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Atmospheric Acoustic Remote Sensing - Chapter 5 potx

Atmospheric Acoustic Remote Sensing - Chapter 1 ppt

Atmospheric Acoustic Remote Sensing - Chapter 1 ppt

... 34(7): 10 01 10 27.Singal SP (19 97) Acoustic remote- sensing applications. Springer-Verlag, Berlin, 405 pp.3588_C0 01. indd 10 11 /20/07 5 :17 :38 PM© 2008 by Taylor & Francis Group, LLCxviii Atmospheric ... Phased-Array Frequency Range 10 95 .1. 4 Dish Design 11 05 .1. 5 Designing for Absorption and Background Noise 11 15 .1. 6 Rejecting Rain Clutter 11 25 .1. 7 How Much Power Should Be Transmitted? 11 43588.indb ... Methods 10 04 .14 Summary 10 3References 10 3 Chapter 5 SODAR Systems and Signal Quality 10 55 .1 Tra nsducer and A nt enna Combinations 10 55 .1. 1 Speakers and Microphones 10 55 .1. 2 Hor ns 10 85 .1. 3...
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Atmospheric Acoustic Remote Sensing - Chapter 2 potx

Atmospheric Acoustic Remote Sensing - Chapter 2 potx

... TABLE 2. 1Proles of CT 2 and CV 2 from Moulsley et al. (1981)z (m) CV 2 (m4/3s 2 ) CT 2 (K 2 m 2/ 3)46 3.1 ì 10 2 6.31 ì 10460 2. 5 ì 10 2 6.0ì10467 2. 2 ì 10 2 5.0ì10481 2. 1 ì 10 2 4.0ì10495 ... 10 2 4.0ì10495 2. 0 ì 10 2 3.0ì104109 2. 1 ì 10 2 2 .21 ì 104137 2. 2 ì 10 2 1.51 ì 104193 1.9 ì 10 2 8.0ì105 24 2 1.5 ì 10 2 5.0ì105The SODAR frequency was 20 48 Hz, beamwidth 9, and T = 12C.â 20 08 ... areEEÔƯƠƠƠƠảàààààCCCCCVTVT 2 32 2 2 197 022 .,.,/1VViriRPRTgz 2 163 dd1 (2. 21) 2. 6 MONIN-OBOUKHOV LENGTHThe cascade theory predicts that when F = 0 there is no turbulent energy. From (2. 19) this...
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Atmospheric Acoustic Remote Sensing - Chapter 3 ppt

Atmospheric Acoustic Remote Sensing - Chapter 3 ppt

... identify small-scale land surface characteristics. Acta Acoustica 87: 731737 . 35 88_C0 03. indd 53 11/20/07 4 :39 : 43 PM© 2008 by Taylor & Francis Group, LLC 36 Atmospheric Acoustic Remote Sensing In ... andAPPeyĐâăăăÃạáákCTCcTV 13 11 3 222220 033 076// ááyMMPL 83 21 23 1 13 20 53 20 3 520 033 /////.dLTkLCTTCcV222076ÔƯƠƠƠƠảààààà PPan-Naixian (20 03) argues that ... thatcTs . (3. 2)Allowing for T being the temperature in K, and that the speed of sound at 0°C is 33 2ms–1,cT T() ( . ) , 33 2 1 0 001661$ ms (3. 3) 35 88_C0 03. indd 27 11/20/07 4 :37 : 13 PM©...
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Atmospheric Acoustic Remote Sensing - Chapter 4 ppt

Atmospheric Acoustic Remote Sensing - Chapter 4 ppt

... (4. 38)3588_C0 04. indd 97 11/20/07 5:00: 24 PM© 2008 by Taylor & Francis Group, LLC96 Atmospheric Acoustic Remote Sensing 4. 10 FREQUENCY-DEPENDENT FORM OFTHE ACOUSTIC RADAR EQUATIONThe acoustic ... FourJay 44 0-8 speaker at 3 kHz with a 1.2-m diameter dish having a focal length of 580 mm.3588_C0 04. indd 61 11/20/07 4: 57:05 PM© 2008 by Taylor & Francis Group, LLC88 Atmospheric Acoustic Remote ... , , .FIGURE 4. 44 A step-chirp signal having M = 5 frequency steps.3588_C0 04. indd 101 11/20/07 5:00:37 PM© 2008 by Taylor & Francis Group, LLC58 Atmospheric Acoustic Remote Sensing cal....
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Atmospheric Acoustic Remote Sensing - Chapter 5 potx

Atmospheric Acoustic Remote Sensing - Chapter 5 potx

... (m)100090080000202040–40–40–20–20–60–60700600 50 04003002001001 1 .5 2 2 .5 3 3 .5 4 4 .5 5 5. 5 6Frequency (kHz)Height (m)1000900800700600 50 04003002001001 1 .5 2 2 .5 3 3 .5 4 4 .5 5 5. 5 6FIGURE 5. 27 SNR versus ... (m)AeroVironment 4000RISØ 450 0 50 3 10Metek PCS200 0-6 4 with 1290 MHz RASSSalford 1674 64 5 15 Scintec SFAS WINDTESTKWK 254 0–4 850 64 9 5 358 8_C0 05. indd 140 11/20/07 4:24: 35 PM© 2008 by Taylor ... 10203040 50 60708090100z/L 50 00100200300400Data availability (%)Height z (m)128 Atmospheric Acoustic Remote Sensing 5. 5 LOSS OF SIGNAL IN NOISEOne of the principal problems of ground-based remote sensing...
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Atmospheric Acoustic Remote Sensing - Chapter 6 pdf

