Alexander Quevedo's repositories
Hands-On-Gradient-Boosting-with-XGBoost-and-Scikit-learn
Hands-On Gradient Boosting with XGBoost and Scikit-learn Published by Packt
2020_analysis_of_big_earth_data_with_jupyter
This repository hosts the Jupyter notebooks developed for the lecture on 'Analysis of Big Earth Data with Jupyter notebooks' during the OpenGeoHub Summer School 2020.
2020_OpenGeoHub_machine-learning-madlene
OpenGeoHub Summer School: Mastering Machine Learning - Lecture and Training
arrow-user2022
Larger-Than-Memory Data Workflows with Apache Arrow
BanDiTS
Tool for extracting all kinds of statistics from Sentinel-1 time series and visualizing them
bayts
Set of tools to apply the probabilistic approach of Reiche et al. (2015, 2018) to combine multiple optical and/or Radar satellite time series and to detect deforestation/forest cover loss in near real-time. The package includes functions to apply the approach to both, single pixel time series and raster time series. Examples and test data are provided below.
bfast-1
GPU Implementation for BFAST
dashboarding_jupyter_voila
This repository hosts the Jupyter notebooks developed for the lecture on 'Dashboarding with Jupyter and Voila' during the OpenGeoHub Summer School 2020.
Dockerfile
Contiene los archivos Dockerfile creados en por la CGIG
earthpy
A package built to support working with spatial data using open source python
EGU_2021_lgeo_workshops
Workshop materials for EGU General Assembly 2021 sessions Spatio-temporal trend analysis of spatial climate data (temperature and rainfall) using Python Satellite image processing using Python programming
gee-ccdc-tools
Tools and Earth Engine apps to interact with the outputs from the CCDC algorithm
gee_s1_ard
Creates an analysis ready sentinel-1 SAR image collection in Google Earth Engine by applying additional border noise correction, speckle filtering and radiometric terrain normalization.
GeoStatsTutorials
Tutorials in the form of Jupyter notebooks for the GeoStats.jl framework
ogh_summer_school_2020
Material for the session "Introduction to Deep Learning in R for the analysis of UAV-based remote sensing data"
OpenGeoHub_2020
Ressources for the session on machine learning and remote sensing at the OpenGeoHub Summer school in Wageningen 2020
opengeohub_summerschool2020
Materials for OpenGeoHub summer school 2020 tutorial on "Creating and Analyzing Multi-Variable Earth Observation Data Cubes in R"
parallel-python-workshop
Environment for the Parallel Python workshop
PlanetaryComputerExamples
Examples of using the Planetary Computer
redcastle-resources_CONAFOR-
Trainings for CONAFOR IP trip
sentinel-tree-cover
Image segmentations of trees outside forest
STRbook
Supplementary package for "Spatio-Temporal Statistics with R" by C.K. Wikle, A. Zammit-Mangion, and N. Cressie
whitebox-geospatial-analysis-tools
An open-source GIS and remote sensing package
workshops-setup_cloud_analytics_machine
Tips and Tricks to setup a cloud machine for Analytics and Data Science with R, RStudio and Shiny Servers, Python and JupyterLab