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.
LATEST DEVELOPMENT
Please join us for our second soil spectroscopy webinar featuring Dr. Leonardo Ramirez-Lopez (Wednesday, May 5 2021, 9 am EDT). Dr. Ramirez-Lopez is head of the Data
An applied online platform for soil properties estimation using spectroscopy has been developed by the Department of Soil Science, University of Sao Paulo, Brazil. The
Dear all, Please join us for our inaugural soil spectroscopy webinar featuring Dr. Alexandre Wadoux from the University of Sydney, Australia (Tuesday, April 27 2021, 7 pm
AN OPEN SOIL
SPECTROSCOPY LIBRARY
Making soil data available across borders
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
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.
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.
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
