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GIS

Geospatial Risk Assessment: A Python Approach

Posted on May 5, 2025May 5, 2025 by admin

In today’s data-driven world, understanding and mitigating risks through geospatial analysis has become crucial for industries ranging from insurance to urban planning. In this post, we’ll explore a Python implementation for geospatial risk assessment based on a GitHub repository that demonstrates these concepts. Understanding the Project Structure The repository contains a well-organized src directory with the following…

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Analyzing Employee Arrival Patterns and Delays Using Geospatial Data

Posted on May 4, 2025 by admin

Introduction In this analysis, we explore employee work arrival patterns using geospatial data to understand delays and their relationship with distance from the workplace. The dataset includes employee IDs, arrival times, expected arrival times, and geographic locations. Key Findings 1. Data Preparation and Merging We started by merging two datasets: 2. Calculating Delays We converted…

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Real-Time GPS Tracking on a Web Map using FastAPI & Leaflet

Posted on February 17, 2025February 17, 2025 by admin

Introduction Tracking real-time location data is essential for applications like fleet management, asset tracking, and live location sharing. In this tutorial, we will build a real-time GPS tracking system that receives location data from a moving device and displays it dynamically on a web map. What You’ll Learn By the end of this tutorial, you’ll…

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How to Create a Simple WebGIS with FastAPI, PostGIS, and Leaflet.js

Posted on February 14, 2025 by admin

Introduction In this tutorial, we’ll walk through creating a WebGIS application using FastAPI, PostGIS, and Leaflet.js. The goal is to create a map that displays points stored in a PostGIS database and allows users to add new points by clicking on the map. We’ll cover setting up the FastAPI backend, creating the PostGIS database, and developing the frontend with Leaflet.js…

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Exploring Spatial Density with Python: KDE Analysis of Schools in Tehran

Posted on January 14, 2025January 14, 2025 by admin

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…

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How to Analyze Walking Paths Between Metro Stations and Shopping Centers in Tehran Using Python

Posted on January 7, 2025January 7, 2025 by admin

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…

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Comparing Geospatial Data Formats

Posted on January 5, 2025January 5, 2025 by admin

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…

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Geofencing: A Powerful Tool for the Modern GIS Developer

Posted on January 4, 2025January 4, 2025 by admin

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…

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Extracting and Visualizing Driving Ways with OSMnx and NetworkX in Python

Posted on December 30, 2024December 30, 2024 by admin

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…

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Building Footprint Processor: Simplify GIS Data Processing with Python!

Posted on December 29, 2024December 29, 2024 by admin

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…

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Recent Posts

  • Geospatial Risk Assessment: A Python Approach
  • Analyzing Employee Arrival Patterns and Delays Using Geospatial Data
  • Real-Time GPS Tracking on a Web Map using FastAPI & Leaflet
  • How to Create a Simple WebGIS with FastAPI, PostGIS, and Leaflet.js
  • Graph Coloring: How Many Colors Do You Need?

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Araz Shahkarami

I’m a software enthusiast with a deep love for crafting robust and efficient solutions. My journey into the world of programming began several years ago when I was introduced to the world of code. Since then, I’ve been on an exhilarating ride of learning, problem-solving, and continuous improvement.

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