based on Mobile Transect Measurements - METEO FRANCE · Relationship between Land Use and Microclimate based on Mobile Transect Measurements Kathrin Häb1, Ariane Middel2, Benjamin

Relationship between

Land Use and

Microclimate based on

Mobile Transect Measurements

Kathrin Häb1, Ariane Middel2, Benjamin L. Ruddell3

1 Computer Graphics and HCI Group, TU Kaiserslautern, Germany 2 School of Geographical Sciences and Urban Planning, Arizona State University, USA 3 Fulton School of Engineering, Arizona State University, USA

Häb et al.: Relationship between Land Use and Microclimate based on Mobile Transect Measurements 9th International Conference on Urban Climate (ICUC9) July 20-24, 2015; Toulouse, France

2 July 21, 2015

Introduction

Possible research topics:

o Canopy-Layer Urban Heat Island

o Park Cool Islands

o Impact of certain land-use configurations on the urban microclimate

o Derive implications about thermal comfort

Relate observations to surrounding land

use and land cover

Mobile transect measurements in urban

climatology result in a complex data

set:

o Spatially dependent, multivariate, time-

varying, and afflicted with uncertainties


3 July 21, 2015

Background: TraVis Data preprocessing Geospatial Visualization

Data Analysis and Exploration

Häb et al. (2015): TraVis – A Visualization Framework for Mobile Transect Data Sets in an Urban Microclimate Context. In Proceedings of the IEEE PacificVis, Hangzhou, China, 2015.


4 July 21, 2015

Background: TraVis

May 08, 2014 14:40 LST

Surface Temperature [°C]

Relative Humidity [%]

14.50

17.23

19.96

22.70

25.43

28.16

Air Temperature [°C]

24.77

26.11

27.46

28.80

30.15

31.49

17.76

26.21

34.66

43.11

51.56

60.01 Image created with TraVis

1 m

2 m

2 m

1 m

0 m


5 July 21, 2015

Background: TraVis

May 08, 2014 14:40 LST

Surface Temperature [°C]

Relative Humidity [%]

14.50

17.23

19.96

22.70

25.43

28.16

Air Temperature [°C]

24.77

26.11

27.46

28.80

30.15

31.49

17.76

26.21

34.66

43.11

51.56

60.01 Image created with TraVis

1 m

1 m

0 m

http://www.cameronjwheeler.com/


6 July 21, 2015

Materials and Methods

April 10,

20142

Source Area Computation for Microclimate Measurements within the Urban Canopy Layer

AAG Annual Meeting 2014

Introduction

Which signals of its environment does a sensor capture?

Wind direction

Radiometer source area: Dependent on the FoV of a sensor

and its height

Source areas for passive scalars or fluxes: Complex to determine!

The source area concept: How much of its

spatial context can a sensor see?

„Rule of Thumb“: 𝑟 = 𝑧𝑚 ∗ 100 More complex techniques,

taking wind direction into account


7 July 21, 2015


• mini-SAM-2 (Schmid 1994): Source area for a passive scalar

(e.g., Air Temperature)

Schmid, H.P. (1994): Source Areas for Scalars and Scalar Fluxes. Boundary Layer Meteorology 67 (3), p. 293-318.


8 July 21, 2015


Observations: 21 transect runs in 3 seasons, recorded in Gilbert, AZ


9 July 21, 2015




10 July 21, 2015




11 July 21, 2015

Correlating LULC Fractions in the Fetch with Air Temperature (𝑧𝑚 =1m)

𝑅2

𝑅2

data set

14

:40

LST

1

5:5

0 L

ST

17

:40

LST

1

8:3

9 L

ST

20

:18

LST

0

7:2

0 L

ST

08

:40

LST

1

1:2

6 L

ST

May 10, 2014

May 08, 2014

06

:59

LST

0

9:4

5 L

ST

11

:58

LST

1

6:4

6 L

ST

18

:33

LST

Sep 15, 2014

06

:22

LST

0

9:3

7 L

ST

12

:25

LST

1

5:0

6 L

ST

17

:37

LST

1

8:1

1 L

ST

21

:23

LST

0

7:1

2 L

ST

Feb 05, 2015

14

:40

LST

1

5:5

0 L

ST

17

:40

LST

1

8:3

9 L

ST

20

:18

LST

0

7:2

0 L

ST

08

:40

LST

1

1:2

6 L

ST

06

:59

LST

0

9:4

5 L

ST

11

:58

LST

1

6:4

6 L

ST

18

:33

LST

0

6:2

2 L

ST

09

:37

LST

1

2:2

5 L

ST

15

:06

LST

1

7:3

7 L

ST

18

:11

LST

0

7:1

2 L

ST

21

:23

LST

data set

May 08, 2014

May 10, 2014

Sep 15, 2014

Feb 05, 2015

„Rule of Thumb“: 𝑟 = 𝑧𝑚 ∗ 100 Mini-SAM-2 (Schmid, 1994)


12 July 21, 2015

Discussion and Limitations

o Both approaches do not seem suitable for observations within the

urban canopy layer o They have not been designed for this setting

o They do not take the three-dimensional environment into account

o Parameters needed for the Mini-SAM-2 partially difficult to retrieve o Obhukov length, friction velocity, standard deviation of lateral wind: Not enough

data to estimate these parameters

o Need to take data into account, which have not been measured in-situ

o For the example, they have been estimated based on the final source area‘s shape

o Both approaches are computationally inexpensive o Allow for computing a source area at each location on a route


13 July 21, 2015

Conclusion and Future Work

Future Work:

o Include the three-dimensional geometry into source area modelling

o Validate results using more complex dispersion / flow models

o Use relationship between land cover fractions and microclimate for

extrapolation of measurements / statistical modelling

An interface for the exploration of mobile measurement data sets

was developed;

We are currently investigating appropriate techniques for the interactive (real-time!) and accurate exploration of a sensor‘s

field-of-view


14

Thank you.

Questions?

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Acknowledgements: The authors wish to thank the Arizona State University Environmental Remote Sensing and Geoinformatics Lab (ERSG) for providing the NAIP data set (additional support was furnished by the Gilbert F. White Environment and Society endowment. Source data: National Agriculture Imagery Program (NAIP), http://www.fsa.usda.gov). This work was supported in part by the NSF Grant SES-0951366, Decision Center for a Desert City II: Urban Climate Adaptation, NSF EaSM Program EF-1049251, the NSF LTER Program BCS-1026865, the Salt River Project grant to ASU, Alan and Sandra Ruffalo, and the Power Ranch Homeowners Association.

July 21, 2015

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based on Mobile Transect Measurements - METEO FRANCE · Relationship between Land Use and Microclimate based on Mobile Transect Measurements Kathrin Häb1, Ariane Middel2, Benjamin