Satellite Visible–Near Infrared Reflectance Correlates to Soil Nitrogen and Carbon Content in Three Fields of the Thessaly Plain (Greece)
Surface visible–near infrared (NIR) reflectance of bare soil by remote sensing devices has been used to infer topsoil properties such as organic matter, soil texture, water content, salinity, and crop residue cover. Spectral mapping of soil properties can be ultimately used as a tool for the impleme...
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Published in | Communications in Soil Science and Plant Analysis Vol. 44; no. 1-4; pp. 28 - 37 |
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Main Authors | , , , , , , , , , , |
Format | Journal Article Conference Proceeding |
Language | English |
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Taylor & Francis Group
2013
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Abstract | Surface visible–near infrared (NIR) reflectance of bare soil by remote sensing devices has been used to infer topsoil properties such as organic matter, soil texture, water content, salinity, and crop residue cover. Spectral mapping of soil properties can be ultimately used as a tool for the implementation of site-specific management practices at the field scale or for soil–landscape modeling at a regional scale. The accuracy of prediction of soil properties with satellite imagery is affected by conditions and properties of the soil surface, by radiometric and atmospheric effects, and by spatial and spectral resolutions. In this study, a high-resolution World View 2 image was used to map soil reflectance in three 10-ha fields of differing soil types and textures that were located in different sections of the east Thessaly Plain. Radiance data from four visible-NIR channels were extracted from the same coordinates that soil samples were taken at two soil depths within each field. Point radiance values were correlated to soil organic matter, total carbon (C) and nitrogen (N) contents, their isotopic composition, carbonate content, nitrate content, pH, electrical conductivity, and soil texture that were analyzed in the laboratory. Strong correlation coefficients emerged between green/NIR image reflectance and total soil N, organic matter, and carbonate content across the three fields in both soil depths. The greatest negative correlation coefficient (R² = 0.77) was obtained between satellite NIR reflectance and soil N content. More data are needed to verify these relationships, but the results indicated the potential of high-resolution satellite imagery to quantify within-field and regional-scale variability of soil N and C in the Thessaly Plain. |
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AbstractList | Surface visible–near infrared (NIR) reflectance of bare soil by remote sensing devices has been used to infer topsoil properties such as organic matter, soil texture, water content, salinity, and crop residue cover. Spectral mapping of soil properties can be ultimately used as a tool for the implementation of site-specific management practices at the field scale or for soil–landscape modeling at a regional scale. The accuracy of prediction of soil properties with satellite imagery is affected by conditions and properties of the soil surface, by radiometric and atmospheric effects, and by spatial and spectral resolutions. In this study, a high-resolution World View 2 image was used to map soil reflectance in three 10-ha fields of differing soil types and textures that were located in different sections of the east Thessaly Plain. Radiance data from four visible-NIR channels were extracted from the same coordinates that soil samples were taken at two soil depths within each field. Point radiance values were correlated to soil organic matter, total carbon (C) and nitrogen (N) contents, their isotopic composition, carbonate content, nitrate content, pH, electrical conductivity, and soil texture that were analyzed in the laboratory. Strong correlation coefficients emerged between green/NIR image reflectance and total soil N, organic matter, and carbonate content across the three fields in both soil depths. The greatest negative correlation coefficient (R² = 0.77) was obtained between satellite NIR reflectance and soil N content. More data are needed to verify these relationships, but the results indicated the potential of high-resolution satellite imagery to quantify within-field and regional-scale variability of soil N and C in the Thessaly Plain. Surface visible-near infrared (NIR) reflectance of bare soil by remote sensing devices has been used to infer topsoil properties such as organic matter, soil texture, water content, salinity, and crop residue cover. Spectral mapping of soil properties can be ultimately used as a tool for the implementation of site-specific management practices at the field scale or for soil-landscape modeling at a regional scale. The accuracy of prediction of soil properties with satellite imagery is affected