**2.3 Constraints identification in earthwork planning**

Analytical simulation or optimization for construction operations planning requires knowledge of practical constraints on the construction site so as to make a sufficient problem definition. In rough grading, a certain volume of earth needs to be excavated at one area and filled at another. Accessibility issues during project execution become the primary concern for earthwork construction

**Figure 2.** *Integrated project data management and visualization.*

planners, especially when only limited accesses between site areas are available at the very beginning of the project. Moreover, earthmoving operations need to be executed in a safe, efficient manner, accommodating many concurring construction activities on site.

These site constraints can be categorized into quantitative constraints and qualitative constraints, as listed in **Table 4**. A quantitative constraint can be defined with a number; by contrast, qualitative constraints cannot be quantitatively represented in *GoogleEarthWork*. The two basic constraints in earthwork construction planning are (1) cut/fill volume takeoff and assignment and (2) site accessibility and haul path planning. Besides, in order to improve project performance in terms of cost and duration, a solid plan needs to consider more factors. For instance, swell/shrinkage factors account for earth volume changes during excavation and compaction. These factors have a direct impact on quantity takeoff. The haul distance, road surface condition, and slope impact earthmoving productivity. Site layout design and concurring construction activities also potentially introduce spatial constraints. For example, certain areas on site are reserved for trenching and utility installation, hence remain temporarily unpassable to trucks in earthmoving.

*GoogleEarthWork* assists project planners in identifying abovementioned constraints more efficiently through information integration and visualization. Among them, cut/fill volumes can be readily acquired from a dense 3D reconstruction of the construction site. The slope of the terrain can be evaluated based on the 3D reconstruction if necessary. For instance, in **Figure 3**, the volume of the stockpiles can be precisely estimated from 3D reconstruction using Pix4D as presented in **Figure 3(a)**. The relative positioning accuracy is evaluated using the width of the paved road in front of the house. The average width out of 20 measurements is 8.008 m. Detailed measurements can be found in **Figure 3(b)**. Compared with the actual width 8 m, the average error is about 8 mm, and the standard deviation is around 29 mm. Note, the absolute positioning accuracy was not evaluated in this research due to unavailability of ground truth references. Nonetheless, the visualization effect of *GoogleEarthWork* proves that positioning accuracy is sufficient and acceptable for construction planning and monitoring purposes.

Obviously, site photos provide valuable information to identify qualitative constraints. The accessibility issues, site layout constraints, and road conditions can also be assessed with high-resolution panoramic images and/or ground photos on computer. As these images are geo-located, *GoogleEarthWork* enables rapid identification of constraints at a particular spot. From **Figure 4**, it is straightforward to define one access road (pattern fill), four storage areas (solid lines), and three stockpiles (dashed lines) on the construction site directly from high-resolution panoramic image overlay.


**141**

**Figure 3.**

**Figure 4.**

*Google Earth Augmented for Earthwork Construction Planning*

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

*(b) relative positioning accuracy evaluation.*

**3. Earthwork optimization and planning**

Given identified quantitative and qualitative constraints, the analytical method

presented in [56, 57] will be introduced for automated earthwork construction planning. This method provides an analytical approach to plan rough grading operations while making problem formulation and modeling more intuitive and simplified by the use of material flow networks. To a certain extent, it can potentially eliminate temporal-spatial conflicts (such as trucks are not allowed to haul on ungraded areas) in generation of an optimized yet more practically feasible work plan. The two-phase approach splits *earthwork optimization* and *earthwork planning* into two distinct, logically connected problems. The two problems were commonly combined in previous methods; thus representing time-dependent constraints such

*Qualitative constraints identification in GoogleEarthWork: geo-relationship between accesses, stockpiles, storage area, and the building identified from high-resolution panoramic images stitched from aerial photos.*

*GoogleEarthWork features demonstration: (a) earth volume survey from automated 3D reconstruction and* 

**Table 4.**

*Typical quantitative and qualitative constraints for earthwork projects.*

*Google Earth Augmented for Earthwork Construction Planning DOI: http://dx.doi.org/10.5772/intechopen.82008*

#### **Figure 3.**

*Geographic Information Systems and Science*

tion activities on site.

able to trucks in earthmoving.

monitoring purposes.

panoramic image overlay.

• Cut/fill volume for each area • Soil swell/shrinkage factors

• Traveling distance/time between areas

*Typical quantitative and qualitative constraints for earthwork projects.*

planners, especially when only limited accesses between site areas are available at the very beginning of the project. Moreover, earthmoving operations need to be executed in a safe, efficient manner, accommodating many concurring construc-

These site constraints can be categorized into quantitative constraints and qualitative constraints, as listed in **Table 4**. A quantitative constraint can be defined with a number; by contrast, qualitative constraints cannot be quantitatively represented in *GoogleEarthWork*. The two basic constraints in earthwork construction planning are (1) cut/fill volume takeoff and assignment and (2) site accessibility and haul path planning. Besides, in order to improve project performance in terms of cost and duration, a solid plan needs to consider more factors. For instance, swell/shrinkage factors account for earth volume changes during excavation and compaction. These factors have a direct impact on quantity takeoff. The haul distance, road surface condition, and slope impact earthmoving productivity. Site layout design and concurring construction activities also potentially introduce spatial constraints. For example, certain areas on site are reserved for trenching and utility installation, hence remain temporarily unpass-

*GoogleEarthWork* assists project planners in identifying abovementioned constraints more efficiently through information integration and visualization. Among them, cut/fill volumes can be readily acquired from a dense 3D reconstruction of the construction site. The slope of the terrain can be evaluated based on the 3D reconstruction if necessary. For instance, in **Figure 3**, the volume of the stockpiles can be precisely estimated from 3D reconstruction using Pix4D as presented in **Figure 3(a)**. The relative positioning accuracy is evaluated using the width of the paved road in front of the house. The average width out of 20 measurements is 8.008 m. Detailed measurements can be found in **Figure 3(b)**. Compared with the actual width 8 m, the average error is about 8 mm, and the standard deviation is around 29 mm. Note, the absolute positioning accuracy was not evaluated in this research due to unavailability of ground truth references. Nonetheless, the visualization effect of *GoogleEarthWork* proves that positioning accuracy is sufficient and acceptable for construction planning and

Obviously, site photos provide valuable information to identify qualitative constraints. The accessibility issues, site layout constraints, and road conditions can also be assessed with high-resolution panoramic images and/or ground photos on computer. As these images are geo-located, *GoogleEarthWork* enables rapid identification of constraints at a particular spot. From **Figure 4**, it is straightforward to define one access road (pattern fill), four storage areas (solid lines), and three stockpiles (dashed lines) on the construction site directly from high-resolution

> • Access to/on the site • Site layout from the design • Other construction activities

• Road condition

**Quantitative constraints Qualitative constraints**

**140**

• Unit cost

**Table 4.**

*GoogleEarthWork features demonstration: (a) earth volume survey from automated 3D reconstruction and (b) relative positioning accuracy evaluation.*

#### **Figure 4.**

*Qualitative constraints identification in GoogleEarthWork: geo-relationship between accesses, stockpiles, storage area, and the building identified from high-resolution panoramic images stitched from aerial photos.*
