An Index Based on Joint Density of Corners and Line Segments for Built-Up Area Detection from High Resolution Satellite Imagery

Xiaogang Ning,Xiangguo Lin

doi:10.3390/ijgi6110338

Abstract

Detection of built-up areas from Very High Spatial Resolution (VHSR) remote sensing images is a critical step in urbanization monitoring. This paper presents a method for extracting built-up areas from VHSR remote sensing imagery by using feature-level-based fusion of right angle corners, right angle sides and road marks. This method has six main steps. First, line segments are detected. Second, the Harris corner points are detected. Third, the right-angle corners and right-angle sides are determined by cross-verification of the above detected Harris corners and line segments. Fourth, the potential road marks are detected by the template matching method. Fifth, a built-up index image is constructed. Finally, the built-up areas are extracted through a binary thresholding of the above index image. Three satellite images with wide coverage are employed for evaluating the above proposed method. The experimental results suggest that the proposed method outperforms the classic PanTex method. On average, the completeness and the quality of the proposed method are respectively 17.94% and 13.33% better than those of the PanTex method, while there is no great difference between the two methods on the correctness.

Highlights

Very High Spatial Resolution (VHSR) aerial and satellite images provide valuable information [1] in diverse fields such as geography, cartography, surveillance, city planning, surveying and mapping
The above indices may fail to accurately detect built-up areas from the VHSR images because the VHSR images may not contain the necessary spectral bands that are needed in computing these indices
Our method achieves a satisfactory performance it is subject to recognizing some croplands as built-up areas because these croplands have similar shapes as the buildings

Summary

Introduction

Very High Spatial Resolution (VHSR) aerial and satellite images provide valuable information [1] in diverse fields such as geography, cartography, surveillance, city planning, surveying and mapping. Built-up regions’ information such as area, shape, location, distribution, growth and characteristics greatly helps government agencies and urban planners in updating land use maps, forming long-term plans and monitoring urbanization. The monitoring of built-up regions has received increasing attention [2]. In this kind of monitoring, the first step is to detect built-up areas from the VHSR remote sensing images [3]. For low and medium spatial resolution remote sensing images with abundant spectral bands, researchers have proposed many built-up area indices such as the Normalized Difference Built-up Index [4], the Enhanced Built-Up and Bareness Index [5] and the Combinational Built-Up Index [6]. The above indices may fail to accurately detect built-up areas from the VHSR images because the VHSR images may not contain the necessary spectral bands that are needed in computing these indices

Methods

Results

Discussion

Conclusion