Evaluation of Airborne HySpex and Spaceborne PRISMA Hyperspectral Remote Sensing Data for Soil Organic Matter and Carbonates Estimation

Remote sensing and soil spectroscopy applications are valuable techniques for soil property estimation. Soil organic matter (SOM) and calcium carbonate are important factors in soil quality, and although organic matter is well studied, calcium carbonates require more investigation. In this study, we validated the performance of laboratory soil spectroscopy for estimating the aforementioned properties with referenced in situ data. We also examined the performance of imaging spectroscopy sensors, such as the airborne HySpex and the spaceborne PRISMA. For this purpose, we applied four commonly used machine learning algorithms and six preprocessing methods for the evaluation of the best fitting algorithm.. The study took place over crop areas of Amyntaio in Northern Greece, where extensive soil sampling was conducted. This is an area with a very variable mineralogical environment (from lignite mine to mountainous area). The SOM results were very good at the laboratory scale and for both remote sensing sensors with R2 = 0.79 for HySpex and R2 = 0.76 for PRISMA. Regarding the calcium carbonate estimations, the remote sensing accuracy was R2 = 0.82 for HySpex and R2 = 0.36 for PRISMA. PRISMA was still in the commissioning phase at the time of the study, and therefore, the acquired image did not cover the whole study area. Accuracies for calcium carbonates may be lower due to the smaller sample size used for the modeling procedure. The results show the potential for using quantitative predictions of SOM and the carbonate content based on soil and imaging spectroscopy at the air and spaceborne scales and for future applications using larger datasets

Evaluation of Airborne HySpex and Spaceborne PRISMA Hyperspectral Remote Sensing Data for Soil Organic Matter and Carbonates Estimation

Remote sensing and soil spectroscopy applications are valuable techniques for soil property estimation. Soil organic matter (SOM) and calcium carbonate are important factors in soil quality, and although organic matter is well studied, calcium carbonates require more investigation. In this study, we validated the performance of laboratory soil spectroscopy for estimating the aforementioned properties with referenced in situ data. We also examined the performance of imaging spectroscopy sensors, such as the airborne HySpex and the spaceborne PRISMA. For this purpose, we applied four commonly used machine learning algorithms and six preprocessing methods for the evaluation of the best fitting algorithm.. The study took place over crop areas of Amyntaio in Northern Greece, where extensive soil sampling was conducted. This is an area with a very variable mineralogical environment (from lignite mine to mountainous area). The SOM results were very good at the laboratory scale and for both remote sensing sensors with R2 = 0.79 for HySpex and R2 = 0.76 for PRISMA. Regarding the calcium carbonate estimations, the remote sensing accuracy was R2 = 0.82 for HySpex and R2 = 0.36 for PRISMA. PRISMA was still in the commissioning phase at the time of the study, and therefore, the acquired image did not cover the whole study area. Accuracies for calcium carbonates may be lower due to the smaller sample size used for the modeling procedure. The results show the potential for using quantitative predictions of SOM and the carbonate content based on soil and imaging spectroscopy at the air and spaceborne scales and for future applications using larger datasets

Πρόβλεψη της εδαφικής οργανικής ουσίας λαμβάνοντας υπόψη την περιεκτικότητα σε υγρασία χρησιμοποιώντας φασματικά δεδομένα και τεχνικές μηχανικής μάθησης

