PowerPoint Presentation

Robert TaylorMehdi HerisAustin Troy, PhDUniversity of Colorado DenverPresented at the Partners in Community Forestry Conference 2015

How Urban Tree Canopy Regulates Microclimate and Urban Heat Islands: A Study from Denver and Baltimore

Why do we care about urban heat?

http://www.urban-climate-energy.com/urbanHeatIsland.htm

EPA

How does land cover change impact urban energy budget?Absorptivity, reflectivity, transmissivity, and emissivity. Different surfaces absorb and reflect different quantities in different wavelengths of the spectrum. Impervious surface absorbs lots of radiation in the short-wave portion Different surfaces shed heat (emissivity) at different rates Building canyons can impede release of long-wave energy to atmosphereConvective heat transferAnthropogenic heatLess evapotranspiration (see next slide)

Canyons work in two ways: trap radiation through bouncing against surface. Second, canyons can channelize and intensify wind, increases convective heat loss. Canyon effect can mitigate, but bouncing effect increases it. Convective heat transfer: when object heats up, it exchanges heat through air movement. The more complex the objects, the less convective heat loss. 3

How do trees work with urban heat?Evapotranspiration: e.g. 40,000 GPY for large oak. ET cools air by using heat from air to evaporate water and can reduce temp. Effects can be up to 9FDirect shade (well get to this later): in summer only 10-30% of suns E reaches area belowHigher emissivity and less stored heat

Evaporative cooling. Technical: latent heat loss. Veg stores less heat. Has more water in it, so can store as latent heat. 4

Note dotted lines. Surface temperature is more spatially variable than air temperature. Note heterogeneity of surface temps. Surface temperature is a proxy for air temperature. 5

Blue in city due to vegetation6

Note the turquoise color so close to downtown7

impervious surface to canopy ratio

Aster data. 5 Infra red thermal bands. Denver: used 4 scenes, Baltimore: 4 or 5. 2008-2014. Chose one day, based on best fit. 11 AM Denver. After noon Baltimore. 10

Highways have highest heat storage capacity. 11

North SideSouth Side

Surface Temperature and Morphology in Denver

Notice small variations can have significant impact on temperature. 12

If can edit, move earlier. Units is square meters. Daytime temps. Butterfly patter, One wing is hot, high impervious low canopy areas. Other is mid impervious but high canopy. Seems like only need small amount of tree cover (1500) to get big temperature impact. This is Denver13

Our project: Urban heat at two scales

http://thinkgreendegrees.com/wp-content/uploads/2012/08/urban-heat-island-comparison.gif

Research QuestionsHow does the heat island effect differ in a humid temperate city (Baltimore) versus and semi-arid zone city (Denver)?How does the spatial pattern of tree canopy mediate trees influence on the heat island effect and how does this effect vary between Denver and Baltimore?How can we calculate the amount of tree shade that directly hits buildings and does the proportion of shaded building area vary between Denver and Baltimore?

Question 1: Heat island in Denver vs. Baltimore

Tree Canopy ComparisonDenver has 31.8 square km of tree canopy coverage Baltimore has 48.4 square km of tree canopy coverage

18Surface Temperature: BaltimoreFrom ASTER Satellite

Surface Temperature: Denver

Nighttime August 2003Daytime June 2012

The canopied neighborhoods are cooler than prairie in daytime, because no shade in prairie. They are cooler than downtown in evening, because absorbed less heat. 19

Transect analysis

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trend of building area (vertical axis), distance from center (horizontal axis), average patch area radius of circles), and temperature (color)

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Patch area is vegetation21

trend of building area (vertical axis), distance from center (horizontal axis), average patch area radius of circles), and temperature (color)

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Transect analysisx axis: distance from downtowns23

24Denver Baltimore

Why?In eastern city surrounded by natural forest, outskirts cool down much quicker at night due to high emissivity relative to cityIn semi-arid location, trees are not endemic to outskirts, rather urbanization results in MORE trees than would otherwise be there. The fact that urbanized areas tend to go along with trees means that heat trapping effect of impervious area is largely offset by increase in tree cover relative to surrounding prairie. Exceptions: downtown, where tons of building area relative to trees; airport, where lots of impervious area

In day the shaded neighborhoods are cooler than then outskirtsIn the night, the shaded neighborhoods are cooler than downtown. They are moderated. 25

Question 2: Spatial patterns of trees and urban heat mitigation

Average patch circularityAt 500 m scale:Circularity of patch geometriescirRatio = (math.pi * 4* area) / math.pow (perimeter,2)

27Patch circularity(blue is low, red is high)

Each cell is 500x500. Change legend to patch circulatity 27

Patch edge/area ratioAt 500 m scale:Average edge/area ratio28Patch edge area ratio (blue is low, red is high)

