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Urban Growth Monitoring Kitale Town

📍 Kitale, Trans-Nzoia County📅 2023Academic Project — Commended
QGISPythonUrban PlanningSatellite Imagery

Overview

This project tracked the spatial growth of Kitale town, Trans-Nzoia County between 2010 and 2023 using a time-series of Landsat and Sentinel-2 imagery. Python scripts using Rasterio and GeoPandas automated the extraction of built-up area extents from each image epoch.

Growth was compared against the Trans-Nzoia County Integrated Development Plan 2018-2022 planning boundaries to identify areas of unplanned or informal expansion. Hotspot analysis was performed using Kernel Density Estimation to reveal growth corridors.

Final maps were produced in QGIS using the Atlas function to generate a series of comparable layout plates for each time period.

Key highlights

  • Tracked urban growth across 13 years (2010–2023)
  • Quantified 340% increase in built-up area extent
  • Identified 5 informal growth hotspots outside planning boundaries
  • Automated processing pipeline saved 6+ hours vs manual approach

Challenges

Distinguishing built-up surfaces from bare agricultural soils required careful band combination and threshold tuning, particularly during dry season when spectral signatures converge.

Outcome & results

Project presented to the Trans-Nzoia County Spatial Planning Office as a reference dataset. Received commendation from course supervisor.

Tools used
QGIS 3.xPython (Rasterio, GeoPandas)Sentinel-2Landsat 8QGIS Atlas
Project details
LocationKitale, Trans-Nzoia County
Year2023
CategoryUrban
OutcomeAcademic Project — Commended
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