This dissertation explores the potential of VNIR-SWIR spectroscopy as a cost-effective method for Soil Organic Matter (SOM) prediction in Mediterranean soils with low Organic Matter (OM) content. The research emphasizes the need for robust spectral libraries representing various soil strata and highlights the impact of different multivariate methods and spectral pre-processing techniques on SOM prediction accuracy. More specifically it was found that for laboratory measurements the results give high accuracies irrespective of the multivariate method used. However the preprocessing method plays an important role mainly for machine learning techniques rather than PLSR which provident more constant results with smaller deviations. The study also underscores the significant influence of soil moisture on spectral data and SOM predictions. It is suggested employing separate calibration models for different moisture levels and incorporating appropriate correction techniques to enhance prediction accuracy. It became evident that models that were developed from air dried and sieved samples could not be utilized to predict soil samples with moisture contents even if SM was relative low. The second part of the thesis is dedicated to SOM predictions utilizing hyperspectral sensors both airborne (HySpex) and the recently launched PRISMA satellite sensor. Results were very promising for both sensors with HySpex showing slightly better prediction accuracies. Regarding the model validation HySpex had more consistent results irrespective of the method used. On the other hand PRISMA showed better and more consistent results with the use of PLSR and Cubist. Furthermore, the study explores the potential of auxiliary variables from satellite radar data, (Sentinel_1) that marginally improved the models’ accuracies emphasizing the importance of a detailed analysis and larger datasets for their effective incorporation into soil property prediction models. In conclusion, the research suggests meticulous calibration, validation, and consideration of site-specific conditions in utilizing soil spectroscopy for accurate and reliable SOM predictions. Additionally, the study emphasizes the role of earth observation data, in understanding the spatial distribution of SOM, offering valuable insights for sustainable land management and addressing global challenges such as climate change and food security. Future research directions include evaluating the proposed approaches with larger datasets, incorporating additional soil-related variables, development of common protocols and exploring detailed soil mapping for agricultural monitoring.Η διατριβή διερευνά τις δυνατότητες της φασματοσκοπίας ανάκλασης εδάφους στο VNIR-SWIR φασματικό εύρος ως μια οικονομικά αποδοτική μέθοδο για την πρόβλεψη της οργανικής ουσίας του εδάφους (ΟΟ) σε εδάφη της Μεσογείου με χαμηλή περιεκτικότητα σε ΟΟ. Η έρευνα υπογραμμίζει την ανάγκη για τη δημιουργία μεγάλων και αξιόπιστων φασματικών βιβλιοθηκών που αντιπροσωπεύουν διάφορα εδάφη και τονίζει τον αντίκτυπο των διαφορετικών πολυμεταβλητών μεθόδων και τεχνικών φασματικής προ επεξεργασίας στην ακρίβεια πρόβλεψης της ΟΟ. Πιο συγκεκριμένα, διαπιστώθηκε ότι για τις εργαστηριακές μετρήσεις που πραγματοποιούνται σε εργαστηριακό επίπεδο τα αποτελέσματα δίνουν υψηλές ακρίβειες ανεξάρτητα από την μέθοδο που χρησιμοποιείται. Ωστόσο, η μέθοδος προ επεξεργασίας παίζει σημαντικό ρόλο κυρίως για τις τεχνικές μηχανικής μάθησης παρά για την μέθοδο των ελαχίστων τετραγώνων PLSR που παρέχει πιο σταθερά αποτελέσματα με μικρότερες αποκλίσεις στην ακρίβεια. Υπογραμμίζεται επίσης η σημαντική επίδραση της υγρασίας του εδάφους στα φασματικά δεδομένα και τις προβλέψεις ΟΟ. Προτείνεται η χρήση ξεχωριστών μοντέλων βαθμονόμησης για διαφορετικά επίπεδα υγρασίας και η ενσωμάτωση κατάλληλων τεχνικών διόρθωσης για την ενίσχυση της ακρίβειας πρόβλεψης. Έγινε προφανές ότι τα μοντέλα που αναπτύχθηκαν από δείγματα αεροξηρανθέντα και κοσκινισμένα δεν μπορούσαν να χρησιμοποιηθούν για την πρόβλεψη δειγμάτων εδάφους με περιεκτικότητα σε υγρασία, ακόμη και αν η υγρασία ήταν σχετικά χαμηλή. Το δεύτερο μέρος της διατριβής είναι αφιερωμένο στις προβλέψεις της ΟΟ με την χρήση υπερφασματικών αισθητήρων προσαρτημένους τόσο σε αεροπλάνα (HySpex) όσο και τον πιο πρόσφατο δορυφορικό αισθητήρα PRISMA. Τα αποτελέσματα ήταν πολλά υποσχόμενα και για τους δύο αισθητήρες με το HySpex να δείχνει ελαφρώς καλύτερες ακρίβειες πρόβλεψης. Όσον αφορά την επικύρωση του μοντέλου, το HySpex είχε πιο συνεπή αποτελέσματα ανεξάρτητα από τη μέθοδο που χρησιμοποιήθηκε. Από την άλλη ο PRISMA έδειξε καλύτερα και πιο συνεπή αποτελέσματα με τη χρήση του PLSR και του Cubist. Επιπλέον, η μελέτη διερεύνησε την προοπτική της χρήσης βοηθητικών μεταβλητών από δεδομένα ραντάρ, (Sentinel_1) που βελτίωσαν οριακά την ακρίβεια των μοντέλων, τονίζοντας τη σημασία μιας λεπτομερούς ανάλυσης και μεγαλύτερων συνόλων δεδομένων για την αποτελεσματική ενσωμάτωσή τους σε μοντέλα πρόβλεψης εδαφικών παραμέτρων. Συμπερασματικά, η διατριβή αυτή συνηγορεί υπέρ της σχολαστικής βαθμονόμησης, επικύρωσης και μελέτης των συνθηκών κάθε τοποθεσίας κατά τη χρήση της φασματοσκοπίας εδάφους για ακριβείς και αξιόπιστες προβλέψεις της ΟΟ. Επιπλέον, τονίζεται ο ρόλος των δεδομένων παρατήρησης γης, στην κατανόηση της χωρικής κατανομής της ΟΟ, προσφέροντας πολύτιμες γνώσεις για τη βιώσιμη διαχείριση της γης και την αντιμετώπιση των παγκόσμιων προκλήσεων όπως η κλιματική αλλαγή και η επισιτιστική ασφάλεια. Οι μελλοντικές κατευθύνσεις για περαιτέρω έρευνας περιλαμβάνουν την αξιολόγηση των προτεινόμενων προσεγγίσεων με μεγαλύτερα σύνολα δεδομένων, την ενσωμάτωση πρόσθετων μεταβλητών που σχετίζονται με το έδαφος, την ανάπτυξη κοινών πρωτοκόλλων και τη διερεύνηση λεπτομερούς χαρτογράφησης του εδάφους για γεωργική παρακολούθηση

