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Fig.12. P40/R30, Landsat 7 ETM+ 4/8/2000, Colored T s image (300K:Blue to 306K:Red,307K:light blue, 308.5K:yellow, and 310K: pink). Center to the east of the plain.When we scan the entire area of interest, we find that the surface temperature in thesoutheast region is higher. A type of “heat island” can be recognized in the following T simage (Figure 13).Fig.13. P40/R30, Landsat 7 ETM+ 4/8/2000, T s image (Black and white, entire snake riverplain)78
We conclude that this “heat island” is a local phenomenon, occurring during the early springimage, and that our “hot” pixel of 302.7 K from a more typical part of the image is valid. Thisvalue for T hot is probably not a good value to apply for the southeast region. It would bebest to separate this region into a separate <strong>SEBAL</strong> application. In our application, we willinclude this region, but we will ignore the ET estimates for this region since it is outside ourarea of interest.After selecting a “hot” pixel, T hot should be recorded along with its coordinates.79
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SEBALSurface Energy Balance Algorit
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6. Tables for surface albedo comput
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δ declination of the earth radians
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INTRODUCTION1. BACKGROUNDLand manag
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THE THEORETICAL BASIS OF SEBAL1. OV
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The surface emissivity is the ratio
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• Reference evapotranspiration, E
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Figure 3. Flow Chart of the Net Sur
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2. The reflectivity for each band (
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and ET are specified for the two ex
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To complete step 2, model F06_surfa
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D. Choosing the “Hot” and “Co
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irrigated crops near Kimberly, Idah
Page 27 and 28: where; u * is the friction velocity
Page 29 and 30: Weather stationu, z x, z om, u *H f
Page 31 and 32: Note: An alternative method used by
Page 33 and 34: where;⎛ 2 ⎞⎜1+ x(0.1m)Ψ = 2
Page 35 and 36: where; ET inst is the instantaneous
Page 37 and 38: Figure 6 shows an example of a dail
Page 39 and 40: 1. If there is some cloud cover in
Page 41 and 42: • For all other formats (includin
Page 43 and 44: On the main page, select Type in Pa
Page 45 and 46: These values for z om can vary by r
Page 47 and 48: Appendix 3Reference Evapotranspirat
Page 49 and 50: and click on “Open”3. Provide t
Page 51 and 52: 5. Describe weather station and wea
Page 53 and 54: 8. Save the output file using a nam
Page 55 and 56: 4. Go to the Viewer tool and view t
Page 57 and 58: Appendix 5Time Issues Around Weathe
Page 59 and 60: 2. What time interval does the data
Page 61 and 62: The wind speed is 3.4 m/s for the 1
Page 63 and 64: Table 6.3. ESUN λ for Landsat 5 TM
Page 65 and 66: Table 6.6. Typical albedo values.Fr
Page 67 and 68: 4. Make a first guess for T cold by
Page 69 and 70: Fig.3. P40/R30, Landsat 7 ETM+ 4/8/
Page 71 and 72: Fig.5. P40/R30, Landsat 7 ETM+ 4/8/
Page 73 and 74: We open the image or subset image a
Page 75 and 76: Now, we look at the northwest area
Page 77: (2) The regional weather or soil co
Page 81 and 82: Part 1: using the manual iteration
Page 83 and 84: Part 2: Using the automatic iterati
Page 85 and 86: Appendix 9SAVI and LAI for Southern
Page 87 and 88: equation for G. The following are e
Page 89 and 90: and for 24-hours:Gwater = 0.9 Rn -
Page 91 and 92: The Stability of the AtmosphereAppe
Page 93 and 94: Appendix 12The SEBAL Mountain Model
Page 95 and 96: where; t is the standard clock time
Page 97: N. Momentum Roughness LengthThe mom
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