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cooling_in_urban_areas.py
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cooling_in_urban_areas.py
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"""
Code specific for the cool city model
"""
import pcraster as pcr
from ... import algorithm, checked_call2, validate
from .. import project
from ..io import IO
@checked_call2
def wrapper(project_file_pathname):
"""
Calculate cooling effect of vegetation and water on urban heat
island effect
:param str project_file_pathname: Name of project file
"""
configuration = project.configuration(project_file_pathname)
io = IO(configuration)
# Inputs
land_cover_pathname = configuration.input_raster_pathname(
"cooling_in_urban_areas", "land_cover"
)
roughness_length_pathname = configuration.input_table_pathname(
"cooling_in_urban_areas", "roughness_length"
)
wind_speed_pathname = configuration.input_raster_pathname(
"cooling_in_urban_areas", "wind_speed"
)
wind_class_pathname = configuration.input_table_pathname(
"cooling_in_urban_areas", "wind_class"
)
population_pathname = configuration.input_raster_pathname(
"cooling_in_urban_areas", "population"
)
built_up_pathname = configuration.input_table_pathname(
"cooling_in_urban_areas", "built_up"
)
uhi_reduction_lut_pathname = configuration.input_table_pathname(
"cooling_in_urban_areas", "uhi_reduction_lut"
)
trees_pathname = configuration.input_raster_pathname(
"cooling_in_urban_areas", "trees"
)
shrubs_pathname = configuration.input_raster_pathname(
"cooling_in_urban_areas", "shrubs"
)
grass_pathname = configuration.input_raster_pathname(
"cooling_in_urban_areas", "grass"
)
# Outputs
maximum_uhi_effect_pathname = configuration.output_raster_pathname(
"cooling_in_urban_areas", "maximum_uhi_effect"
)
potential_uhi_effect_pathname = configuration.output_raster_pathname(
"cooling_in_urban_areas", "potential_uhi_effect"
)
in_situ_cooling_effect_pathname = configuration.output_raster_pathname(
"cooling_in_urban_areas", "in_situ_cooling_effect"
)
actual_uhi_effect_pathname = configuration.output_raster_pathname(
"cooling_in_urban_areas", "actual_uhi_effect"
)
cooling_effect_pathname = configuration.output_raster_pathname(
"cooling_in_urban_areas", "cooling_effect"
)
land_cover = io.read_raster(land_cover_pathname)
roughness_length = pcr.lookupscalar(roughness_length_pathname, land_cover)
wind_speed = io.read_raster(wind_speed_pathname)
wind_speed = pcr.lookupscalar(wind_class_pathname, wind_speed)
population = io.read_raster(population_pathname)
built_up = pcr.lookupboolean(built_up_pathname, land_cover)
uhi_reduction = pcr.lookupscalar(uhi_reduction_lut_pathname, land_cover)
trees = io.read_raster(trees_pathname)
shrubs = io.read_raster(shrubs_pathname)
grass = io.read_raster(grass_pathname)
(
maximum_uhi_effect,
potential_uhi_effect,
in_situ_cooling_effect,
actual_uhi_effect,
cooling_effect,
) = function(
land_cover,
roughness_length,
wind_speed,
population,
built_up,
uhi_reduction,
trees,
shrubs,
grass,
)
io.write_raster(maximum_uhi_effect, maximum_uhi_effect_pathname)
io.write_raster(potential_uhi_effect, potential_uhi_effect_pathname)
io.write_raster(in_situ_cooling_effect, in_situ_cooling_effect_pathname)
io.write_raster(actual_uhi_effect, actual_uhi_effect_pathname)
io.write_raster(cooling_effect, cooling_effect_pathname)
