# Changes in the Building Stock of Da Nang between 2015 and 2017
## 3 Data Description
### Administrative Level  
The dataset <DaNang_buildings_adm_UTM49N> contains the changes in the building stock aggregated by wards. These represent the official administrative units, so this dataset is best compatible with other socio-demographic data, such as the official Vietnam Population and Housing Census released by the General Statistics Office of Vietnam [15]. However, it must be kept in mind that, in particular, the wards at the edges are not entirely covered by the satellite images, so absolute numbers have to be interpreted with care. For this reason, the attribute table of the administrative dataset contains an additional attribute, \"per_cover\", which tells the percentage of each ward's area inside the AOI. It is illustrated in Figure 13 in the Appendix B, which highlights the ten wards which are only covered by 70% or less of the satellite images. Figure 5 shows the dominance of new construction activities over demolitions in the observed time between 2015 and 2017. Except for the already very densely built-up wards of An Hai Dong, Binh Hien, and Phuoc Ninh, which are located near the city center, and the rural wards of Hoa Vang district in the western outskirts of the city, all parts of Da Nang have experienced a considerable increase in building numbers, mostly exceeding 500 new buildings per ward. In contrast, the number of demolitions is visibly lower throughout the city. Over 90% of all wards range between 10 and 200 demolished buildings. Of course, these numbers are strongly dependent on the size of a ward. For this reason, the attribute \"area\" is contained in the dataset to calculate the absolute changes per square kilometer (c1/area or c5/area), as shown in Figure 6, which gives a more representative picture for each ward. It highlights the increase in Hoa Minh in the north and the relative high demolitions in Hai Chau district, representing the historic city center with its extreme building density. Another method of calculating a spatially uncorrelated representation of changes is given by the hexagons described in Section 3.4. \begin{table}
\begin{tabular}{c c c c c} \hline
**Attribute** & **Description** & **adm** & **hex** & **Source** \\ \hline nc\_t1 & net change in “basic” buildings & x & x & t2017\_1-t2015\_1 \\ nc\_t2 & net change in “local-type shophouse” buildings & x & x & t2017\_2-t2015\_2 \\ nc\_t3 & net change in “bungalow” buildings & x & x & t2017\_3-t2015\_3 \\ nc\_t4 & net change in “villa-type” buildings & x & x & t2017\_4-t2015\_4 \\ nc\_t5 & net change in “apartment, local” buildings & x & x & t2017\_5-t2015\_5 \\ nc\_t6 & net change in “apartment, modern” buildings & x & x & t2017\_6-t2015\_6 \\ nc\_t7 & net change in “hall” buildings & x & x & t2017\_7-t2015\_7 \\ nc\_t8 & net change in “outbuilding” buildings & x & x & t2017\_8-t2015\_8 \\ nc\_t9 & net change in “special” buildings & x & x & t2017\_9-t2015\_9 \\ nc\_all & net change in all buildings & x & x & t2017\_sum-t2015\_sum \\ pc\_t1 & \% of change in “basic” buildings & x & x & nc\_t1/t2015\_1 \\ pc\_t2 & \% of change in “local-type shophouse” buildings & x & x & nc\_t2/t2015\_2 \\ pc\_t3 & \% of change in “bungalow” buildings & x & x & nc\_t3/t2015\_3 \\ pc\_t4 & \% of change in “villa-type” buildings & x & x & nc\_t4/t2015\_4 \\ pc\_t5 & \% of change in “apartment, local” buildings & x & x & nc\_t5/t2015\_5 \\ pc\_t6 & \% of change in “apartment, modern” buildings & x & x & nc\_t6/t2015\_6 \\ pc\_t7 & \% of change in “hall” buildings & x & x & nc\_t7/t2015\_7 \\ pc\_t8 & \% of change in “outbuilding” buildings & x & x & nc\_t8/t2015\_8 \\ pc\_t9 & \% of change in “special” buildings & x & x & nc\_t9/t2015\_9 \\ pc\_all & \% of changed buildings based on all buildings in 2015 & x & x & c\_sum/t2015\_sum \\ \hline \end{tabular}
\end{table} 
Table 3: _Cont._Figure 7 demonstrates further spatial patterns revealed in the data: It shows that multifamily apartments largely increased between 2015 and 2017, but with spatially distinct patterns.