harmon...
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Applied and Environmental Soil Science |
| Online Access: | http://dx.doi.org/10.1155/2023/4155390 |
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| author | Nicolas Francos Daniela Heller-Pearlshtien José A. M. Demattê Bas Van Wesemael Robert Milewski Sabine Chabrillat Nikolaos Tziolas Adrian Sanz Diaz María Julia Yagüe Ballester Asa Gholizadeh Eyal Ben-Dor |
| author_facet | Nicolas Francos Daniela Heller-Pearlshtien José A. M. Demattê Bas Van Wesemael Robert Milewski Sabine Chabrillat Nikolaos Tziolas Adrian Sanz Diaz María Julia Yagüe Ballester Asa Gholizadeh Eyal Ben-Dor |
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| collection | DOAJ |
| description | Soil spectral libraries (SSLs) are important big-data archives (spectra associated with soil properties) that are analyzed via machine-learning algorithms to estimate soil attributes. Since different spectral measurement protocols are applied when constructing SSLs, it is necessary to examine harmonization techniques to merge the data. In recent years, several techniques for harmonization have been proposed, among which the internal soil standard (ISS) protocol is the most largely applied and has demonstrated its capacity to rectify systematic effects during spectral measurements. Here, we postulate that a spectral transfer function (TF) can be extracted between existing (old) SSLs if a subset of samples from two (or more) different SSLs are remeasured using the ISS protocol. A machine-learning TF strategy was developed, assembling random forest (RF) spectral-based models to predict the ISS spectral condition using soil samples from two existing SSLs. These SSLs had already been measured using different protocols without any ISS treatment the Brazilian (BSSL, generated in 2019) and the European (LUCAS, generated in 2009–2012) SSLs. To verify the TF’s ability to improve the spectral assessment of soil attributes after harmonizing the different SSLs’ protocols, RF spectral-based models for estimating organic carbon (OC) in soil were developed. The results showed high spectral similarities between the ISS and the ISS–TF spectral observations, indicating that post-ISS rectification is possible. Furthermore, after merging the SSLs with the TFs, the spectral-based assessment of OC was considerably improved, from R2 = 0.61, RMSE (g/kg) = 12.46 to R2 = 0.69, RMSE (g/kg) = 11.13. Given our results, this paper enhances the importance of soil spectroscopy by contributing to analyses in remote sensing, soil surveys, and digital soil mapping. |
| format | Article |
| id | doaj-art-cfc8c5a02b104b24bdeccdd722280ad9 |
| institution | Kabale University |
| issn | 1687-7675 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied and Environmental Soil Science |
| spelling | doaj-art-cfc8c5a02b104b24bdeccdd722280ad92025-02-03T06:08:39ZengWileyApplied and Environmental Soil Science1687-76752023-01-01202310.1155/2023/4155390A Spectral Transfer Function to Harmonize Existing Soil Spectral Libraries Generated by Different ProtocolsNicolas Francos0Daniela Heller-Pearlshtien1José A. M. Demattê2Bas Van Wesemael3Robert Milewski4Sabine Chabrillat5Nikolaos Tziolas6Adrian Sanz Diaz7María Julia Yagüe Ballester8Asa Gholizadeh9Eyal Ben-Dor10The Remote Sensing LaboratoryThe Remote Sensing LaboratoryDepartment of Soil ScienceEarth and Life InstituteHelmholtz Zentrum Potsdam Deutsches GeoForschungsZentrum (GFZ)Helmholtz Zentrum Potsdam Deutsches GeoForschungsZentrum (GFZ)School of AgricultureGMV Aerospace and DefenceGMV Aerospace and DefenceDepartment of Soil Science and Soil ProtectionThe Remote Sensing LaboratorySoil spectral libraries (SSLs) are important big-data archives (spectra associated with soil properties) that are analyzed via machine-learning algorithms to estimate soil attributes. Since different spectral measurement protocols are applied when constructing SSLs, it is necessary to examine harmonization techniques to merge the data. In recent years, several techniques for harmonization have been proposed, among which the internal soil standard (ISS) protocol is the most largely applied and has demonstrated its capacity to rectify systematic effects during spectral measurements. Here, we postulate that a spectral transfer function (TF) can be extracted between existing (old) SSLs if a subset of samples from two (or more) different SSLs are remeasured using the ISS protocol. A machine-learning TF strategy was developed, assembling random forest (RF) spectral-based models to predict the ISS spectral condition using soil samples from two existing SSLs. These SSLs had already been measured using different protocols without any ISS treatment the Brazilian (BSSL, generated in 2019) and the European (LUCAS, generated in 2009–2012) SSLs. To verify the TF’s ability to improve the spectral assessment of soil attributes after harmonizing the different SSLs’ protocols, RF spectral-based models for estimating organic carbon (OC) in soil were developed. The results showed high spectral similarities between the ISS and the ISS–TF spectral observations, indicating that post-ISS rectification is possible. Furthermore, after merging the SSLs with the TFs, the spectral-based assessment of OC was considerably improved, from R2 = 0.61, RMSE (g/kg) = 12.46 to R2 = 0.69, RMSE (g/kg) = 11.13. Given our results, this paper enhances the importance of soil spectroscopy by contributing to analyses in remote sensing, soil surveys, and digital soil mapping.http://dx.doi.org/10.1155/2023/4155390 |
| spellingShingle | Nicolas Francos Daniela Heller-Pearlshtien José A. M. Demattê Bas Van Wesemael Robert Milewski Sabine Chabrillat Nikolaos Tziolas Adrian Sanz Diaz María Julia Yagüe Ballester Asa Gholizadeh Eyal Ben-Dor A Spectral Transfer Function to Harmonize Existing Soil Spectral Libraries Generated by Different Protocols Applied and Environmental Soil Science |
| title | A Spectral Transfer Function to Harmonize Existing Soil Spectral Libraries Generated by Different Protocols |
| title_full | A Spectral Transfer Function to Harmonize Existing Soil Spectral Libraries Generated by Different Protocols |
| title_fullStr | A Spectral Transfer Function to Harmonize Existing Soil Spectral Libraries Generated by Different Protocols |
| title_full_unstemmed | A Spectral Transfer Function to Harmonize Existing Soil Spectral Libraries Generated by Different Protocols |
| title_short | A Spectral Transfer Function to Harmonize Existing Soil Spectral Libraries Generated by Different Protocols |
| title_sort | spectral transfer function to harmonize existing soil spectral libraries generated by different protocols |
| url | http://dx.doi.org/10.1155/2023/4155390 |
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