Synergistic use of proximally sensed and time series remotely sensed imagery to map soil sodicity
COMPUTERS AND ELECTRONICS IN AGRICULTURE(2024)
Abstract
Soil sodicity can cause crusting in the topsoil which impedes water infiltration, and erosion in the subsoil owing to instability. These can impose constraints to sugarcane growth in the form of reduced plant emergence and root extension. To improve soil capability, a map of topsoil (0-0.15 m) exchangeable sodium percentage (ESP) can be used to determine the amount of gypsum required to ameliorate soil condition. Herein, a digital soil mapping (DSM) approach was used to map top- and subsoil (0.3-0.45 m) ESP. To do this, we first examined prediction agreement of a calibration model between digital data and ESP, first comparing individual use of remotely sensed time series imagery (i.e., Sentinel-2 and Landsat-8) or proximal sensor (i.e., electromagnetic [EM] induction and gamma-ray [gamma-ray]) data. To account for the large amount of remote data we combined them using principal component analysis (PCA). We also investigated combining digital data using a backward feature elimination - BFE), along with minimum calibration sample size (n = 150-10) determined. Prediction agreement (Lin's concordance correlation coefficient - LCCC) and accuracy (ratio of performance to deviation - RPD) were assessed using an independent validation dataset (n = 32). To predict topsoil ESP, PCs from Landsat-8 provided excellent (LCCC = 0.90) agreement and very good (RPD = 2.26) accuracy, followed by Sentintel-2 (0.86, 1.75), gamma-ray (0.83, 1.84) and EM (0.78, 1.78), with subsoil ESP also excellent (0.90) and very good (2.51) using Landsat8, however; Sentintel-2 outperformed the others with even better results (0.95, 3.24), followed by EM (0.78, 1.76) and gamma-ray (0.73, 1.54). Moreover, slightly better results were achieved when EM, gamma-ray, and PCs of Sentinel2 were combined, with top- and subsoil ESP agreement (0.93 and 0.94, respectively) and accuracy (2.53 and 3.14, respectively) excellent. A minimum of 40 sampling sites were required (1.2 sites ha- 1) for the good prediction agreement and accuracy of top- (0.85, 2.13) and subsoil (0.84, 1.90) ESP. Based on the best results, DSM of ESP was made to recommend gypsum application rates to ameliorate sodic soils according to the Six-Easy-Steps Management Guidelines. The northern fields required variable rates (5, 7.5, and 10 t ha- 1) of gypsum, whereas the southern fields would not require gypsum.
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Key words
Proximal soil sensing,Landsat-8,Time series,Dimensionality reduction,PCA,Exchangeable sodium percentage,Digital soil mapping,Sentinel-2
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