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Format pseudo tags docs

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Manuel Fuhr 2023-10-18 21:23:59 +02:00
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docs/developers/environmental_considerations_and_pseudo_tags.md
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@ -1,7 +1,9 @@
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 https://github.com/abrensch/brouter/blob/master/misc/scripts/mapcreation/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. 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 https://github.com/abrensch/brouter/blob/master/misc/scripts/mapcreation/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.
### consider_noise, noise_penalty ### consider_noise, noise_penalty
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 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 motorways and trunk roads with max speed < 105 by 1.5
- for primary roads 2 times - for primary roads 2 times
- 3 times if maxspeed is 75 - 105 for primary and secondary - 3 times if maxspeed is 75 - 105 for primary and secondary
@ -10,6 +12,7 @@ For proximity of noisy roads (secondary and higher). The noise factor represents
Noise class is roughly proportional to the noise factor: Noise class is roughly proportional to the noise factor:
noise_factor = noise class noise_factor = noise class
- < 0.1 = '1' - < 0.1 = '1'
- < 0.25 = '2' - < 0.25 = '2'
- < 0.4 = '3' - < 0.4 = '3'
@ -17,7 +20,7 @@ noise_factor = noise class
- < 0.8 = '5' - < 0.8 = '5'
- ELSE = '6' - 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 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
**Max noise class:** **Max noise class:**
| Max speed | Motorway, trunk |Primary|Secondary | | Max speed | Motorway, trunk |Primary|Secondary |
@ -26,15 +29,17 @@ To be classified as noise class 6, a way must be less than 13 m on average from
| 105 |5 |4 |3 | | 105 |5 |4 |3 |
| 75 |5 |3 |2 | | 75 |5 |3 |2 |
### consider_river, no_river_penalty ### consider_river, no_river_penalty
OSM data recognized as river: OSM data recognized as river:
- waterway: river, canal - waterway: river, canal
- natural: water (except wastewater) - natural: water (except wastewater)
Waterways have 32 m wide buffers. Water areas have 77 m wide buffers. Waterways have 32 m wide buffers. Water areas have 77 m wide buffers.
river_see = river class river_see = river class
- < 0.17 = '1' - < 0.17 = '1'
- < 0.35 = '2' - < 0.35 = '2'
- < 0.57 = '3' - < 0.57 = '3'
@ -43,7 +48,9 @@ river_see = river class
- ELSE = '6' - ELSE = '6'
### consider_forest, no_forest_penalty ### consider_forest, no_forest_penalty
OSM data recognized as forest: OSM data recognized as forest:
- landuse: forest, allotments, flowerbed, orchard, vineyard, recreation_ground, village_green - landuse: forest, allotments, flowerbed, orchard, vineyard, recreation_ground, village_green
- leisure: garden, park, nature_reserve - leisure: garden, park, nature_reserve
@ -52,6 +59,7 @@ 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. 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 green_factor = forest class
- < 0.1 = NULL - < 0.1 = NULL
- < 0.2 = '1' - < 0.2 = '1'
- < 0.4 = '2' - < 0.4 = '2'
@ -60,12 +68,12 @@ green_factor = forest class
- < 0.98 = '5' - < 0.98 = '5'
- ELSE = '6' - ELSE = '6'
### consider_town, town_penalty ### consider_town, town_penalty
Town_class is determined by population data from OSM. Town_class is determined by population data from OSM.
Class Class
- 1 = 50-80 k people - 1 = 50-80 k people
- 2 = 80-150 k people - 2 = 80-150 k people
- 3 = 150 - 400 k people - 3 = 150 - 400 k people
@ -74,8 +82,10 @@ Class
- 6 = > 2 million people - 6 = > 2 million people
### consider_traffic, traffic_penalty ### consider_traffic, traffic_penalty
(modified copy from the sql file). (modified copy from the sql file).
OSM data used to estimate the traffic: OSM data used to estimate the traffic:
- population of towns (+ distance from position to the towns) - population of towns (+ distance from position to the towns)
- size of industrial areas (landuse=industrial) and distance to them. Not considered: solar & wind farms. - size of industrial areas (landuse=industrial) and distance to them. Not considered: solar & wind farms.
- airports international - airports international
@ -83,5 +93,5 @@ OSM data used to estimate the traffic:
- 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. - 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 - 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) - 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 ) - 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) - town-radius is calculated as sqrt(population)