Use of multispectral remote sensing data for predicting topsoil organic matter content : the case of Doulou watershed
Prédiction cartographique de la matière organique du sol par télédétection multispectrale.
DOI:
https://doi.org/10.64707/revstsna.v44i2.1987Keywords:
Soil organic matter, Spectral band, Cartographic predictor, Multiple linear regressionAbstract
The importance of organic matter for agricultural soils in Burkina Faso to increase their fertility and productivity requires an assessment of soil organic matter needs to rationalize inputs and optimize producers' efforts. Through field measurements of soil organic matter in the Doulou watershed, in Boulkiemdé province, Nando region, carried out from December 2017 to February 2018, and spectral reflectance data from the Landsat 8 OLI sensor, we develop a multiple linear regression model for the mapping prediction of topsoil organic matter content. Only four Landsat image acquisition dates are available for this period. According to a grouping into three groups according to the measurement dates carried out, January 10 and 11 (12 observations), January 10, 11 and 12 (21 observations), then the entire period (49 observations), we observe a variable correlation in the case of 0.942, 0.859, or 0.703, respectively; the explanatory variance of the model is 0.888, 0.739 and 0.495 in the respective case. The corresponding standard deviations or residuals of these models are 0.211, 0.205 and 0.279 respectively. These results show that the cartographic predictor of organic matter content is an existing model, very real, but for it to be very precise, good synchronization between the field measurement dates and the satellite image acquisition dates is required.
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