## 3 Results
### Prediction of Total Imperviousness for New Urban Regions in 2057  
Method 2, as the more accurate method than method 1, was used to predict total imperviousness in this study. Population density projections in 2057 for three potential development areas (PDAs) were used to predict residential imperviousness by the linear regression model (Table 3). Residential imperviousness, as the main part of development in the PDAS, is expected to occupy 28.3%, 18.2%, and 24.7% area of Ripley Valley, Greater Flagstone, and Yarrabilba. Moreover, according to the non-residential impervious area per person (M = 12 m\({}^{2}\)), non-residential imperviousness is expected to be approximately 3.1%, 2%, and 2.7% in the PDAs (Table 4). Totally, this study predicted that total imperviousness would be around 31.4%, 20.2%, and 27.4% for the three PDAs. Results showed that more than 20% of area of the PDAs would be replaced with impervious surface area (ISA) in the future. Therefore, sustainable environmental management decisions should be taken to reduce adverse effects of the expected increase in the imperviousness on the ecosystem of these regions.  
Figure 7: Observed and estimated total imperviousness values derived from methods 1 and 2 for the 67 dense residential suburbs.  
Here, some sources of uncertainty which may affect the reliability of the predicted total imperviousness are discussed. First, there is uncertainty in the predicted residential imperviousness using the linear regression model (Table 3). The 95% confidence intervals were calculated to show the uncertainty interval for the predicted residential imperviousness. Detailed description to calculate 95% confidence interval for predicted values from regression models was discussed in, e.g., [PERSON] et al. (2015). The 95% confidence interval was predicted to range from 3.6% to 3.7% for the three PDAs (Table 4). Considering these prediction intervals, a range of total imperviousness for the three PDAs are presented in Table 4. For example, total imperviousness in the Yarrabilba was predicted to range from 23.8% to 31%. Second, uncertainty in population projections was yet another source of uncertainty in the predicted total imperviousness for the PDAs. While, it is difficult to quantify the uncertainty in estimates of population increases. Simple analysis showed how sensitive the predicted imperviousness could be to population projection uncertainties. For example, a 10% increase in population projection would lead to increase in the impervious area between 2% and 3.1% for the three PDAs. The last source of uncertainty source is related to the M ratio which was used to estimate non-residential imperviousness in the PDAs. Analysis showed that there is 45 m\({}^{2}\) of non-residential area per person in all 154 suburbs, because non-residential area in some of the suburbs was extremely high. Considering 45 m\({}^{2}\) would lead to overestimation of non-residential area, thus, our recommended method could present a low uncertain level of non-residential area for the predicted non-residential imperviousness in the PDAs. Due to the increased land value and population density, our estimate is likely to be the upper limit based on established dense residential suburbs in SEQ.