Understanding the spatial distribution of facilities like schools is crucial for urban planning and decision-making. In this post, we’ll walk you through how to use Python to perform a Kernel Density Estimation (KDE) analysis and visualize the results interactively. Why Kernel Density Estimation? KDE is a statistical method used to estimate the probability density function…
Introduction:With the increasing need for efficient urban planning and accessibility analysis, spatial data processing has become more vital than ever. In this blog post, I’ll guide you through analyzing walking paths between metro stations and shopping centers in Tehran using Python’s robust geospatial libraries like OSMnx, GeoPandas, Folium, Shapely, and NetworkX. By the end, you’ll…
GeoParquet vs Shapefile vs GeoJSON When it comes to handling geospatial data, choosing the right format is crucial for performance, compatibility, and usability. In this blog post, we will compare three popular geospatial data formats: GeoParquet, Shapefile, and GeoJSON. Each format has its strengths and weaknesses, making them suitable for different use cases. Below is…
Introduction In today’s interconnected world, geofencing has emerged as a groundbreaking technology that leverages geographic information systems (GIS) to redefine how businesses and organizations interact with the world around them. For GIS developers, understanding geofencing is not just an added skill but a vital component in creating innovative and impactful solutions. What is Geofencing? Geofencing…
This tutorial provides a step-by-step guide to extracting and visualizing driving paths in a specified location using Python’s OSMnx and NetworkX libraries. Learn how to compute the shortest paths between points, convert graph data into geospatial formats, and export the results as GeoJSON files for further analysis. Tutorial Content: Introduction Working with geospatial data is…
Easily Process Building Data for GIS Projects! In this video, I introduce you to the Building Footprint Processor, a powerful Python library that makes downloading and processing building footprint data simple and efficient. Whether you’re a GIS developer, urban planner, or researcher, this tool is perfect for extracting geospatial data for any area of interest…
Map projections are methods used to represent the three-dimensional surface of the Earth on a two-dimensional plane. In Python, several libraries can be used to work with map projections, such as Matplotlib, Cartopy, and Basemap. Below, I’ll provide an overview of how to use Cartopy, a popular library for geospatial data visualization, to create a…
What is WKT? Well-Known Text (WKT) is a standardized text format used to represent geometric objects such as points, lines, and polygons. It provides a human-readable and compact way to convey the spatial properties of these objects. WKT is widely used in Geographic Information Systems (GIS) to exchange geospatial data between different systems and applications….
Spatial geometry is an essential foundation for understanding the world around us, particularly in fields like GIS (Geographic Information Systems), urban planning, and computational modeling. My course is designed to guide you step by step through the fundamental concepts, techniques, and applications of spatial geometry. Here’s a sneak peek into what you’ll learn: 1. Introduction…
A GIS Developer (Geographic Information Systems Developer) is a professional who specializes in designing, developing, and maintaining software applications and tools that work with spatial data and geographic information. They combine skills in programming, GIS technology, and spatial analysis to create solutions for mapping, data visualization, and geospatial problem-solving. Key Responsibilities of a GIS Developer: Industries Where…