Change legend to edge area ratio28

Patch area/patch envelope ratioAt 500 m scale:Average patch area/patch envelope ratio

29Patch area envelope ratio (blue is low, red is high)

Change legend. This ratio refers to how much of envelope the shape fills. Things with low value are more complex and irregular shapes. 29

Results of Correlations30Temperature 5th Jul 2014Temperature 29th Jun 2012Temperature 18th Jun 2005 (nighttime)Temperature 24th Aug 2009Patch density (number of patches)0.640.570.050.17Total patch area-0.39-0.27-0.300.02Patch average area-0.28-0.23-0.11-0.03Patch length0.390.41-0.120.16Patch circularity0.380.310.100.12Patch Length / area ratio0.440.350.180.11Patch Envelope Length / width ratio0.070.08-0.120.08Patch area to envelope area ratio-0.22-0.14-0.240.08Moran's I0.290.340.440.07

Temperature 5th Jul 2014Temperature 29th Jun 2012Temperature 18th Jun 2005 (nighttime)Temperature 24th Aug 2009Road area0.130.17-0.060.06Water area-0.14-0.250.25-0.01Grass area-0.040.06-0.360.06Parking area0.770.630.310.15Housing unit 20000.640.560.160.12Housing unit 20100.640.560.170.12Building area0.820.710.210.16Tree Canopy area-0.47-0.27-0.300.02Patch area to minimum bounding envelope area ratio-0.020.050.01-0.05Patch orientation0.210.150.070.21Minimum bounding geometry length to width ratio0.020.010.020.02

Gray= Nighttime temperature Yellow= Relatively high correlation values Orange= Statistically insignificant correlations

These are for Baltimore One of the temperature values is for nighttime and is highlighted with gray color. Relatively high correlation values are highlighted with yellow color. Statistically insignificant correlations are highlighted with red color. Allnighttime correlations are significant. Note high patch density is high in day, low at night. Indicates more dispersed and discrete tree cover. All for Baltimore. Similar table for Denver not here. These are univariate correlations30

Patch correlation trend analysis

Levelling off point around 5000 sq m. 31we measured correlation of temperature and patch-length/area-ratio when the patch average area increases

Green line is significant31

Results so far for BaltimoreEdginess has less of an impact on increasing temperatures for small patches than large patches of forest; influence increases until 5000 square meter patch sizeEffects of tree canopy pattern when controlling for impervious/ built area (R-squared ~ .78):Patch area decreases tempPatch density (means more, small patches) increases tempPatch length increases tempPatch circularity (associated more with individual crowns) increases tempPatch edge to area ratio increases tempCircularity and edge-area results may seem at odds, but they proxy different things

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Circularity represents small individual trees. Circularity and edge/area ratio results are at odds with each other. 32

Question 3: Quantifying tree shade hitting buildings: Denver vs. Baltimore

Analysis of shade based on LiDAR

6pm Shadow from Buildings & Canopy

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Video of lidar scene from far to close to illustrate use of data points35

Shade Effects Solar Angle & Azimuth

Shade Effects Integrated over time

9am6am12pm3pm6pm

Shade Effects Isolated & CombinedTreesBuildingsTrees & Buildings

3D Shade Approach: 8am

3D Shade Approach: 9am

Methods1) Data Processing2) Insolation Calculations3) Shade Calculations4) Insolation-Shade Integration

Data ProcessingInsolationCalculationsShade CalculationsInsolation-ShadeCalculationsData ProcessingStatistical ProcessingUnclassified LiDAR DataVector DataDEM BuildingsDEM DeciduousDEM ConiferousDSMSuns Position DataLAISolar Potential Grid Roof SurfaceShade Effect Grid SurfaceSolar Potential Post-Shade EffectAggregated Shade Effect per Apt. UnitResulting Statistical Relationships1234541

Total Shade ComparisonTotal Tree Shade : 4 hour interval (summed) * 3 days (June 15, July 15, August 15)

Roof-Tree Intersection Shade ComparisonRoof-Tree Intersection Shade : 4 hour interval (summed) * 3 days (June 15, July 15, August 15)

Conclusion and next stepsHeat island effect is very different in eastern and western USWestern cities surrounded by treeless lands tend to have more trees relative to natural surroundings than do eastern citiesSpatial pattern of tree canopy has a big impact on heat mitigation Tree shade varies between Denver and Baltimore: more overall tree shade in Baltimore, but more tree shade hitting buildings in Denver by farNext step: relate this to energy consumption data

Change message on compact. Actually compact associated with more heat. 44

Thanks to the Baltimore Ecosystem Study and the USDA Forest Services Northern Research Station and Northeastern Area State and Private Forestry Program for their support of this research Robert TaylorMehdi HerisAustin Troy, PhDUniversity of Colorado DenverAustin.troy@ucdenver.edu

Thanks! Questions?