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Surface Heat Balance Analysis by using ASTER and Formosat-2 data

Surface Heat Balance Analysis by using ASTER and Formosat-2 data. Soushi Kato Department of Earth Sciences, Earth Dynamic System Research Center, National Cheng Kung University 2008. 3. 11. Introduction. Estimation of surface heat balance in urban area

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Surface Heat Balance Analysis by using ASTER and Formosat-2 data

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  1. Surface Heat Balance Analysis by using ASTER and Formosat-2 data Soushi Kato Department of Earth Sciences, Earth Dynamic System Research Center, National Cheng Kung University 2008. 3. 11

  2. Introduction Estimation of surface heat balance in urban area helpful to understand the causes of heat island effect Using Remote Sensing data useful to obtain spatial pattern RS data with high spatial resolution and wide spectral coverage are suitable to heat balance estimation

  3. ASTER and Formosat-2 ASTER VNIR Formosat-2 Visible & NIR 3 band 15m resolution SWIR TIR 6 band 5 band 30 m 90 m Visible & NIR 4 band 8 m & 2 m resolution False-color images around NCKU, Taiwan (NIR, Green,Red)

  4. Surface Heat Balance Net radiation Short- and longwave radiation Sensible heat Surface-atmosphere temperature difference Latent heat Evapotranspiration H LE Rn G A Surface Ground heat Surface-subsurface temperature difference Anthropogenic heat Energy consumption Rn + A = H + LE + G Sensible heat flux increase → Heat island phenomenon

  5. Storage Heat Flux (DG) Ground heat (G) Anthropogenic heat (A) Difficult to obtain through a wide area Net radiation Sensible heat Latent heat DG = G – A = Rn – H – LE Rn H LE [W/m2] G A • Combine G and A • Estimated by Rn, H and LE Ground heat Anthropogenic heat Based on the method for ground measurement (e.g. Oke et al., 1999) Rn H LE DG > 0 ⇒Heat storage Storage heat flux DG DG < 0⇒Heat discharge

  6. Net Radiation (Rn) Estimation Rn = (1 ｰa) Rs + es RL↓ｰ RL↑ RL↓ RL↑ a : Albedo Rs Reflectance(Liang, 2000) a es Rs: Solar radiation(W/m2) RL: Longwave radiation (W/m2) = eisTi4 (Stefan-Boltzmann’s law) Ta: Atmospheric temperature(K) Ts :Surface temperature(K) es: Surface emissivity (absorptance) (Ogawa et al., 2003) ea : Atmospheric emissivity (Prata, 1996) Atmospheric temperature(K) Relative humidity(%)

  7. Sensible Heat Flux (H) Estimation Ts – Ta ra H =rCp Ta Bulk resistance approach ra Ts r : Air density(kg/m3) Cp: Specific heat of air at constant pressure(J/kg K) Ts:Surface temperature(K) Ta: Atmospheric temperature(K) ra: Aerodynamic resistance(s/m) Wind speed(m/s) Roughness length(m)Surface type (Brutsaert, 1982; Kondo, 1994; Yasuda, 1995)

  8. Latent Heat Flux (LE) Estimation es* – ea ra+ rs rCp g LE = ea ra rs Bulk resistance approach es* r : Air density(kg/m3) Cp: Specific heat of air at constant pressure(J/kg K) es*: Saturation vapor pressure(hPa) ea: Vapor pressure(hPa) g : Psychrometric constant (hPa/k) ra : Aerodynamic resisntance (s/m) rs : Stomatal resistance(s/m) (Nishida et al., 2003) Surface temperature(K) Air temperature(K) Solar radiation(W/m2) Minimum rs(s/m) Surface type Air temperature(K) Relative humidity(%)

  9. Data Used 0 5km false color (NIR:Green:Red) Study area Tainan, Taiwan Satellite data ASTER 2000 / 3 / 6 Formosat-2 2004 / 7 / 12 Meteorological data Meteorological Station Tainan 2000 / 3 / 6

  10. Surface Classification Map Derived from Maximum likelihood method and manual correction Formosat-2 Urban Road Water Bare soil Short grass Tall grass Bush Forest

  11. 0 1km Comparison of Classification Maps Surface classification map around Tainan Station ASTER Formosat-2 Roads and vegetations are distinguished more clearly

  12. Heat Fluxes by ASTER & Formosat-2 Sensible heat H Net radiation Rn Latent heat LE 190 360 W/m2 -5 120 W/m2 0 90 W/m2 Storage heat DG 40 360 W/m2

  13. Further Study • Usage of ASTER and Formosat-2 data acquired on the same (at least closer) dates • 2-m resolution pan-sharpened Formosat-2 image • ASTER 15m Formosat-2 8m Formosat-2 2m

  14. Thank you for your attention.

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