Institute of Industrial Science, The University of Tokyo, Japan

Remote sensing of environment and disaster laboratory

Evaluating Thermal Comfort in Cityand its Relation to Socio Economic Activities
Noriko OKAMURA(1), Wataru TAKEUCHI

(1)

(2)

, Shin AKATSUKA

and Kei OYOSHI(1)Institute of Industrial Science, University of Tokyo, Japan (2)Yamanashi Institute of Environmental Science, Japan(3)(3)JAXA, Japan

Abstract: In this study, we developed methods for calculating Wet Bulb Globe Temperature (WBGT) and Wind Chill Temperature (WCT) from Multi-functional Transport Satellite (MTSAT) data (IR1~IR2), and tried toimprove the methods, so that we can evaluate thermal comfort in Asia-Pacific region by satellite remote sensing in near real time. As a result, it was found that our WBGT formula could express the tendency of WBGT
change and detect the risk value (WBGT over 25). That enabled making thermal comfort image mappings in 4km resolution. About formula of WCT, we needed further study to get accuracy. In addition, as one of the indicesof socio economic activity, we examined the relationship between WBGT and GDP per capita of each country in this study. As a result it was found that high WBGT countries tend to have low GDP per capita. From thisresearch, hourly evaluation of thermal comfort in whole hot area and its visualization became possible, and the database from this calculation would be useful in analyses about relationships between thermal comfort andsocio economic activities.

Introduction Urban environmental assessment is one of important issues for remote sensing now. For example, heat island is one of the urban problems in cities. For evaluating

its effect, algorithms for land surface temperature retrieval from satellite have been developed[Oyoshi et. Al, 2009]. However, human’s health and thermal comfort are affected by not
only the temperature but also other factors including humidity, wind speed and solar radiation. So we usually use composite temperatures, which are indexes expressing sensible
climate, for assessing environment. In this study, we developed methods for calculating WBGT(for hot season) and WCT(for cold season). It is useful for evaluating thermal comfort incity life in large area in real time. In addition, regional thermal comfort’s relevance to various statistical data about social life could be examined.

What is WBGT (Wet Bulb Globe Temperature)?

What is WCT (Wind Chill Temperature)?

･ estimate the effect of temperature, humidity and radiation on humans･ calculate the dangers from winter winds and freezing temperatures･ determine appropriate exposure levels to high temperature and prevent from heat disorder

WBGT (outdoor) = 0.7Tw + 0.2Tg + 0.1Td

WCT =13.12 +0.6215･T -11.37･𝑽𝟎.𝟏𝟔 +0.3965･T･𝑽𝟎.𝟏𝟔
Where T=air temperature(℃) / V=wind speed(km/h)

Table1:Risk level of heat disorder
WBGT(℃)
Level*>31
Danger
28-31
Alert
25-28
Advisory
21-25
Caution

Where Tw=wet bulb temperature
Tg=globe temperature
Td=dry bulb temperature(C.P.Yaglou and D.Minard, 1957)

Simple estimate formula:

WBGT = 0.7Tw + 0.4Td – 1.4(Siple and Passel, 1941)

Table2: Risk level of frostbite*by Japan Amateur Sports Association(1994)

Cf. Tg and Td,”Tg=1.45Td-7.09” (Niigata Agricultural Research Institute,2004)

Methodology

WCTLevel-10 - -27

Low-28 - -39

Risk: exposed skin can freeze in 10 to 30 minutes-40 - -47

High risk: exposed skin can freeze in 5 to 10 minutes-48 - -54

Very high risk: exposed skin can freeze in 2 to 5 minutes< Data used in this study >Surface data

WBGT at the stations(Tokyo, Taipei)

Surface data

WCT at the stations

Selecting data satisfying the following conditions

Surface data downloaded from NNDC Climate Data Online(Sapporo, Urumqi)(http://hurricane.ncdc.noaa.gov/pls/plclimprod/cdomain.abb
rev2id)Station①Tokyo ②Taipei ③Sapporo ④Urumqi

Selecting data satisfying the following conditions･it is clear･WBGT>20

Latitude･air temperature<5℃, wind speed>4.8km/h･WCT<0MTSAT data
(IR1, IR2)

Regression analysis

WBGT = f (IR1 , (IR1-IR2), (IR1 − IR2)2 )35.683

43.8

Longitude 139.767 141.329 121.517

87.65

hourly43.06

3 hourly Hourly④②①330360 DOY

3 hourly

2011/1/1ー 2011/12/31

MTSAT thermal infrared data(IR1 and IR2 channels)archived by IIS,Channel Wavelength
The University of Tokyo
IR110.5-11.5μm(http://webgms.iis.uIR211.5-12.5μmtokyo.ac.jp/)

