Novel Building Detection and Location Intelligence Collection in Aerial Satellite Imagery

TL;DR

This paper presents a method for detecting various types of buildings in aerial satellite images to support city planning, disaster management, and land use analysis, emphasizing accurate detection and categorization.

Contribution

The paper introduces a novel approach for detecting and classifying diverse building types in aerial imagery, enhancing urban analysis capabilities.

Findings

Effective detection of different building types achieved

Improved accuracy in locating buildings at specific coordinates

Facilitated clustering and categorization of buildings

Abstract

Building structures detection and information about these buildings in aerial images is an important solution for city planning and management, land use analysis. It can be the center piece to answer important questions such as planning evacuation routes in case of an earthquake, flood management, etc. These applications rely on being able to accurately retrieve up-to-date information. Being able to accurately detect buildings in a bounding box centered on a specific latitude-longitude value can help greatly. The key challenge is to be able to detect buildings which can be commercial, industrial, hut settlements, or skyscrapers. Once we are able to detect such buildings, our goal will be to cluster and categorize similar types of buildings together.