Evaluation of a Micro-Electro Mechanical Systems Spectral Sensor for Soil Properties Estimation

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. This work presents the assessment of a MEMS sensor (1750–2150 nm) in estimating clay and soil organic carbon (SOC) contents. The sensor was first tested under various experimental setups (different working distances and light intensities) through its similarity assessment (Spectral Angle Mapper) to the measurements of a spectroradiometer of the full 350–2500 nm range that was used as reference. MEMS performance was evaluated over spectra measured from 102 samples in laboratory conditions. Models’ calibrations were performed using random forest (RF) and partial least squares regression (PLSR). The results provide insights that MEMS could be employed for soil properties estimation, since the RF model demonstrated solid performance over both clay (R2 = 0.85) and SOC (R2 = 0.80). These findings pave the way for supporting daily agriculture applications and land related policies through the exploration of a wider set of soil properties

The Effects of Dexmedetomidine on Children Undergoing Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis

Background: Magnetic Resonance Imaging (MRI) is a valuable diagnostic tool but often requires sedation to complete, especially in children. Dexmedetomidine (DEX) is an a2 agonist, for which there are experimental findings that support its potential neuroprotective effects. Given the potential risks of anesthetic drugs, we ran this study to examine DEX’s effectiveness and cardiopulmonary safety as a sedative drug for children undergoing MRI. Material and Methods: Systematic research was conducted in PubMed, Google Scholar, Scopus and Cochrane databases for randomized controlled trials published between 2010 and 6th/2022 and involving children undergoing MRI who received DEX as sedative medication. The records which met the including criteria, after indexing via the PRISMA chart and assessing for bias, were processed, and a meta-analysis was carried out with the random effects method. Results: Thirteen studies were included. Out of 6204 measurements obtained, in 4626, it was planned for the participants to only receive DEX (measure group) as an anesthetic drug throughout the procedure. The participants’ mean age was 57 months (Ι2 = 4%, τ2 = 0.5317, p = 0.40). A total of 5.6% (95% CI: 0.6–14.1%, I2 = 98%, p 2 = 93%, τ2 = 0.0454, p 2 = 81%, τ2 = 0.0107, p 2 = 92%, p 2 = 84%, p 2 = 89%, p 2 = 95%, p 2 = 68%, p < 0.01). There was no statistically significant incidence in respiratory rate decrease (comparing the children who received DEX to their baseline). Five cases of vomiting and one of apnea were recorded. Conclusions: Given that DEX seems to be an effective as well as respiratory and hemodynamically safe drug, it may be a future spotlight in (pediatric) sedation for imaging procedures such as MRI

Remote Sensing Techniques for Soil Organic Carbon Estimation: A Review

Towards the need for sustainable development, remote sensing (RS) techniques in the Visible-Near Infrared–Shortwave Infrared (VNIR–SWIR, 400–2500 nm) region could assist in a more direct, cost-effective and rapid manner to estimate important indicators for soil monitoring purposes. Soil reflectance spectroscopy has been applied in various domains apart from laboratory conditions, e.g., sensors mounted on satellites, aircrafts and Unmanned Aerial Systems. The aim of this review is to illustrate the research made for soil organic carbon estimation, with the use of RS techniques, reporting the methodology and results of each study. It also aims to provide a comprehensive introduction in soil spectroscopy for those who are less conversant with the subject. In total, 28 journal articles were selected and further analysed. It was observed that prediction accuracy reduces from Unmanned Aerial Systems (UASs) to satellite platforms, though advances in machine learning techniques could further assist in the generation of better calibration models. There are some challenges concerning atmospheric, radiometric and geometric corrections, vegetation cover, soil moisture and roughness that still need to be addressed. The advantages and disadvantages of each approach are highlighted and future considerations are also discussed at the end