An interlaboratory comparison of mid-infrared spectra acquisition: Instruments and procedures matter

Diffuse reflectance spectroscopy has been extensively employed to deliver timely and cost-effective predictions of a number of soil properties. However, although several soil spectral laboratories have been established worldwide, the distinct characteristics of instruments and operations still hamper further integration and interoperability across mid-infrared (MIR) soil spectral libraries. In this study, we conducted a large-scale ring trial experiment to understand the lab-to-lab variability of multiple MIR instruments. By developing a systematic evaluation of different mathematical treatments with modeling algorithms, including regular preprocessing and spectral standardization, we quantified and evaluated instruments' dissimilarity and how this impacts internal and shared model performance. We found that all instruments delivered good predictions when calibrated internally using the same instruments' characteristics and standard operating procedures by solely relying on regular spectral preprocessing that accounts for light scattering and multiplicative/additive effects, e.g., using standard normal variate (SNV). When performing model transfer from a large public library (the USDA NSSC-KSSL MIR library) to secondary instruments, good performance was also achieved by regular preprocessing (e.g., SNV) if both instruments shared the same manufacturer. However, significant differences between the KSSL MIR library and contrasting ring trial instruments responses were evident and confirmed by a semi-unsupervised spectral clustering. For heavily contrasting setups, spectral standardization was necessary before transferring prediction models. Non-linear model types like Cubist and memory-based learning delivered more precise estimates because they seemed to be less sensitive to spectral variations than global partial least square regression. In summary, the results from this study can assist new laboratories in building spectroscopy capacity utilizing existing MIR spectral libraries and support the recent global efforts to make soil spectroscopy universally accessible with centralized or shared operating procedures

Improvement of clay and sand quantification based on a novel approach with a focus on multispectral satellite images.

Abstract: Soil mapping demands large-scale surveys that are costly and time consuming. It is necessary to identify strategies with reduced costs to obtain detailed information for soil mapping. We aimed to compare multispectral satellite image and relief parameters for the quantification and mapping of clay and sand contents. The Temporal Synthetic Spectral (TESS) reflectance and Synthetic Soil Image (SYSI) approaches were used to identify and characterize texture spectral signatures at the image level. Soil samples were collected (0?20 cm depth, 919 points) from an area of 14,614 km 2 in Brazil for reference and model calibration. We compared different prediction approaches: (a) TESS and SYSI; (b) Relief-Derived Covariates (RDC); and (c) SYSI plus RDC. The TESS method produced highly similar behavior to the laboratory convolved data. The sandy textural class showed a greater increase in average spectral reflectance from Band 1 to 7 compared with the clayey class. The prediction using SYSI produced a better result for clay (R 2 = 0.83; RMSE = 65.0 g kg − 1 ) and sand (R 2 = 0.86; RMSE = 79.9 g kg − 1 ). Multispectral satellite images were more stable for the identification of soil properties than relief parameters

Multi-Temporal Satellite Images on Topsoil Attribute Quantification and the Relationship with Soil Classes and Geology

The mapping of soil attributes provides support to agricultural planning and land use monitoring, which consequently aids the improvement of soil quality and food production. Landsat 5 Thematic Mapper (TM) images are often used to estimate a given soil attribute (i.e., clay), but have the potential to model many other attributes, providing input for soil mapping applications. In this paper, we aim to evaluate a Bare Soil Composite Image (BSCI) from the state of São Paulo, Brazil, calculated from a multi-temporal dataset, and study its relationship with topsoil properties, such as soil class and geology. The method presented detects bare soil in satellite images in a time series of 16 years, based on Landsat 5 TM observations. The compilation derived a BSCI for the agricultural sites (242,000 hectare area) characterized by very complex geology. Soil properties were analyzed to calibrate prediction models using 740 soil samples (0–20 cm) collected of the area. Partial least squares regression (PLSR) based on the BSCI spectral dataset was performed to quantify soil attributes. The method identified that a single image represents 7 to 20% of bare soil while the compilation of the multi-temporal dataset increases to 53%. Clay content had the best soil attribute prediction estimates (R2 = 0.75, root mean square error (RMSE) = 89.84 g kg−1, and accuracy = 74%). Soil organic matter, cation exchange capacity and sandy soils also achieved moderate predictions. The BSCI demonstrates a strong relationship with legacy geological maps detecting variations in soils. From a single composite image, it was possible to use spectroscopy to evaluate several environmental parameters. This technique could greatly improve soil mapping and consequently aid several applications, such as land use planning, environmental monitoring, and prevention of land degradation, updating legacy surveys and digital soil mapping

