GIS Articles

Geospatial Cross-Validation in Machine Learning: Preventing Spatial Autocorrelation Leakage 1. Introduction Using Geospatial Cross Validation Machine Learning GIS techniques is essential when modeling spatial phenomena like land surface temperature or soil properties. Machine learning models are increasingly used to predict spatial phenomena, including land surface temperature, soil properties, flood susceptibility, vegetation condition, species distributions, housing … Read more

Querying OpenStreetMap Data at Scale with Python and DuckDB 1. Introduction: Why Combine OpenStreetMap with DuckDB? To Query OpenStreetMap Data Python DuckDB effectively, regional extracts provide detailed, openly accessible geographic data covering roads, buildings, and amenities. OpenStreetMap (OSM) provides detailed, openly accessible geographic data covering roads, buildings, amenities, land use, and countless other geographic features. … Read more

Segment Anything Model (SAM) for Automated Building Extraction in QGIS Introduction Using the Segment Anything Model SAM QGIS building extraction workflow significantly streamlines automated feature digitizing and spatial analysis compared to manual vector tracing. Building footprint extraction is one of the most time-consuming tasks in remote sensing and GIS. In conventional workflows, an analyst examines … Read more

Building Offline-First Field Collection Web Apps with Progressive Web App (PWA) Architecture Introduction “Implementing an Offline First Field Collection Web App PWA GIS is essential when field data collection takes place where internet connectivity is unreliable or unavailable. Field data collection frequently takes place where internet connectivity is unreliable or unavailable. Environmental surveys, agricultural assessments, … Read more

Spatial Regression with R: Fitting Spatial Lag and Spatial Error Models in spdep Introduction When performing spatial regression with R spdep, Ordinary Least Squares (OLS) is often the natural starting point for regression analysis. Ordinary Least Squares (OLS) is often the natural starting point for regression analysis. In a conventional linear model, we assume that … Read more

Managing Large Geospatial Datasets Locally with DuckDB and the Spatial Extension Introduction Large geospatial datasets can expose the limitations of conventional desktop GIS workflows. Opening a multi-gigabyte vector file may involve parsing geometry, decoding attributes, building rendering structures, and loading data into memory before an analyst can begin meaningful exploration. When a project contains millions … Read more

Extracting Building Footprints from Aerial Imagery Using OpenCV and Python 1. Introduction Mastering the fundamentals of extracting building footprints OpenCV Python offers a practical way to automate part of the building-mapping workflow before investing in deep learning models. Extracting building footprints with OpenCV and Python GIS tools offers a practical way to automate part of … Read more

Spatial Window Functions and Recursive CTEs in PostGIS Introduction Complex spatial analysis in PostgreSQL rarely requires abandoning SQL for procedural code. By combining PostgreSQL’s analytical SQL features with PostGIS geometry functions, it is possible to build sophisticated workflows for trajectory analysis, spatial hierarchies, network-like traversals, and sequential geographic processes entirely inside the database. Two SQL … Read more

Automated Metadata Generation and ISO Standards Compliance with Python 1. Introduction Mastering Automated Metadata Generation Python scripts helps organizations transition from manual documentation to automated spatial data governance. Spatial data pipelines frequently produce valuable datasets without producing the metadata needed to understand, maintain, discover, or reuse them. A workflow may generate a road network, a … Read more