Notebooks and libraries for spatial/geo Python explorations
A set of Python scripts and notebooks to help administer track views and analyze track data
Repository of Jupyter notebooks aimed at learning how to use Python to retrieve data from Google Earth Engine
Spatiotemporal analysis of ENSO & IOD impacts on drought variability in Central Java using Google Earth Engine, Wavelet Coherence, and EOF PCA. (BRIN Research Project).
All the code in this branch will be python based, upon jupyter notebook. You will be able to find all codes for Google Earth Engine(GEE) on this repository. You will be able to link code with each post blog on readme file for each folders. Content from the Blog https://kaflekrishna.com.np will be uploaded here. https://google-earth-engine.com/
Performing GeoSpatial Data Science on PostGIS-hosted data through Jupyter Notebooks
A Jupyter notebook to identify collective cell signalling in raw microscopy images
A collection of code notebooks designed to support researchers, analysts, and data enthusiasts create reproducible spatial workflows in R. Designed in collaboration with IPUMS and the NSF I-GUIDE.
Jupyter notebooks for the workshop *Introduction to Python language and Google Colab for spatial data visualization and analysis*
Set of functions, scripts and notebooks used in the brain-wide auditory processing project
🧪 A curated collection of Python Jupyter Notebooks for GIS data processing, spatial analysis, and map visualization.
Region-level analysis of Türkiye's housing market that separates real (inflation-adjusted) price growth from inflation, comparing the six years before and after the COVID-19 pandemic (2014–2025) — reproducible Python notebook, high-res figures, and LISA spatial analysis.
Python notebook for retrieving and visualizing polygon data from MAPID, then performing basic spatial operations (100m buffer, simplify, clip bounding box, dissolve per class, union, calculate area) and saving the output in GeoJSON format.
Code for the paper: A Hybrid AHP and Ensemble Machine Learning Approach for Flood Susceptibility Assessment in Tapanuli Tengah Regency, Indonesia. Reproducible Jupyter notebooks for flood susceptibility mapping using AHP, Random Forest, XGBoost, and SHAP analysis.
Air pollution exposure disparities by race, ethnicity and HOLC redlining grade across U.S. census blocks, 2000-2015: notebook, figures and tables for two manuscripts in preparation (drafts of 18 September 2026). See CORRECTIONS.md for the corrections of 4 October 2026.
This repository contains all the various and noteworthy short simple codes (in Python 3.13.5, Jupyter Notebook 7.4.5, Mathematica 13.3, R 4.4.2, and Julia 1.11.3) I have ever made while studying for my degree and future studies in Physics at the University of the Balearic Islands (UIB).
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