by conditions and properties of the soil surface, by radiometric and atmospheric effects, and by spatial and spectral resolutions. In this study, a high-resolution World View 2 image was used to map soil reflectance in three 10-ha fields of differing soil types and textures that were located in different sections of the east Thessaly Plain. Radiance data from four visible-NIR channels were extracted from the same coordinates that soil samples were taken at two soil depths within each field. Point radiance values were correlated to soil organic matter, total carbon (C) and nitrogen (N) contents, their isotopic composition, carbonate content, nitrate content, pH, electrical conductivity, and soil texture that were analyzed in the laboratory. Strong correlation coefficients emerged between green/NIR image reflectance and total soil N, organic matter, and carbonate content across the three fields in both soil depths. The greatest negative correlation coefficient (R 2 = 0.77) was obtained between satellite NIR reflectance and soil N content. More data are needed to verify these relationships, but the results indicated the potential of high-resolution satellite imagery to quantify within-field and regional-scale variability of soil N and C in the Thessaly Plain. Surface visible-near infrared (NIR) reflectance of bare soil by remote sensing devices has been used to infer topsoil properties such as organic matter, soil texture, water content, salinity, and crop residue cover. Spectral mapping of soil properties can be ultimately used as a tool for the implementation of site-specific management practices at the field scale or for soil-landscape modeling at a regional scale. The accuracy of prediction of soil properties with satellite imagery is affected by conditions and properties of the soil surface, by radiometric and atmospheric effects, and by spatial and spectral resolutions. In this study, a high-resolution World View 2 image was used to map soil reflectance in three 10-ha fields of differing soil types and textures that were located in different sections of the east Thessaly Plain. Radiance data from four visible-NIR channels were extracted from the same coordinates that soil samples were taken at two soil depths within each field. Point radiance values were correlated to soil organic matter, total carbon (C) and nitrogen (N) contents, their isotopic composition, carbonate content, nitrate content, pH, electrical conductivity, and soil texture that were analyzed in the laboratory. Strong correlation coefficients emerged between green/NIR image reflectance and total soil N, organic matter, and carbonate content across the three fields in both soil depths. The greatest negative correlation coefficient (R2 = 0.77) was obtained between satellite NIR reflectance and soil N content. More data are needed to verify these relationships, but the results indicated the potential of high-resolution satellite imagery to quantify within-field and regional-scale variability of soil N and C in the Thessaly Plain. [PUBLICATION ABSTRACT] |
Author | Tsadilas, Christos Tsitouras, Alexandros Chroni, Christina Dalezios, Nikolaos Evangelou, Lefteris Dimogiannis, Dimitris Stamatiadis, Stamatis Blanta, Anna Tsantila, Eleftheria Christophides, Calliopi Samaras, Vasilis |
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Keywords | stable isotopes Organic matter soil texture Satellite Nitrogen soil organic matter Texture Depth Remote sensing Precision agriculture Near infrared radiation soil depth Soils Plain Carbon content Calcium carbonate Visible radiation spacial variability site-specific management Mediterranean region Isotopes Reflectance |
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Snippet | Surface visible–near infrared (NIR) reflectance of bare soil by remote sensing devices has been used to infer topsoil properties such as organic matter, soil... Surface visible-near infrared (NIR) reflectance of bare soil by remote sensing devices has been used to infer topsoil properties such as organic matter, soil... |
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SubjectTerms | Agronomy. Soil science and plant productions Biological and medical sciences Calcium carbonate Carbon Chemical, physicochemical, biochemical and biological properties correlation crop residues electrical conductivity Fundamental and applied biological sciences. Psychology Herbivores nitrates Nitrogen nitrogen content Organic matter Physics, chemistry, biochemistry and biology of agricultural and forest soils reflectance Remote sensing Satellites site-specific management soil depth soil heterogeneity soil organic matter soil sampling Soil science Soil sciences soil surveys soil texture soil types spacial variability stable isotopes Tillage topsoil water content |
Title | Satellite Visible–Near Infrared Reflectance Correlates to Soil Nitrogen and Carbon Content in Three Fields of the Thessaly Plain (Greece) |
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