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Land usage patterns are very important for urban planning. The land development applications require the knowledge of already built structures and their status. Field surveys are costly and time consuming due to extensiveness of the unplanned areas. So with the availability of satellite imagery, we can classify land up to much accuracy

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MuhammadHaseebAli/Detecting-Planned-and-Unplanned-Locality-Using-Satellite-Imagery

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Detecting-Planned-and-Unplanned-Locality-Using-Satellite-Imagery

In under developed countries like Africa and Asia, unplanned settlements like slums come into existence with the spread of urban populations. People from remote areas comes to the city for finding jobs and labor work and demand lost cost residency which in turn give raise to these unplanned slums and shantytowns. Effective management, improvements and reconstruction of these unplanned settlement become important policy in big city. So for urban reconstruction identification and characterization of these areas is very crucial for reconstructing those areas. As these areas are widely spread so field surveys are very time consuming and costly so we want to use remote sensing techniques for the segmentation of these areas.

Archhitecture used

Comparison of different results

Capture111

confusion Metrices

Focal Loss

Exposed Soil Grass High Building Density (_80%) Irregular Layout Large Buildings Low Building Density(_50%) Moderate Building Density (50%-80%) Regular Layout Sparse Greenery (10-50%) Trees Very Sparse Greenery(_5%) Dense Greenery(_50%)

CrossEntropy Loss

Low Building Density(_50%) (1) Moderate Building Density (50%-80%) (1) Regular Layout (1) Sparse Greenery (10-50%) (1) Trees (1) Very Sparse Greenery(_5%) (1) Dense Greenery(_50%) (2) Exposed Soil (1) Grass (2) High Building Density (_80%) (2) Irregular Layout (1) Large Buildings (1)

Location Comaprison

We Tried Our Model on Two Different Locations Model Town and Raiwind Road

Raiwind ROad Model TOwn

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Land usage patterns are very important for urban planning. The land development applications require the knowledge of already built structures and their status. Field surveys are costly and time consuming due to extensiveness of the unplanned areas. So with the availability of satellite imagery, we can classify land up to much accuracy

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