Tidy Geospatial Networks in R

The Geospatial Neighborhood Analysis Package

Spatial cross-validation in Python.

Automated Valuation Machine Learning Model for Lima House Pricing

AISdb Python package for smart AIS data storage and interaction.

Spatial Data Science Complementary Features

Spatially-Encouraged Spectral Clustering, a method of discovering clusters/deriving labels for spatially-referenced data with attribute/labels attached.

Repository for the website of the book (github hosting support)

An R package for handling fuzzy spatial data

LoD1 3D City Model from OpenStreetMap contributions and raster DEM

Python module to access shootings reported in Fogo Cruzado app.

Analyzing Urban Heat Islands Risk Index

Contains materials to reproduce descriptive statistics and figures from 'Spatial Inequality in the Smart City: The Sensor Desert Quandary" published in Transactions of the Institute of British Geographers.

Detection of spatio temporal hotspots of traffic accidents in Saudi Arabia for the years 2015 to 2018. The data is aggregated nonetheless using Hijri calendar years 1437, 1438, 1439. Each Hijri year consists of 12 months and approx. 355 days.

Materials for the Introduction to Spatial Data Science and Machine Learning workshops and UCL's Urban Design B-Pro programme 2022/2023

Base teórica de geomática e prática no python de geoprocessamento para geospatial data science. Página em construção.

AISdb Python package (server-side) for smart AIS data storage and interaction.

The code simulates the movement of birds between various stations, generating data points for each visit, including the station visited, exact (slightly perturbed) coordinates, and a timestamp. This data is stored in a GeoDataFrame that can be used for spatial analysis and visualization.

This repository contains exploratory spatial data analysis (ESDA) functions and scripts. These functions are designed for geothermal spatial datasets, and are applicable to other spatial datasets.

01.12.18 - Notebook provides basic introduction to spatial data science in python for UMN Day of Data 2018