# Geotechnical Property Modeling and Construction Safety Zoning Based on GIS and BIM Integration
## 3 Implementation on the Peshawar Region Borehole Data
### Geotechnical Parameter Map Generation and Validation  
A geodatabase was created in the ArcMap software by incorporating boreholes information before applying a geostatistical approach for interpolation. The 20 borehole dataset used in this study is arranged in a mesh grid pattern that provides at minimum four input data points for cell interpolation. The data provided by consultants include the coordinates of each borehole. The spatial analysis tool in the ArcMap GIS software has been utilized for geotechnical mapping of the study area. The digital mapping employing the GIS tool is based on the procedure explained in Figure 2. The digital map presenting the field geotechnical parameter SPT-N value of the area is shown in Figure 5a, while Figure 5b,c illustrates the variation of laboratory test parameters; plasticity index and unconfined compressive strength. The obtained maps show the variation of the SPT-N value, plasticity index, and unconfined compressive strength all around the study area. The GIS tools successfully managed and represented the geotechnical information of the area. The representation in the form of digital maps instead of showing in complex tabular form or excel spreadsheet makes it user-friendly and easy to understand. Furthermore, the distribution of the underground information with the geographical location in this way is an innovative approach and provides ready-to-use geotechnical information for the whole area instead of only borehole information that shows geotechnical information along one dimension. The results show that the GIS technique adequately maps the geotechnical parameters that can help the planners and construction manager in the critical decision about safe construction site selection before initiating construction. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Location ID** & **Depth Top** & **Depth Bottom** & **Geology** \\ \hline \multirow{4}{*}{BH1} & 0 & 7 & silty sand \\  & 7 & 13 & clay \\  & 13 & 18.2 & silt \\  & 18.2 & 26.3 & silty sand \\  & 26.3 & 27.7 & weathered rock \\  & 27.7 & 35 & weathered rock \\ \hline \multirow{4}{*}{BH2} & 0 & 4.7 & silt \\  & 4.7 & 15 & clay \\  & 15 & 18 & silt \\  & 18 & 24.6 & silt \\  & 24.6 & 27.9 & silty sand \\ \hline \multirow{4}{*}{BH3} & 0 & 4.6 & silt \\  & 4.6 & 8 & clay \\  & 8 & 9.7 & silt \\  & 9.7 & 14.3 & silty sand \\  & 14.3 & 19.7 & silt \\  & 19.7 & 27.2 & silt \\  & 27.2 & 30.3 & sand \\  & 30.3 & 34.6 & sand \\  & 34.6 & 37.7 & weathered rock \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Detailed information of some boreholes layer along with the depth. To verify the accuracy of the developed map using the proposed method, additional 9 values of SPT, plasticity index, and UCS at the same depth was collected and comparing the actual test results (laboratory tests results for UCS and Plasticity index and in-situ test results for SPT) with the corresponding values on the developed maps (Figure 5). The actual value collected from the consultants was compared with the generated results using the previous 20 boreholes data. The results are presented in Figure 6 where measured value along the x-axis shows the actual test results and predicted value along the y-axis shows the corresponding value on the developed map. Figure 5: Digital map showing the distribution of geotechnical parameters over the study area (**a**) in-situ parameter SPT-N distribution; (**b**) Laboratory test parameter plasticity index distribution over the study area; and (**c**) unconfined compressive strength distribution. The root-mean-square error (RMSE) that asses the model and tells about the accuracy of the predicted value from the measured one. The RMSE is calculated as 0.16, 0.23, and 0.33 for SPT, plasticity index, and UCS, which shows the generated results are very accurate.