soilspec

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soilspec

soilspec

@soilspec

Tweeting about diffuse reflectance spectroscopy for soil science and updates from USDA NIFA FACT CIN Soil Spectroscopy for the Global Good project

Katılım Aralık 2020
52 Takip Edilen828 Takipçiler
soilspec
soilspec@soilspec·
It is great to see the OSSL being used in so many applications. Selecting the right samples rather than more samples: A new spectral–e... sciencedirect.com/science/articl…
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soilspec@soilspec·
Neat paper emulating various low cost sensors using the LUCAS VisNIR spectral database - conclusion: sensors that cover the later part of the NIR range are much better than those that only cover the lower wavelengths bsssjournals.onlinelibrary.wiley.com/doi/10.1111/ej…
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soilspec@soilspec·
Nice paper by a great team working across multiple soil spectral libraries to produce quality predictions from field measurements - good harmonization & standardization methods are the key sciencedirect.com/science/articl…
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Jonathan Sanderman
Jonathan Sanderman@sandersoil·
workforcenow.adp.com/mascsr/default… We're looking for a talented data/code wrangler to join our rangeland carbon research program to understand the climate benefits of regenerative grazing practices across millions of acres of grasslands.
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soilspec@soilspec·
Exploring Generative Artificial Intelligence and Data Augmentation Techniques for Spectroscopy Analysis | Chemical Reviews pubs.acs.org/doi/full/10.10…
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OpenGeoHub Foundation
OpenGeoHub Foundation@opengeohub·
After almost 3 years of data preparation, testing, optimization, we have finished the v1 of the 30 m resolution global #soilcarbon density, soil carbon content, pH, texture fractions, bulk density and soil types (USDA subgroups). Soil carbon and soil pH are mapped as dynamic soil variables for 5-year intervals; soil texture fractions, bulk density and soil types as static vars. The preprint of the paper is at: doi.org/10.5194/essd-2… Maps are available under CC-BY license #OpenData as COGs from: github.com/openlandmap/so… (almost 6TB of data). Our results show that #landdegradation & intensive urbanization leads to losses in SOC; in some places these losses are significant. Although the uncertainty of the predictions is still relatively limited, we believe that investing in processing #Landsat archive and investing in harmonizing soil laboratory data was worth the effort. But this is just a start! We plan to update predictions and build a community of users and developers (compatible with the Open Soil Spectral Library @soilspec and similar initiatives) around this initiative. If you spot an issue or artifacts please report using Github link. If you are curator of the soil laboratory data and soil observations, please share your data with us, so we can make even more accurate #worldsoildata for everyone. PS: If you are at #LPS25 please find us for a demo of the predictions and data use tutorial.
GIF
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soilspec@soilspec·
Fantastic free resource from the @FAO Global Soil Partnership led by Alexandre Wadoux et al. - A course on applied data analytics for soil analysis with infrared spectroscopy openknowledge.fao.org/handle/20.500.…
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