Full 1
SOIL SPECTROSCOPY FOR ALL!
Full 1
Full 1
OPEN SOIL SPECTROSCOPY LIBRARY
Full 1
Full 1
DIFFUSE REFLECTANCE SOIL SPECTROSCOPY
Full 1
Full 1
MACHINE LEARNING FOR SOIL SCIENCE
Full 1
previous arrow
next arrow

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

NEWS

LATEST DEVELOPMENT

News

Spectroscopy Ring Trial

Hello soil spectroscopists! Under the SoilSpec4GG initiative, we started this year an inter-laboratory spectroscopy ring trial for comparing the variability of spectral response across different

Read More »
News

OSSL Updates

Happy World Soils Day! Since the last release of the Open Soil Spectral Library (OSSL), a lot of work has been done behind the scenes

Read More »

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

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.

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.

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.

Happy #WorldSoilDay from the team at Soil Spectroscopy for the Global Good. Some updates from us:

https://tinyurl.com/ycysb9xr
https://soilspectroscopy.org/ossl-updates/
https://soilspectroscopy.org/spectroscopy-ring-trial/

#iphone for estimating #soilcarbon. Predictions are not bad but highly dependent upon illumination level.

https://www.sciencedirect.com/science/article/pii/S0168169922008328

A big thanks to @fao GLOSOLAN & @vargasfao for keeping soil spectroscopy front and center as a key tool in soil science. We're looking forward to continuing to work with GLOSOLAN to build a global soil spec community.

https://www.fao.org/global-soil-partnership/glosolan-old/soil-analysis/dry-chemistry-spectroscopy/en/

Soil order knowledge as a driver in soil properties estimation from Vis-NIR spectral data – Case study from northern Karnataka (India)
https://www.sciencedirect.com/science/article/pii/S235200942200116X

Load More...