**2. GIS-based site information management and visualization**

Google Earth has been widely used by scientists and relevant stakeholders in addressing environmental and construction planning issues thanks to its ubiquity and rich geographic information. Diversified geographical information is presented to the user through a combination of digital elevation models, satellite imagery, 3D building models, street views, and user-uploaded images. Features such as tiling and level of detail (LOD) for images and 3D models enable Google Earth to manage large datasets with ease and efficiency, eclipsing majority of BIM software. Besides, KML enriches the extensibility of Google Earth significantly by providing users a standardized language to add data and customize analyses. With temporal and spatial information associated with each object, Google Earth enables efficient information retrieval through content navigation, 3D exploration, and time window filtering.

The *GoogleEarthWork*—which is prototyped based on Google Earth using KML—seamlessly integrates information contained in unordered images, geometric models, and 3D GIS system. As presented in **Figure 1**, the system encompasses data collection, data processing, data management, and information visualization and distribution. Aerial and ground imageries of the construction site captured

**Figure 1.**

*GoogleEarthWork for earthwork construction planning.*

with unmanned aerial vehicles (UAVs) and mobile devices are selected as major data sources for actual site monitoring and modeling. As-planned models and project schedules provide main data sources to build a virtual construction process. In addition, the 3D environment construction environment is reproduced in the visualization system. Subsequent to data acquisition, images and models need to be processed such that they are compatible with KML. Models are divided into parts in order to denote distinct construction stages in line with construction schedule.

Photogrammetry algorithms are also used in order to align unordered images within the WGS84 coordinate system adopted in Google Earth. Panoramic views and 3D reconstruction of the construction site are produced to facilitate a better comprehension of the construction environment. The resulting 3D point cloud captures the geometry of the construction site and is thereby used for cut/fill volume takeoff, as well as measuring the hauling distance between two areas. As-planned models are converted in the KML format and time-stamped in order to visualize the construction progress. The system provides stakeholders with a visually intuitive platform to perceive the construction site and identify potential problems such as spatial limits in connection with site accesses and site layouts through integrated information visualization. By storing data on the cloud, KML enables efficient

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volume estimation.

phones on the ground.

example is given in the subsequent section.

*Google Earth Augmented for Earthwork Construction Planning*

being built also affect site accessibility and traffic flows.

distribution and improves computing efficiency performances.

management of large volumes of data in images and models. Sharing KML documents of limited size instead of original datasets also streamlines information

Google Earth provides project managers with free high-resolution satellite images and topographic information of the environment around a construction site. Such information is essential to plan for site accesses, site layouts, and traffic flows. As-planned information in 2D/3D drawings is crucial for scope definition, quantity takeoff, and progress monitoring. For earthwork projects specifically, the as-designed surface is required to take off cut/fill volumes. Besides, the structures

For as-built information, site photos have been widely used on a construction site for updating construction progress and reporting safety issues or other problems. However, images collected by different personnel are barely reused due to lack of efficient image management tools. It is desirable to automatically organize images with locations in a GIS system, but the positioning accuracy of mobile devices is inadequate for two main reasons, namely, (1) low-end localization sensors embedded in mobile devices and (2) multipath effect of radio frequency signals. In general, the camera pose obtained from a consumer-grade mobile device does not satisfy the need for geo-referencing and AR applications. Higher positioning accuracy can be obtained from aerial images taken by UAV due to high-grade localization sensors embedded and lessened multipath effects. After bundle adjustment [51], the camera pose can be further improved. By taking the optimized geo-location of aerial images as references, ground imageries can also be precisely aligned in the physical coordinate system. In addition, 3D reconstruction from images is instrumental in quantifying cut/fill volumes of earthmoving jobs and fixing distances and slopes of haul roads in earthwork construction planning. Most recent research endeavors [52] have demonstrated the cost-effectiveness of UAV photogrammetry for earthwork

Structure from motion (SfM) [53] has been well studied in photogrammetry and computer vision domains to reconstruct the 3D structure of the scene from image collections and to recover the pose of these images. Taking unordered images as inputs, SfM outputs the precise image position and orientation, plus 3D reconstruction of the site as point cloud or model. Besides, high-resolution panoramas stitched from aerial photos are cost-effective substitutes for outdated low-resolution satellite images. As an incremental approach, SfM is suitable for processing construction site photos collected on an irregular basis along the time line. However, it requires redundant images in order to ensure "realism" of the scene. This is usually not assured when ground photos are taken by different personnel on a construction site. Therefore aerial images taken by UAV are used to materialize connecting and aligning scattered ground images. With a sequence of imageries taken on the construction site, the system implements the SfM procedure, starting from the first aerial imagery and taking it as the reference in subsequent processing of images taken by cell

The direct output of SfM includes the camera pose and a 3D point cloud of the object. A much denser 3D reconstruction of the object can be achieved using stereo matching subject to coplanar constraints [54]. To visualize the 3D reconstruction in *GoogleEarthWork*, a mesh model of the object is also produced. Further, panoramic images are generated by projecting original aerial photos onto the mesh model. An

*DOI: http://dx.doi.org/10.5772/intechopen.82008*

**2.1 Data collection and preprocessing**

management of large volumes of data in images and models. Sharing KML documents of limited size instead of original datasets also streamlines information distribution and improves computing efficiency performances.
