# Changes in the Building Stock of Da Nang between 2015 and 2017
## 3 Data Description
### Data Structure  
Table 3 summarizes the attributes contained by the administrative (adm) and hexagonal (hex) datasets. Both datasets contain the absolute number of changes (c1 to c5, as defined in Table 2), the absolute number of buildings per year and type (t2015_1 to t2017_9, as defined in Table 1), as well as the absolute (nc) number of changes per building type in each ward and hexagon. The relative number of changes (pc) denotes the share of the changes in one building type compared to the total number of changes in the reference area. For the administrative dataset, the results can also be summarized by district, using the respective attributes (dist_ID or district). As one suggestion for further spatial analyses, the hexagon dataset additionally contains an attribute named dist_mean, which defines the Euclidean distance of each hexagon from the historic city center in Hai Chau district. This will be discussed in Section 3.4.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Attribute** & **Description** & **adm** & **hex** & **Source** \\ \hline province & name of the province & x & & GADM \\ dist\_ID & id of the district & x & & GADM \\ district & name of the district & x & & GADM \\ ward\_ID & id of the ward & x & & GADM \\ ward\_en & name of the ward without special characters & x & & GADM \\ area & area of the ward in square kilometers & x & & GIS analysis \\ per\_cover & \% of ward area covered by satellite & x & & GIS analysis \\ hex\_ID & id of the hexagon & & x & GIS analysis \\ dist\_mean & mean distance from the historic city center & & x & GIS analysis \\ c1 & no of buildings with no-change & x & x & Satellite image \\ c2 & no. of new buildings & x & x & Satellite image \\ c3 & no. of changed buildings (same type) & x & x & Satellite image \\ c4 & no. of upgraded buildings (other type) & x & x & Satellite image \\ c5 & no. of demolished buildings & x & x & Satellite image \\ c\_sum & no. of all changed buildings & x & x & c2 + c3 + c4 + c5 \\ t2015\_1 & no. of “basic” buildings in 2015 & x & x & Satellite image \\ t2015\_2 & no. of “local”’s pbehouse” buildings in 2015 & x & x & Satellite image \\ t2015\_3 & no. of “bungalow” buildings in 2015 & x & x & Satellite image \\ t2015\_4 & no. of “villa-type” buildings in 2015 & x & x & Satellite image \\ t2015\_5 & no. of “apartment, local” buildings in 2015 & x & x & Satellite image \\ t2015\_6 & no. of “apartment, modern” buildings in 2015 & x & x & Satellite image \\ t2015\_7 & no. of “hall” buildings in 2015 & x & x & Satellite image \\ t2015\_8 & no. of “outbuilding” buildings in 2015 & x & x & Satellite image \\ t2015\_9 & no. of “special” buildings in 2015 & x & x & Satellite image \\ t2015\_sum & no. of all buildings in 2015 & x & x & sum(t2015) \\ t2017\_1 & no. of “basic” buildings in 2017 & x & x & Satellite image \\ t2017\_2 & no. of “local-type shophouse” buildings in 2017 & x & x & Satellite image \\ t2017\_3 & no. of “bungalow” buildings in 2017 & x & x & Satellite image \\ t2017\_4 & no. of “villa-type” buildings in 2017 & x & x & Satellite image \\ t2017\_5 & no. of “apartment, local” buildings in 2017 & x & x & Satellite image \\ t2017\_6 & no. of “apartment, modern” buildings in 2017 & x & x & Satellite image \\ t2017\_7 & no. of “small” buildings in 2017 & x & x & Satellite image \\ t2017\_8 & no. of “outbuilding” buildings in 2017 & x & x & Satellite image \\ t2017\_9 & no. of “special” buildings in 2017 & x & x & Satellite image \\ t2017\_sum & no. of all buildings in 2017 & x & x & Satellite image \\ \hline \hline \end{tabular}
\end{table}
Table 3: Attributes of the two shapefiles.  
Accordingly, the dataset does not contain any data related to individuals collected during the field campaigns. The attributes are purely a result of the geospatial analyses described in the methodology section. This aggregation grants that no user can calculate the original building or plot geometries, nor their exact type or location.