This paper explores and investigates potential of the close range terrestrial photogrammetry for urban parking space, which is occluded by trees and surrounded by buildings. The main challenge is to map boundaries of horizontal ground surface adjacent to vertical building structures. The study outlines a strategy for comprehensive mapping of such spaces at local scale. The methodology accounts for four criteria, namely, target characteristics, camera positions, overlap, and environmental conditions for planning of data acquisition. Further, target design and camera target geometry are considered to implement data acquisition with a consumer grade camera. Target design decides effective shape, orientation, and pattern of targets, and further determines the optimal distance with camera. Two-sided planar targets in vertical orientation with distinct and discriminate patterns, placed at a short distance to camera, are found appropriate. Camera target geometry designs the target and camera positions at specific distances in both longitudinal and lateral directions. Targets are placed in parallel lines, spaced at a constant distance in lateral direction on building surface and ground, and camera positions are interspaced geometrically in the same pattern. Camera positions acquire images that maintain designed overlap in lateral direction and contain minimum two layers of targets. This mechanism acquires images and generates 3D model that maps both building and horizontal ground surfaces simultaneously. A study site of 84,000 m<sup>2</sup> requires a total of 6615 images, which are processed to generate the 3D photogrammetric model. The model is geo-registered to local reference frame. Area occupied by parking spaces, open areas, and buildings are calculated. Parking space is 6.85% of the total area of the study site and can accommodate 141 car vehicles. Apart from mapping of parking area, the study also prepares a comprehensive map of site that can be used for planning of other utilities and facilities. Though the developed strategy generates and processes voluminous data of images, yet it is an attractive alternate as it demands minimum resources and logistics.