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ICRAF Soil and Land Health Theme (World Agroforestry Centre)
Land Health Decisions has a vision to support the growing political momentum for large-scale commitments to prevent land degradation, and to restore or regenerate degraded natural resources and ecosystem services, contributing to an unprecedented change in national and global agendas, and a unique opportunity for research to influence policy and action. The theme is contributing to the ICRAF strategy by supporting wise stakeholder decision making on climate-smart land management options that work towards a more equitable world where all people have viable livelihoods supported by healthy and productive landscapes. These options include harnessing the multiple benefits trees provide for agriculture, livelihoods, resilience and the future of our planet, from farmers’ fields through to continental scales.
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81 to 90 of 151 Results
Unknown - 14.7 MB - MD5: 98d025104365df48f79a66dca730d89e
Spectra are saved in this files in RDS format and they work with open-source code repositories (CloudCal and cloudFTIR, both open github projects). The CloudFTIR can be found at: https://github.com/leedrake5/cloudFTIR."
Jun 13, 2022
Rosenstock, Todd; Steward, Peter; Lamanna, Christine, 2022, "Meta-analysis of peer-reviewed agricultural research data from Africa", https://doi.org/10.34725/DVN/2QV0DW, World Agroforestry (ICRAF), V1
The ERAg r-package provides access to the ERA dataset, bibliographic information, associated biophysical data, analytical functions and vignettes. See the package vignettes for how to use the package and access the data contained within. Version: 0.0.1.0000 Evidence for Resilient...
Aug 10, 2020
Vågen, Tor-Gunnar; Winowiecki, Leigh Ann; Desta, Luseged; Tondoh, Ebagnerin Jérôme; Weullow, Elvis; Shepherd, Keith; Sila, Andrew, 2020, "Mid-Infrared Spectra (MIRS) from ICRAF Soil and Plant Spectroscopy Laboratory: Africa Soil Information Service (AfSIS) Phase I 2009-2013", https://doi.org/10.34725/DVN/QXCWP1, World Agroforestry - Research Data Repository, V1, UNF:6:bMN2MBGqFewDKHPgIeRjog== [fileUNF]
AfSIS Phase I was a collaborative projective funded by the Bill and Melinda Gates Foundation (BMGF), which aimed to provide a consistent baseline of soil information for monitoring soil ecosystem services in sub-Saharan Africa (SSA). Partners included, CIAT-TSBF, ISRIC, CIESIN, T...
Tab-Delimited - 2.9 MB - MD5: 8362ced45ea5d1bdce9773d08bb21e9a
MIR spectra of the manure standards using Alpha KBr instrument
Tab-Delimited - 1.8 MB - MD5: b56570fc695ece2feb1d58627985846c
MIR spectra of the manure standards using Alpha ZnSe instrument
Tab-Delimited - 27.2 MB - MD5: 07a83a619303878809426e2e7a3bb1c3
MIR Spectral data
Unknown - 81.6 MB - MD5: a6b8d8504ce61253cae2079c2f3885ed
Using forest regression machine learning models, excellent calibration functions could be established using the MIR spectra. Forest models for there DRIFT-MIR spectra were run using 1500 trees with 200 resampling events using k-fold cross validation over 25 iterations based on th...
Unknown - 29.3 MB - MD5: ac2c20646882bb5b387f26ed9ed53cae
Extreme gradient boosting machine learning (XGBoost) models were used with data from DRIFT-MIR spectroscopy and these differ from forest in that trees can be weighted differently, have fixed depths, and different resembling. XGBoost (0.82.1) models were run using 400 rounds with...
Aug 7, 2019
Moria, Mulugeta; Mekuria, Wolde; Gebrekirstos, Aster; Aynekulu, Ermias; Belay, Beyene; Gashaw; Bra ̈uning, Achim, 2018, "Mixed-species allometric equations and estimation of aboveground biomass and carbon stocks in restoring degraded landscape in northern Ethiopia", https://doi.org/10.34725/DVN/URYP1I, World Agroforestry - Research Data Repository, V1
Processed data used to generate allometric equations to estimate aboveground biomass
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