WCT = f (IR1 , (IR1-IR2), (IR1 − IR2)2 )Fig.1 Flow chart of making relational expressions

WBGT= 0.0209IR1 +2.58(IR1-IR2) -0.272(IR1-IR2)2 +16.1
WCT= 0.0788IR1 +1.95(IR1-IR2) -0.149(IR1-IR2)2 -29.6

25.033

Data
Table3 :station dataRegression analysis

Results The following relational expressions were derived as the results.

③IR3
Table4: MTSAT technical IR4
specifications
VIS･･･(1)･･･(2)Spatial Res.
4km
4km

6.5-7.0 µm
4km
3.5-4.0 µm
4km
0.55-0.90 µm 1km

Fig.2～3 show annual change of WBGT(in Tokyo) and WCT(in Sapporo). “satellite” is calculated from (1)(2).
30302525201515WCTWBGT2010RMSE(WBGT>25､clear):0.980
RMSE(all data):13.7

50-5

RMSE(T<5℃, V>4.8km/h):4.01
RMSE(all data):17.3

130

60

90120150

180210240270

Fig.2 WBGT annual change in Tokyo(2011)

1050-5300

330

in-situ

360 DOY

satellite

13060

90120150

180210240270300-10-15Fig.3 WCT annual change in Sapporo(2011)

in-situsatellite

Fig.5 shows averageannual days (2007~2012)
when WBGT reaches 25.
Table5:the number of days incities
LAT LON
CITY0Fig.4 WBGT daily mean map(2012.8.1)

100

200

300

366

Sapporo43.1 141.3

185

Tokyo

35.7 139.8

225

Seoul

37.6 127.0

244

Taipei25.0 121.5

Bangalore

13.0 77.58

362

Bali

8.22 115.8

365

235

Fig.5 Average annual days
when WBGT takes critical value

Conclusion●It can be said that WBGT formula(1) can be applied to the data when WBGT is over 25.(Fig.2) We
could evaluate thermal comfort in hot season by number of days when WBGT takes critical value(over25) of each city by satellite remote sensing.(Fig.5)●WBGT image mappings can be made in 4km resolution.(Fig.4)●As the result of the examination into relation between WBGT and GDP per capita, it can be said thathigh WBGT countries tend to have low GDP per capita.(Fig.6)

Future works●further study for getting accuracy of WCT formula●further analyses of regional thermal comfort’s relevance to various statistical data about social lifeCircle
Size: amount of GDP per capitaColor: height of average WBGT

aAustralia/ｂJapan/ｃHongKong/ｄKorea/eTaiwan/ｆRussia/ｇNorthKorea/ｈChina/iNepal/
ｊPakistan/ｋBangladesh/ｌPhilippines/ｍIndia/
ｎThailand/oMyanmar/ｐIndonasia/ｑVietnam/
ｒSingapore

Fig.6 Relation between WBGT and GDP per capita
REFERENCESOyoshi, K., Takeuchi, W. and Tamura, M. (2009). High- frequency land surface temperaturemonitoring with MTSAT. In: proceed. annual meeting of JSPRS
Noriko Okamura, Wataru Takeuchi, Shin Akatsuka and Kei Oyoshi, 2012. Evaluating thermal
comfort in city life by satellite remote sensing and in-situ measurements. 33rd Asianconference on remote sensing (ACRS)Shin Akatsuka, Kei Oyoshi and Wataru Takeuchi, 2010. Mapping of precipitable water using
MTSAT data. 31st Asian conference on remote sensing (ACRS): Hanoi, Vietnam, 2010 Nov.
2.
Wataru Takeuchi, Kei Oyoshi and Shin Akatsuka, 2012. Super-resolution of MTSAT land
surface temperature by blending MODIS and AVNIR2. Asian Journal of Geoinformatics, 12(2)Tsuyoshi Kinouchi, A Study on Thermal Indices for the Outdoor Environment(in Japanese),
2001.The Meteorological Society of JapanFor further details, contact: Noriko Okamura, Ce-505, 6-1, Komaba 4-chome, Meguro, Tokyo 153-8505 JAPAN (URL: http://wtlab.iis.u-tokyo.ac.jp/

E-mail: nokamura@iis.u-tokyo.ac.jp)