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ADVANCING GLOBAL SOIL SCIENCE
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OPEN SOIL SPECTROSCOPY LIBRARY
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DIFFUSE REFLECTANCE SOIL SPECTROSCOPY
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MACHINE LEARNING FOR SOIL SCIENCE
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SOIL.SPECTROSCOPY

   4 GLOBAL GOOD

An Open Soil Spectroscopy library based on the Open Source Software

ENABLE

Accelerate the pace of scientific discovery in soil spectroscopy by facilitating and supporting a collaborative network of researchers.

CONNECT

Connect international teams and experts in the fields of soil spectroscopy, remote sensing of soils and data science.

DEVELOP

Develop an advanced yet intuitive, open source, web-hosted platform to predict various soil properties from MIR spectra collected on any spectrometer anywhere in the world.
 

DOCUMENT

Document and publish the code and procedures used to generate data and models.

NEWS

LATEST DEVELOPMENT

AN OPEN SOIL

SPECTROSCOPY LIBRARY

Making soil data available across borders

WHY SOILSPEC4GG?

Today's data-driven agriculture demands access to high-resolution spatial and temporal soil data streams. Soil spectroscopy can help fill this data gap. Diffuse reflectance spectroscopy is becoming an indispensable tool in soil science; however, several technical challenges still limit its broader application outside of research projects.

SoilSpec4GG is a USDA-funded Food and Agriculture Cyberinformatics Tools Coordinated Innovation Network. This project will bring together soil scientists, spectroscopists, informaticians, data scientists and software engineers to overcome some of the current bottlenecks preventing wider and more efficient use of soil spectroscopy. A series of working groups will be formed to address topics including calibration transfer, model choice, outreach & demonstration, and use of spectroscopy to inform global carbon cycle modeling.

MAJOR PROJECT OUTPUTS

DATABASES, SOFTWARE, WEB-SERVICES, PUBLICATIONS

DATABASES

Open Soil Spectroscopy Library

The network will deliver an Open Soil Spectroscopy Library (OSSL), backed by large spectral databases and robust statistical models, which derives soil properties from the spectral data.

SOFTWARE

R AND PYTHON LIBRARIES

The network will create open source software to quality check, harmonize and standardize spectra and soil data collections. The software will built upon existing OS packages for soil spectroscopy.

WEB-SERVICES

ACCESS WEB-SERVICES USING API

Data and software / computing will be served through robust and easy to use web-services and API. Users should be able to upload their soil spectroscopy readings and obtain callibrations in near-to-real time.

PUBLICATIONS

DOCUMENTATION, TUTORIALS

All software and data will be accompanied with extensive documentation. Demonstration, outreach and educational activities will promote the use of the OSSL and data-driven science.

JOIN SOILSPEG4GG!

List of partners on project already contributing data and code. Contact us to join this initative.

Quantifying soil carbon in temperate peatlands using a mid-IR soil spectral library - nice application of transfer learning (RS-LOCAL) from Swiss national library to peatland soils.
https://soil.copernicus.org/articles/7/193/2021/

Can Agricultural Management Induced Changes in SOC Be Detected Using MIR Spectroscopy? by @sandersoil, @birdsavage, @shree_sharma, @CharlotteRivar1, @gabes_shakes and great collaborators at @USDA_ARS & @RodaleInstitute #NIFAImpacts

https://www.mdpi.com/1143956

Recordings of our first two webinars by Alexandre Wadoux and @rlleonardo are now available. Links to videos can be found here:
https://soilspectroscopy.org/resources/

VNIR and MIR spectroscopy of PLFA-derived soil microbial properties. While the inference domain is limited (a single field trial), there's a lot of good analysis in this paper.
https://www.sciencedirect.com/science/article/pii/S0038071721001929

The "water-absorption-trough dewatering machine" - winner of best name for machine learning algorithm in #soilspectroscopy? Looks like an interesting method for dealing with variable soil moisture conditions in field scanned soils.
https://www.sciencedirect.com/science/article/pii/S0269749121010277

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