The Brazilian Soil Spectral Service (BraSpecS): A User-Friendly System for Global Soil Spectra Communication

Author:

Demattê José A. M.ORCID,Paiva Ariane Francine da SilveiraORCID,Poppiel Raul RobertoORCID,Rosin Nícolas AugustoORCID,Ruiz Luis Fernando ChimeloORCID,Mello Fellipe Alcantara de Oliveira,Minasny BudimanORCID,Grunwald SabineORCID,Ge Yufeng,Ben Dor EyalORCID,Gholizadeh AsaORCID,Gomez CecileORCID,Chabrillat Sabine,Francos NicolasORCID,Ayoubi Shamsollah,Fiantis Dian,Biney James Kobina MensahORCID,Wang Changkun,Belal AbdelazizORCID,Naimi SalmanORCID,Hafshejani Najmeh Asgari,Bellinaso Henrique,Moura-Bueno Jean Michel,Silvero Nélida E. Q.ORCID

Abstract

Although many Soil Spectral Libraries (SSLs) have been created globally, these libraries still have not been operationalized for end-users. To address this limitation, this study created an online Brazilian Soil Spectral Service (BraSpecS). The system was based on the Brazilian Soil Spectral Library (BSSL) with samples collected in the Visible–Near–Short-wave infrared (vis–NIR–SWIR) and Mid-infrared (MIR) ranges. The interactive platform allows users to find spectra, act as custodians of the data, and estimate several soil properties and classification. The system was tested by 500 Brazilian and 65 international users. Users accessed the platform (besbbr.com.br), uploaded their spectra, and received soil organic carbon (SOC) and clay content prediction results via email. The BraSpecS prediction provided good results for Brazilian data, but performed variably for other countries. Prediction for countries outside of Brazil using local spectra (External Country Soil Spectral Libraries, ExCSSL) mostly showed greater performance than BraSpecS. Clay R2 ranged from 0.5 (BraSpecS) to 0.8 (ExCSSL) in vis–NIR–SWIR, but BraSpecS MIR models were more accurate in most situations. The development of external models based on the fusion of local samples with BSSL formed the Global Soil Spectral Library (GSSL). The GSSL models improved soil properties prediction for different countries. Nevertheless, the proposed system needs to be continually updated with new spectra so they can be applied broadly. Accordingly, the online system is dynamic, users can contribute their data and the models will adapt to local information. Our community-driven web platform allows users to predict soil attributes without learning soil spectral modeling, which will invite end-users to utilize this powerful technique.

Funder

São Paulo Research Foundation

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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