## 4 User Notes  
In this section, the authors give some recommendations for working with the dataset. The number and the geometries of a large part of the \"Basic\" buildings is the result of a modelling approach informed by the descriptive statistics derived for the sample of manually digitized building footprints. Therefore, the authors advise against reliance on the numbers of the \"Basic\" building class as more than estimates but to utilize the area statistics for more reliable statistical analyses. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Building Type** & **1** & **2** & **3** & **4** & **5** & **6** & **7** & **8** & **All Buildings** \\ \hline Mean absolute derivation in m & 0.78 & 0.83 & 0.84 & 1.28 & 3.83 & 5.11 & 1.54 & 4.23 & 1.21 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Accuracy of building heights of 2015 using 837 reference values. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Column Name** & **Content** & **Valid for 2008–2009** & **Valid for 2015** \\ \hline \multirow{2}{*}{Model} & Value “1” indicates that the object results from the splitting of a large & \multirow{2}{*}{X} & \multirow{2}{*}{X} \\  & \"Basic\" building segment according to the LUT in Section 2.6. & & \\ \hline \multirow{2}{*}{Change} & Indicates the type of change between 2008–2009 and 2015. The value & & \\  & ranges from 1–6 for 2008–2009, and from 1–5 for 2015 (see Table 3). & & \\ \hline \multirow{4}{*}{2015\_ty} & Indicates the building archetype by code for the year 2015. The value & & \\  & ranges from 1–9 (0 in case a building that existed in 2008–2009 & & \\  & was demolished). & & \\ \hline \multirow{4}{*}{2009\_ty} & Indicates the building archetype by code for 2008/2009. The value & & \\  & ranges from 1–9 (0 in the case that a building was newly built & \\  & between 2008/2009 and 2015). & & \\ \hline \multirow{4}{*}{2015\_name} & Indicates the building archetype by its short name for the year 2015. & & \\  & & & \\ \hline \multirow{4}{*}{2009\_name} & Indicates the building archetype by its short name for the year 2009. & & \\  & & & & \\ \hline \multirow{4}{*}{Height} & Corrected mean object height in m (corresponds to the & \\  & & 2015 buildings). & & \\ \hline Shape\_Leng & Total perimeter of the object in m. & & \\ \hline Shape\_Area & Total area of the object in m\({}^{2}\). & & & \\ \hline UID & Unique identifier (Integer) of an object feature. & & \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Attributes of the dataset (EO4 Kigali.shp). Structured Query Language (SQL) can be used to analyze the attributes of the dataset. The following list of exemplary SQL queries might help data users to retrieve additional results and become familiar with the dataset:  
* Which buildings existed in 2015? * SELECT FROM EO4 Kigali.shp WHERE (F2015_ty > 0)
* Which buildings existed in 2008-2009? * SELECT FROM EO4 Kigali.shp WHERE (Change = 1 OR Change = 3 OR Change = 4 OR Change = 6)
* Which/how many \"Bungalow\" buildings existed in 2015? * SELECT FROM EO4 Kigali.shp WHERE (F2015_ty = 3)
* For which buildings were no changes detected between 2008-2009 and 2015? * SELECT FROM EO4 Kigali.shp WHERE (Change = 1)
* Which/how many buildings were demolished between 2008-2009 and 2015? * SELECT FROM EO4 Kigali.shp WHERE (Change = 6)
* To include buildings that were rebuilt/renovated to a new building type:
* SELECT FROM EO4 Kigali.shp WHERE (Change = 6 OR Change = 4)
* Which/how many were newly built/rebuilt between 2008-2009 and 2015? * SELECT FROM EO4 Kigali.shp WHERE (Change = 2 OR Change = 3 OR Change = 4 OR Change = 5); (Remark: with Change = 3 buildings are included that might only be renovated or slightly changed). * Which/how many of object geometries of the \"Basic\" buildings were modelled and do therefore not represent the actual delineation to adjacent buildings?