2021
DOI: 10.3390/land10010063
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Evaluation of a Micro-Electro Mechanical Systems Spectral Sensor for Soil Properties Estimation

Abstract: Soil properties estimation with the use of reflectance spectroscopy has met major advances over the last decades. Their non-destructive nature and their high accuracy capacity enabled a breakthrough in the efficiency of performing soil analysis against conventional laboratory techniques. As the need for rapid, low cost, and accurate soil properties’ estimations increases, micro electro mechanical systems (MEMS) have been introduced and are becoming applicable for informed decision making in various domains. Th… Show more

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Cited by 13 publications
(12 citation statements)
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References 65 publications
(80 reference statements)
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“…This could possibly be due to the data being randomly split between calibration and validation only once, while taking care that the similar range for soil property quantities remained common between the calibration and validation datasets ( Figure 5 ). However this possibility was not tested and could be tested in future by splitting the data many times and modeling the data using the five-fold cross-validation technique [ 47 ].…”
Section: Resultsmentioning
confidence: 99%
See 2 more Smart Citations
“…This could possibly be due to the data being randomly split between calibration and validation only once, while taking care that the similar range for soil property quantities remained common between the calibration and validation datasets ( Figure 5 ). However this possibility was not tested and could be tested in future by splitting the data many times and modeling the data using the five-fold cross-validation technique [ 47 ].…”
Section: Resultsmentioning
confidence: 99%
“…The next step of this research would be to assess the portable mid-IR and vis-NIR soil spectra obtained under field conditions and further eliminate the environmental and systematic factors [ 44 , 63 ] affecting both soil spectra in a similar way to [ 46 , 47 , 72 ]. In addition, a variety of calibration models (ranging from simple to complex), e.g., partial least squares regression (PLSR) [ 1 , 73 , 74 ], principal component regression (PCR) [ 7 , 75 ], artificial neural networks (ANN) [ 76 ], convolution neural networks (CNN) [ 77 , 78 , 79 ], support vector machines (SVM) [ 80 ], and deep learning [ 81 , 82 , 83 , 84 ], to name a few, could be studied.…”
Section: Resultsmentioning
confidence: 99%
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“…Furthermore, compact size and portable sensors based on microelectromechanical systems (MEMS) are undergoing a significant shift [103], enabling among other applications the development of new innovative VNIR-SWIR sensing applications for soil properties or real time variable rate soil sensors [104]. In this context, a set of novel and low-cost spectral acquisition systems has been explored in conjunction with non-linear regression algorithms for predicting soil properties [105][106][107], mainly under controlled illumination conditions in the laboratory. Among other advances, augmented reality now also appears in soil mapping applications, where the locations for sampling are generated automatically, and the user is guided by special glasses to collect the samples representing management zones [108].…”
Section: Integration Of In Situ Sensing Systems and Citizen Science Datamentioning
confidence: 99%
“…Obviously, spectrometers play an important role in spectral analysis [ 10 , 14 , 15 , 16 , 17 , 18 , 19 ]. During the past three years, many studies have investigated the influences of spectrometers on the spectral analysis of SOC ( Table 1 ).…”
Section: Introductionmentioning
confidence: 99%