Exploitation of spectroscopy in proximal and remote sensing for the spatial prediction of soil properties with an emphasis on soil organic carbon content

James Kobina Mensah Biney

Disertační práce

Combining different remote and proximal sensing technologies for prediction of organic carbon content in soils

Anotace:

The publications and manuscripts presented in this thesis constitute research activities from 2017 to 2022, comprising several sections that are linked to the main aim of this work. That is to improve the estimates of soil properties, especially SOC, with the data set obtained from three well-known platforms [spectroscopy (in-situ), satellite (Sentinel-2) and unmanned aircraft systems (UAS)], using several modelling techniques and pre-treatment algorithms. Knowledge of soil organic matter (SOM)/SOC quality in the soil environment is an essential factor for the assessment of the environmental balance of organic carbon stocks. Additionally, the emersion of proximal and remote sensing techniques has identified mapping and monitoring of soil as essential applications. The entire thesis was carried out under the supervision of the Department of Soil Science and Soil Protection at the Czech University of Life Sciences (CZU), Prague. Grant providers and co-authors are acknowledged in the respective publications. Moreover, the thesis investigates the possibility of combining in-situ, UAS, and Sentinel-2 (S2) into a single dataset using data fusion approach to estimate SOC in two agricultural fields in the Czech Republic that are low in organic content. To the best of our knowledge, no other study has explored this, possibly because of its complexity. The manuscript dealing with this research is currently under review. In the context of this Ph.D. thesis, the above-mentioned approach did improve the estimate of SOC in the study field of Nová Ves nad Popelkou. This work was a follow-up to a previous work (Biney et al., 20201) in which the three platforms were in-depth compared using their individual data sets. The current work can help encourage other researchers to also focus on fields with low organic carbon content with the sole goal of improving SOC estimates because of its multiple benefits to the environment. The thesis is composed from the following papers: Biney, J. K. M., Borůvka, L., Chapman Agyeman, P., Němeček, K., and Klement, A. (2020). Comparison of field and laboratory wet soil spectra in the Vis-NIR range for soil organic carbon prediction in the absence of laboratory dry measurements. Remote Sensing, 12(18), 3082. Biney, J. K. M., Blöcher, J. R., Borůvka, L., and Vašát, R. (2021). Does the limited use of orthogonal signal correction pre-treatment approach to improve the prediction accuracy of soil organic carbon need attention? Geoderma, 388, 114945. Biney, J. K. M., Saberioon, M., Borůvka, L., Houška, J., Vašát, R., Chapman Agyeman, P., Coblinski, J. A., and Klement, A. (2021). Exploring the suitability of UAS-based multispectral images for estimating soil organic carbon: Comparison with proximal soil sensing and spaceborne imagery. Remote Sensing, 13(2), 308. Biney, J. K. M., Vašát, R., Blöcher, J. R., Borůvka, L., and Němeček, K. (2021). Using an ensemble model coupled with portable X-ray fluorescence and visible near-infrared spectroscopy to explore the viability of mapping and estimating arsenic in an agricultural soil. Science of the Total Environment, 151805. Biney, J. K. M., Vašát, R., Bell, S, M., Kebonye, N. M., Aleš, K., John, K., and Borůvka. L. Prediction of topsoil organic carbon content with Sentinel-2 imagery and spectroscopic measurements under different conditions using an ensemble model approach with multiple pre-treatment combinations. Soil and Tillage Research (Under revision) Biney, J. K. M., Borůvka, L., Klement, A., Houška, J., Červenka, J., Kebonye, N. M., and Salazar, D. U. Verifying the impact of fusion high-resolution simulated in-situ spectroscopy, Sentinel-2, and unmanned aircraft systems data into a single dataset to estimate soil organic carbon content in low-carbon agricultural fields. Catena (Under review). Additionally, other papers were added with no detailed description or discussion. These studies were either linked with some of the study aims or were done

Anotace:

to improve the estimation of SOC in the study field. Biney, J. K. M., 2022. Verifying the predictive performance for soil organic carbon when employing field Vis-NIR spectroscopy and satellite imagery obtained using two different sampling methods. Computers and Electronics in Agriculture, 194, 106796. Demattê, J.A.M., Paiva, A.F.d.S., Poppiel, R.R., Rosin, N.A., Ruiz, L.F.C., Mello, F.A.d.O., Minasny, B., Grunwald, S., Ge, Y., Ben Dor, E., Gholizadeh, A., Gomez, C., Chabrillat, S., Francos, N., Ayoubi, S., Fiantis, D., Biney, J.K.M., Wang, C., Belal, A., Naimi, S., Hafshejani, N.A., Bellinaso, H., Moura-Bueno, J.M., and Silvero, N.E.Q. (2022). The Brazilian Soil Spectral Service (BraSpecS): A user-friendly system for global soil spectra communication. Remote Sensing, 14, 740.

