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yangxhcaf's Projects

soc-arg icon soc-arg

Data and code from the manuscript 'Temporal harmonization of a national dataset for spatial prediction of soil organic carbon'

socialecological icon socialecological

A model application of the livestock resilience model for social-ecological modelling.

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Support files for a data visualization course and book

soil-carbon-debt icon soil-carbon-debt

R code and spatial predictions for WHRC-TNC project modeling spatial extent of soil carbon loss due to agriculture

soil-moisture icon soil-moisture

A collection of code written along the way to visualizing and analyzing time-series soil moisture data in the continental USA.

soil-nutrient-maps-of-sub-saharan-africa-article icon soil-nutrient-maps-of-sub-saharan-africa-article

Hengl, T., Leenaars, J. G., Shepherd, K. D., Walsh, M. G., Heuvelink, G. B., Mamo, T., et al. (2017) Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutrient Cycling in Agroecosystems, 109(1), 77–102.

soilc-ca-rangelands icon soilc-ca-rangelands

Collection of scripts for the CA rangelands case study of the SNAPP soil carbon working group

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A open source and open access resource for the soil erosion community.

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Global spatial predictions of soil properties and classes at 250 m resolution

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Spatial emergent constraint on the sensitivity of soil carbon turnover to global warming - Varney et al. 2020 Nature Communications

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codes for paper "Trends in persistent seasonal-scale atmospheric circulation patterns responsible for seasonal precipitation totals and occurrences of precipitation extremes over Canada" in Journal of Climate

soudzilovskaia_naturecomm_mycomaps icon soudzilovskaia_naturecomm_mycomaps

Files and R codes to the manuscript Soudzilovskaia et al (2019) Nature Communications "Global mycorrhizal plant distribution linked to terrestrial carbon stocks "

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Space Shepherd: Satellite remote sensing of sheep distributions in 2020 and 2030

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land use land cover change script using space and time models: Yucatan and Ecuador

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Sources of the book "Displaying time series, spatial and space-time data with R" (1st Edition)

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Species Presence/Absence R Trends Analyses

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Slides, code and data for "Scalable methods for large spatial data" course, Spring 2017

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Tutorial for Spatial Data Analysis. Source: https://www.rspatial.org/raster/analysis/index.html

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