# **Box 1: Linking spatial data on road networks with engineering estimates of quality**

The Malawi National Road Authority (NRA) has compiled a GIS database of the roads network. In addition, the NRA is regularly implementing HDM4 surveys to collect information on overall road conditions. While the geo referenced road network data only include basic information such as road name and class, the non geo-referenced HDM4 compiles a rich dataset on pavement roughness (IRI), daily traffic volumes (AADT), and designated speed. Mapping road quality information into the geographic database of road placement is important for identifying specific locations where road quality is impinging on traffic flows as well as locations potentially facing congestion. However, as both databases were compiled independently and without coordination, they cannot be merged directly. A spatial linking algorithm - the “SIS” (Special Information System Ver.6.1) - was developed by the Oriental Consultants Co. in Japan to integrate these two databases. The process is outlined below.

First, the HDM4 location information, which is specifically the starting/ending points of each road segment in GPS longitude & latitude, is overlaid on the GIS road links with the same projection in order to confirm which road links should be identified for the HDM4 links.

Second, the HDM4 locations are revised when the starting/ending points are not on the GIS road link. This process requires engineering decision consulting extra information, such as road name, and road length.

|**Procedure for data linkage**|
|---|
|**1. Indication of the starting/ending points of**<br>**HDM4 road segments into the GIS road link**|
|**2. Revision of HDM4 points to match to the GIS**<br>**road link**|
|**3. Creation of new GIS road shape files**<br>**connecting HDM4 points**|
|**4. Addition of HDM4 information to the new GIS**<br>**road shape files**|

Third, after the revision process being completed, new road links with the same starting/ending points are created using the tracing function of GIS application. Finally, other HDM4 information is added to the newly-created GIS road link data.

12. The combined data from the GIS and HDM systems provide useful insights on road quality. Table 1 summarizes these findings. Consider for example road conditions and traffic flows across different parts of the network. Main roads are relatively wide (1.7 lanes on average) smooth (4.4 roughness) and paved (76%). The Average Daily Traffic (ADT) on these roads is 507 vehicles, with over 40% being motorized. In contrast, secondary roads are rougher and narrower with ADTs of 90 vehicles. Most tertiary roads are unpaved and rough and have lower traffic volumes. The average design road speeds are 57 kilometer per hour for main roads, 38 for secondary roads, and 34 for tertiary roads.

**Table 1: Physical road conditions, GIS+HDM4, by road class**

|Road class|Total road<br>length, km|number of lanes,<br>average|<br>Road roughness,<br>average|% of paved|Average Daily<br>Traffic (ADT)|Motorized<br>transport|
|---|---|---|---|---|---|---|
|Main|1,931.6|1.7|4.4|75.7|506.9|204.9|
|Secondary|1,361.0|1.0|6.9|12.9|90.2|38.3|
|Tertiary|1,509.2|1.0|6.6|5.5|67.3|11.8|
|District|149.5|1.1|5.2|33.6|182.7|73.1|
|Other|3,577.1|1.2|6.1|33.9|223.1|65.8|
|Total|8,528.4|1.2|5.9|35.7|237.9|83.5|

Note: The sample excludes unmatched road segments. Data Source: Road network GIS data, and the HDM4

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