Abstract:

The publications and manuscripts presented in this thesis constitute research activities from 2017 to 2022, comprising several sections that are linked to the main aim of this work. That is to improve the estimates of soil properties, especially SOC, with the data set obtained from three well-known platforms [spectroscopy (in-situ), satellite (Sentinel-2) and unmanned aircraft systems (UAS)], using several modelling techniques and pre-treatment algorithms. Knowledge of soil organic matter (SOM)/SOC quality in the soil environment is an essential factor for the assessment of the environmental balance of organic carbon stocks. Additionally, the emersion of proximal and remote sensing techniques has identified mapping and monitoring of soil as essential applications. The entire thesis was carried out under the supervision of the Department of Soil Science and Soil Protection at the Czech University of Life Sciences (CZU), Prague. Grant providers and co-authors are acknowledged in the respective publications. Moreover, the thesis investigates the possibility of combining in-situ, UAS, and Sentinel-2 (S2) into a single dataset using data fusion approach to estimate SOC in two agricultural fields in the Czech Republic that are low in organic content. To the best of our knowledge, no other study has explored this, possibly because of its complexity. The manuscript dealing with this research is currently under review. In the context of this Ph.D. thesis, the above-mentioned approach did improve the estimate of SOC in the study field of Nová Ves nad Popelkou. This work was a follow-up to a previous work (Biney et al., 20201) in which the three platforms were in-depth compared using their individual data sets. The current work can help encourage other researchers to also focus on fields with low organic carbon content with the sole goal of improving SOC estimates because of its multiple benefits to the environment. The thesis is composed from the following papers: Biney, J. K. M., Borůvka, L., Chapman Agyeman, P., Němeček, K., and Klement, A. (2020). Comparison of field and laboratory wet soil spectra in the Vis-NIR range for soil organic carbon prediction in the absence of laboratory dry measurements. Remote Sensing, 12(18), 3082. Biney, J. K. M., Blöcher, J. R., Borůvka, L., and Vašát, R. (2021). Does the limited use of orthogonal signal correction pre-treatment approach to improve the prediction accuracy of soil organic carbon need attention? Geoderma, 388, 114945. Biney, J. K. M., Saberioon, M., Borůvka, L., Houška, J., Vašát, R., Chapman Agyeman, P., Coblinski, J. A., and Klement, A. (2021). Exploring the suitability of UAS-based multispectral images for estimating soil organic carbon: Comparison with proximal soil sensing and spaceborne imagery. Remote Sensing, 13(2), 308. Biney, J. K. M., Vašát, R., Blöcher, J. R., Borůvka, L., and Němeček, K. (2021). Using an ensemble model coupled with portable X-ray fluorescence and visible near-infrared spectroscopy to explore the viability of mapping and estimating arsenic in an agricultural soil. Science of the Total Environment, 151805. Biney, J. K. M., Vašát, R., Bell, S, M., Kebonye, N. M., Aleš, K., John, K., and Borůvka. L. Prediction of topsoil organic carbon content with Sentinel-2 imagery and spectroscopic measurements under different conditions using an ensemble model approach with multiple pre-treatment combinations. Soil and Tillage Research (Under revision) Biney, J. K. M., Borůvka, L., Klement, A., Houška, J., Červenka, J., Kebonye, N. M., and Salazar, D. U. Verifying the impact of fusion high-resolution simulated in-situ spectroscopy, Sentinel-2, and unmanned aircraft systems data into a single dataset to estimate soil organic carbon content in low-carbon agricultural fields. Catena (Under review). Additionally, other papers were added with no detailed description or discussion. These studies were either linked with some of the study aims or were done

Abstract:

to improve the estimation of SOC in the study field. Biney, J. K. M., 2022. Verifying the predictive performance for soil organic carbon when employing field Vis-NIR spectroscopy and satellite imagery obtained using two different sampling methods. Computers and Electronics in Agriculture, 194, 106796. Demattê, J.A.M., Paiva, A.F.d.S., Poppiel, R.R., Rosin, N.A., Ruiz, L.F.C., Mello, F.A.d.O., Minasny, B., Grunwald, S., Ge, Y., Ben Dor, E., Gholizadeh, A., Gomez, C., Chabrillat, S., Francos, N., Ayoubi, S., Fiantis, D., Biney, J.K.M., Wang, C., Belal, A., Naimi, S., Hafshejani, N.A., Bellinaso, H., Moura-Bueno, J.M., and Silvero, N.E.Q. (2022). The Brazilian Soil Spectral Service (BraSpecS): A user-friendly system for global soil spectra communication. Remote Sensing, 14, 740.

Klíčová slova

Proximal and remote Sensing, Agricultural soil, Digital soil mapping, Soil organic carbon, Spectroscopy

Keywords

Proximal and remote Sensing, Soil organic carbon, Spectroscopy, Digital soil mapping, Agricultural soil

Jazyk práce: angličtina

Datum vytvoření / odevzdání či podání práce: 28. 2. 2022

Obhajoba závěrečné práce

• Vedoucí: prof. Dr. Ing. Luboš Borůvka

Česká zemědělská univerzita v Praze

Fakulta agrobiologie, potravinových a přírodních zdrojů

Doktorský studijní program / obor:
Agricultural Specialization / Exploitation and Conservation of Natural Resources