Marcelo Bueno Dueñas's repositories
soil_moisture_SMAP_machine_learning
Scripts for the spatial analysis, processing and regression modeling of soil moisture retrieved from SMAP satellite using R
smap_downscaling
Notebooks for downscaling SMAP soil moisture and validation against in situ data
Bare-soil-detection_LandSat
Synthetic soil composite derived from LandSat time series in Google Earth Engine
soil-remote-sensing-system
Google Earth Engine algorithm for generating synthetic soil composites from Landsat catalog.
terrain_clustering_gaussian_mixture_modeling
Clustering of geomorphometric atributes for soil clasificación purposes on andean landscapes based on Gaussian mixture modeling. Implementation of the code of Dyba, K., & Jasiewicz, J. (2022). Toward geomorphometry of plains—Country-level unsupervised classification of low-relief areas (Poland). Geomorphology, 413, 108373. https://doi.org/10.1016/j.geomorph.2022.108373
glacier_mapping_peru
Spatial validation of machine learning algorithms for main glacier regions in Peru.
Parlange-Haverkamp-1D-infiltration
Code for solving the 1D analytical Haverkamp infiltration equation using Newton method
spatial_data_analysis_agriculture_R
Code in R for spatial analysis of agricultural and soil data.
latin_hypercube_sampling_R
Case study of Latin Hypercube Sampling in soil sampling with R
mlr3_spatial_cross_validation_R
Code for apply new approaches for spatial cross validation of machine learning predictions of spatial variables, based on MLR3 library and Schratz, P., Becker, M., Lang, M., & Brenning, A. (2021). Mlr3spatiotempcv: Spatiotemporal resampling methods for machine learning in R. ArXiv:2110.12674 [Cs, Stat]. http://arxiv.org/abs/2110.12674
simulate_cluster_raster
simulate_cluster_raster
super_learner_machine_learning_soil_mapping
Code and data from Mario Guevara´s Digital Soil Mapping 2021 course. SuperLearner approach for soil carbon mapping.