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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, VOL. 7, NO. 2, FEBRUARY 2014

503

Integration of LiDAR Data and Orthophoto for
Automatic Extraction of Parking Lot Structure
Lihua Tong, Liang Cheng, Manchun Li, Jiechen Wang, and Peijun Du

Abstract—To overcome the challenges of parking lot structure extraction using optical remote sensing images, this study proposes an automatic method for the extraction of parking lot structure by integrating LiDAR data and orthophoto, which consists of three steps. The first step is to extract vehicles from LiDAR data and then to identify the corresponding central axes for each vehicle. In the second step, orientations of the identified vehicle central axes are used as principle orientation constraints for parking lines extraction from orthophoto. The third step is the determination of parking lot structure with vehicle central axes and parking lines, in which parking lot parameters are calculated and an adaptive growth method is used for parking lot structure determination.
In this method, vehicle central axes identified from LiDAR data and parking lines extracted from orthophoto are integrated for the extraction of parking lot structures. The main novelty of this study lies in two new algorithms: an algorithm on parking lines extraction with principal orientation constraints and an algorithm on parking lot structure determination based on parameter solution and adaptive growth. The experiment shows that the proposed method can effectively extract parking lot structure with high correctness, high completeness, and good geometric accuracy.
Index Terms—LiDAR data, orthophoto, parking lot structure, principal orientation constraint, vehicle central axis.

I. INTRODUCTION

S

INCE remote sensing is providing increasing sensors and techniques to acquire data, data on urban regions is accumulating and expanding, leading to various innovative applications [1]. Parking

References: Remote Sens., vol. 5, no. 1, pp. 59–70, Feb. 2012.