Remote sensing of the Earth's soil color in space and time

Soil color is a key indicator of soil properties and conditions, exerting influence on both agronomic and environmental variables. Conventional methods for soil color determination have come under scrutiny due to their limited accuracy and reliability. In response to these concerns, we developed an innovative system that leverages 35 years of satellite imagery in conjunction with in-situ soil spectral measurements. This approach enables the creation of a global soil color map with a fine spatial resolution of 30 m x 30 m. The system initially identifies bare earth areas worldwide using reflectance bands acquired from Landsat 4 through Landsat 8 between 1985 and 2020. Soil color was quantified using the CIE-XYZ coordinates, utilizing 8005 soil spectral measurements within the visible range (380–780 nm) as ground truth data. We established transfer functions to convert Landsat reflectance bands to standardized XYZ color coordinates. These transfer functions were subsequently applied to images of bare surfaces, covering approximately 38.5% of the Earth's surface. We validated the resulting global soil color map using statistical indices derived from an independent set of ground-truth spectral data, demonstrating a high degree of agreement. By creating the world's first global soil color map, we have set a baseline for future spatial and temporal monitoring of soil conditions, thus enhancing our understanding and management of our planet's vital soil resources

Multiple Sclerosis In South America: Month Of Birth In Different Latitudes Does Not Seem To Interfere With The Prevalence Or Progression Of The Disease [esclerose Múltipla Na América Do Sul: Mês De Nascimento Em Diferentes Latitudes Não Parece Interferir Com A Prevalência Ou Progressão Da Doença]

