Environmental considerations

Environmental considerations (penalties for traffic, noise, town, no river, no forest) are possible due to the creation of pseudo tags during processing OSM data by spatial SQL queries in brouter.sql. During this processing, roads are extended by a 32 m buffer creating 64 m wide lines. Then it is calculated what percentage of such line is at a specific distance to a noise source or within a forest, for example. The percentage is converted to a factor and the factor is assigned to a class. Ways that pass through different environments and are represented by a single OSM way can be problematic because the class is always based on the average environment along an entire OSM way. For traffic, calculations are on another level of complexity.

noise_class

For proximity of noisy roads (secondary and higher). The noise factor represents the proportion of a road’s buffer area that lies within the 64-meter buffer of noisy roads. This proportion is reduced:

• for motorways and trunk roads with max speed < 105 by 1.5
• for primary roads 2 times
• 3 times if maxspeed is 75 - 105 for primary and secondary
• other secondary roads 5 times

noise_class is roughly proportional to the noise factor:

noise_factor	noise_class
< 0.1	1
< 0.25	2
< 0.4	3
< 0.55	4
< 0.8	5
ELSE	6

To be classified as noise class 6, a way must be less than 13 m on average from the middle of the carriageway of a motorway with a maximum speed exceeding 105. For a class 5, the distance must be up to 35 meters. (1 - noise_factor) * 64 m for a given class determines the distance

highway	maxspeed	max noise_class
motorway,trunk	> 105	6
motorway,trunk	105	5
motorway,trunk	75	5
primary	> 105	4
primary	105	4
primary	75	3
secondary	> 105	3
secondary	105	3
secondary	75	2

river_class

OSM data recognized as river:

• waterway: river, canal
• natural: water (except wastewater)

Waterways have 32 m wide buffers. Water areas have 77 m wide buffers.

river_see	river_class
< 0.1	1
< 0.3	2
< 0.5	3
< 0.8	4
< 0.9	5
ELSE	6

forest_class

OSM data recognized as forest:

• landuse: forest, allotments, flowerbed, orchard, vineyard, recreation_ground, village_green
• leisure: garden, park, nature_reserve

No forest buffers are used.

Imagine you trace the way with a pencil drawing lines 62 meters wide. Then estimated_forest_class=6 corresponds to the case that at least 98% of the line is in the woodland. This number is called a green factor.

green_factor	forest_class
< 0.1	NULL
< 0.2	1
< 0.4	2
< 0.6	3
< 0.8	4
< 0.98	5
ELSE	6

town_class

Town_class is determined by population data from OSM.

population	town_class
< 80 k people	1
< 150 k people	2
< 400 k people	3
< 1 million people	4
< 2 million people	5
> 2 million people	6

traffic_class

(modified copy from the sql file). OSM data used to estimate the traffic:

• population of towns (+ distance from position to the towns)
• size of industrial areas (landuse=industrial) and distance to them. Not considered: solar & wind farms.
• airports international
• motorway and trunk road density - traffic on motorways decreases traffic on primary/secondary/tertiary. Calculated on a grid (100 km^2)
• density of highways (tertiary and higher) calculated on a grid (100 km^2). Traffic decreases when more such roads are available. Exceptions: near junctions between motorways and other roads the traffic increases on these roads.
• mountain-ranges calculated as density of peaks > 400 m traffic is generally on highways in such regions higher as only generated by the local population or industrial areas
• calculate traffic from the population (for each segment of type primary secondary tertiary)
• SUM of (population of each town < 100 km) / ( town-radius + 2500 + dist(segment-position to the town) ** 2 )
• town-radius is calculated as sqrt(population)