def function(
land_cover,
roughness_length,
wind_speed_100m,
population,
built_up,
uhi_reduction,
trees,
shrubs,
grass,
):
"""
Calculate cooling effect of vegetation and water on urban heat
island effect
:param nominal_raster land_cover: Land cover
:param scalar_raster roughness_length: Roughness length for momentum
:param scalar_raster wind_speed_100m: Average wind speed at 100m height
:param scalar_raster population: Number of inhabitants per cell
:param boolean_raster built_up: Whether or not a cell is built-up
:param scalar_raster uhi_reduction: Reduction rates per land-cover class
:param scalar_raster trees: Percentage coverage by trees
:param scalar_raster shrubs: Percentage coverage by shrubs
:param scalar_raster grass: Percentage coverage by grass
:return: Tuple of
- Maximum UHI effect, ℃
- Potential UHI effect, ℃
- In-situ cooling effect of urban green and water, ℃
- Actual local UHI effect, ℃
- Cooling effect of urban green and water, ℃
:rtype: tuple of scalar rasters
"""
validate.greater_equal_than(population, 0.0)
validate.in_range(trees, 0.0, 1.0)
validate.in_range(shrubs, 0.0, 1.0)
validate.in_range(grass, 0.0, 1.0)
mask = pcr.defined(land_cover)
trees = pcr.ifthenelse(pcr.pcrand(pcr.pcrnot(pcr.defined(trees)), mask), 0, trees)
shrubs = pcr.ifthenelse(
pcr.pcrand(pcr.pcrnot(pcr.defined(shrubs)), mask), 0, shrubs
)
grass = pcr.ifthenelse(pcr.pcrand(pcr.pcrnot(pcr.defined(grass)), mask), 0, grass)
wind_speed_10m = (
wind_speed_100m
* pcr.ln(10.0 / roughness_length)
/ pcr.ln(100.0 / roughness_length)
)
# Smooth wind speed in 50m radius
wind_speed_10m = pcr.windowaverage(wind_speed_10m, 2 * 50)
validate.greater_equal_than(wind_speed_10m, -1e-6)
wind_speed_10m = pcr.ifthenelse(wind_speed_10m < 0, 0, wind_speed_10m)
population_10km = algorithm.windowtotal(population, 2 * 10000)
population_10km = pcr.ifthenelse(population_10km < 0, 0, population_10km)
maximum_uhi_effect = (
-1.605 + (1.062 * pcr.log10(population_10km)) - (0.356 * wind_speed_10m)
)
maximum_uhi_effect = pcr.ifthenelse(
maximum_uhi_effect < 0, 0, maximum_uhi_effect
) # RK: added for national calculation
validate.greater_equal_than(maximum_uhi_effect, 0)
green = trees + shrubs + grass
green = pcr.ifthenelse(green > 1, 1, green) # remove values above 1
built_up_corrected = pcr.ifthenelse(built_up, 1.0 - green, 0.0)
built_up_1km = algorithm.windowaverage(built_up_corrected, 2 * 1000)
built_up_1km = pcr.ifthenelse(built_up_1km < 0, 0, built_up_1km)
potential_uhi_effect = maximum_uhi_effect * built_up_1km
non_green = 1 - green
# Percentage reduction of the UHI effect of the land-cover type
reduction = trees * 0.5 + shrubs * 0.3 + grass * 0.2 + non_green * uhi_reduction
# validate.in_range(reduction, 0.0, 1.0)
reduction = pcr.ifthenelse(reduction < 0, 0, reduction)
in_situ_cooling_effect = potential_uhi_effect * reduction
reduction_30m = pcr.windowaverage(reduction, 2 * 30)
reduction_30m = pcr.ifthenelse(reduction_30m < 0, 0, reduction_30m)
actual_uhi_effect = potential_uhi_effect * (1.0 - reduction_30m)
cooling_effect = maximum_uhi_effect - actual_uhi_effect
validate.greater_equal_than(
[
maximum_uhi_effect,
potential_uhi_effect,
in_situ_cooling_effect,
actual_uhi_effect,
cooling_effect,
],
0.0,
)
return (
maximum_uhi_effect,
potential_uhi_effect,
in_situ_cooling_effect,
actual_uhi_effect,
cooling_effect,
)