Objective: To assess whether the month of birth in different latitudes of South America might influence the presence or severity of multiple sclerosis (MS) later in life. Methods: Neurologists in four South American countries working at MS units collected data on their patients' month of birth, gender, age, and disease progression. Results: Analysis of data from 1207 MS patients and 1207 control subjects did not show any significant variation in the month of birth regarding the prevalence of MS in four latitude bands (0-10; 11-20; 21-30; and 31-40 degrees). There was no relationship between the month of birth and the severity of disease in each latitude band. Conclusion: The results from this study show that MS patients born to mothers who were pregnant at different Southern latitudes do not follow the seasonal pattern observed at high Northern latitudes.719:00 AM573579Templer, D.I., Trent, N.H., Spencer, D.A., Season of birth in multiple sclerosis (1992) Acta Neurol Scand, 85, pp. 107-109Bharanidharan, P., Monthly distribution of multiple sclerosis patients' births (1997) Int J Biometeorol, 40, pp. 117-118Salemi, G., Ragonese, P., Aridon, P., Is season of birth associated with multiple sclerosis? (2000) Acta Neurol Scand, 101, pp. 381-383Salzer, J., Svenningsson, A., Sundström, P., Season of birth and multiple sclerosis in Sweden (2010) Acta Neurol Scand, 122, pp. 70-73Bayes, H.K., Weir, C.J., O'Leary, C., Timing of birth and risk of multiple sclerosis in the Scottish population (2010) Eur Neur, 63, pp. 36-40Saastamoinen, K.P., Auvinen, M.K., Tienari, P.J., Month of birth is associated with multiple sclerosis but not with HLA-DR15 in Finland (2012) Mult Scler, 18, pp. 563-568Fernandes de Abreu, D.A., Babron, M.C., Rebeix, I., Season of birth and not vitamin D receptor promoter polymorphisms is a risk factor for multiple sclerosis (2009) Mult Scler, 15, pp. 1146-1152Willer, C.J., Dyment, D.A., Sadovnick, A.D., Timing of birth and risk of multiple sclerosis: Population based study (2005) BMJ, 330, p. 120. , Canadian Collaborative Study GroupDeussing, E.C., Jankosky, C.J., Clark, L.L., Estimated incidence of multiple sclerosis among United States Armed Forces personnel using the Defense Medical Surveillance System (2012) Mil Med, 177, pp. 594-600Staples, J., Ponsonby, A.L., Lim, L., Low maternal exposure to ultraviolet radiation in pregnancy, month of birth, and risk of multiple sclerosis in offspring: Longitudinal analysis (2010) BMJ, 340, p. 1640Givon, U., Zeilig, G., Dolev, M., The month of birth and the incidence of multiple sclerosis in the Israeli population (2012) Neuroepidemiology, 38, pp. 64-68Fragoso, Y.D., Shearer, K.D., Adoni, T., Month of birth does not seem to interfere with the development of multiple sclerosis later in life in Brazilian patients (2012) Neuroepidemiology, 39, pp. 70-71Koch, M., de Keyser, J., Tremlett, H., Timing of birth and disease progression in multiple sclerosis (2008) Mult Scler, 14, pp. 793-798Tremlett, H.L., Devonshire, V.A., Does the season or month of birth influence disease progression in multiple sclerosis? (2006) Neuroepidemiology, 26, pp. 195-198Poser, C.M., Paty, D.W., Scheinberg, L., New diagnostic criteria for multiple sclerosis: Guidelines for research protocols (1983) Ann Neurol, 13, pp. 227-231McDonald, W.I., Compston, A., Edan, G., Recommended diagnostic criteria for multiple sclerosis: Guidelines from the International Panel on the diagnosis of multiple sclerosis (2001) Ann Neurol, 50, pp. 121-127Polman, C.H., Reingold, S.C., Edan, G., Diagnostic criteria for multiple sclerosis: 2005 revisions to the "McDonald Criteria" (2005) Ann Neurol, 58, pp. 840-846Kurtzke, J.F., Rating neurologic impairment in multiple sclerosis: An expanded disability status scale (EDSS) (1983) Neurology (Cleveland), 33, pp. 1444-1452Damasceno, A., von Glehn, F., de Deus-Silva, L., Monthly variation of multiple sclerosis activity in the Southern hemisphere: Analysis from 996 relapses in Brazil (2012) Eur J Neurol, 19, pp. 660-662Altmann, D.M., Review series on helminths, immune modulation and the hygiene hypothesis: Nematode coevolution with adaptive immunity, regulatory networks and the growth of inflammatory diseases (2009) Immunology, 126, pp. 1-2Correale, J., Farez, M.F., The impact of environmental infections (parasites) on MS activity (2011) Mult Scler, 17, pp. 1162-1169Watson, P.E., McDonald, B.W., Seasonal variation of nutrient intake in pregnancy: Effects on infant measures and possible influence on diseases related to season of birth (2007) Eur J Clin Nutr, 61, pp. 1271-1280Melcon, M., Melcon, C., Bartoloni, L., Towards establishing MS prevalence in Latin America and the Caribbean (2013) Mult Scler, 19, pp. 145-152. , The "Grupo Colaborativo Multicéntrico para el Estudio de la Esclerosis Multiple en America Latina y el Caribe" (GEEMAL)Taylor, B.V., Pearson, J.F., Clarke, G., MS prevalence in New Zealand, an ethnically and latitudinally diverse country (2010) Mult Scler, 16, pp. 1422-1431Dobson, R., Giovannoni, G., Ramagopalan, S., The month of birth effect in multiple sclerosis: Systematic review, meta-analysis and effect of latitude (2013) J Neurol Neurosurg Psychiatry, 84, pp. 427-43