Atmospheric Acoustic Remote Sensing - Chapter 6 pdf

... s–1) 6 –4 –2–22–44 6 62 4 6 172 Atmospheric Acoustic Remote Sensing TABLE 6. 1List of parameters for the Metek SODARParameter Description ValuefT(Hz) Transmitted frequency 167 4UsPulse ... estimator:SNimimP21200180 160 140120100Height (m)80 60 4020–15 –10 –5 0Along-beam Velocity (m/s)51015FIGURE 6. 6 The spectra of Figure 6. 5 shown as a contour plot.3588_C0 06. indd 165 11/20/07 4:18:27 ... 190 11/20/07 4:20: 56 PM© 2008 by Taylor & Francis Group, LLC1 86 Atmospheric Acoustic Remote Sensing HFFQHFFQ12``uvuvcos sin sinsin cos sin (6. 61)where R is the beam...
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Atmospheric Acoustic Remote Sensing - Chapter 7 docx

Atmospheric Acoustic Remote Sensing - Chapter 7 docx

... International Symposium on Acoustic Remote Sensing. 3588_C0 07. indd 211 11/20/ 07 4: 17: 06 PM© 2008 by Taylor & Francis Group, LLC208 Atmospheric Acoustic Remote Sensing 7. 9.1 RANGEThe maximum ... SODAR.RADARtransmitterRADARreceiver Acoustic arrayFIGURE 7. 6 The layout of the Metek RASS.Wind Profiler Acoustic Acoustic Acoustic AcousticFIGURE 7. 7 A RASS conguration which uses the best of four acoustic antennas, ... downstream.FIGURE 7. 5 The Metek MERASS.3588_C0 07. indd 205 11/20/ 07 4:16:52 PM© 2008 by Taylor & Francis Group, LLC1 97 7RASS SystemsRadio acoustic sounding systems (RASSs) are remote- sensing systems...
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Atmospheric Acoustic Remote Sensing - Chapter 8 (end) pot

Atmospheric Acoustic Remote Sensing - Chapter 8 (end) pot

... 09.15< 98 dB Scale 98 96949290 88 86 84 82 80 78 7674<72100200FIGURE 8. 13 The transition from stable boundary layer to convective boundary layer. The vertical scale is height in m.3 588 _C0 08. indd ... turbulence is suppressed 3 588 _C0 08. indd 217 11/20/07 4:15:14 PM© 20 08 by Taylor & Francis Group, LLC224 Atmospheric Acoustic Remote Sensing 3. Arrays of acoustic remote sensing instruments can ... provide the necessary acoustic refractive index data on a continuous basis over a representative time scale. 02:15 02:30 02:45 03:00> 98 >72 98 96949290 88 86 84 82 80 78 767402:0001:3001:1501:0000:4500:3000:1510020001:45dB...
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Wastewater Purification: Aerobic Granulation in Sequencing Batch Reactors - Chapter 5 potx

Wastewater Purification: Aerobic Granulation in Sequencing Batch Reactors - Chapter 5 potx

... in gure 5. 16, incompleteaerobicgranulationwasobservedinSBRsrunatthedischargetimesof10, 15, and20 minutes, while successful aerobic granulation was only achieved at the dischargetime of 5 minutes. ... 767–771.Yu,H.Q.,Tay,J.H.,andFang,H.H.P.2001.Therolesofcalciuminsludgegranulationduring UASB reactor start-up.Water Res 35: 1 052 –1060.FIGURE 5. 21 FilamentousPSobservedinaerobicgranules,scalebar=3µm. 53 671_C0 05. indd 84 10/29/07 7: 15: 46 AM© 2008 ... strategy for rapid and stable aerobic granulation in both small- and large-scale sequencing batch reactors (SBRs). This 53 671_C0 05. indd 69 10/29/07 7: 15: 18 AM© 2008 by Taylor & Francis Group,...
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A Practical Guide to Particle Counting for Drinking Water Treatment - Chapter 5 potx

A Practical Guide to Particle Counting for Drinking Water Treatment - Chapter 5 potx

... case of online particle counting, trending the grab-sample datawith other plant parameters will add to its value. If these data are available in a usable file format that can be imported into ... prior to eachuse. Certainly an acid washer and particle- free storage area would be ideal, but theseare usually not necessary for 2- m particle counting. It is a good idea to keep the particle ... data handling is a cumbersome task. Anynumber of approaches are available for organizing grab-sample data, and this makes a standardized approach difficult. Hence, none of the manufacturers has...
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High Performance Computing in Remote Sensing - Chapter 7 potx

High Performance Computing in Remote Sensing - Chapter 7 potx

... Group, LLC142 High- Performance Computing in Remote Sensing experiments was Linux Fedora Core, and MPICH was the message-passing libraryused (see http://www-unix.mcs.anl.gov/mpi/mpich). 7. 3.2 Hyperspectral ... architectures.© 2008 by Taylor & Francis Group, LLC144 High- Performance Computing in Remote Sensing TABLE 7. 2Execution Times (in Seconds) and Performance Ratios Reported for the Homogeneous Algorithms ... scores are slightly increased with regard to those obtained for HeteroCOM© 2008 by Taylor & Francis Group, LLC136 High- Performance Computing in Remote Sensing Figure 7. 1 Communication framework...
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Image Processing for Remote Sensing - Chapter 5 pdf

Image Processing for Remote Sensing - Chapter 5 pdf

... SizeFDL-OSS 3791 3. 75% 3812 17.91% 7603 6.21% 23 Â 23FDL-ARS 26 95 2.66% 352 8 16 .58 % 6223 5. 08% 7 Â 7FFL-ARS 2181 2. 15% 3376 15. 86% 55 57 4 .54 % 5 Â 5 C.H. Chen /Image Processing for Remote Sensing ... the two original 5- lookC.H. Chen /Image Processing for Remote Sensing 66641_C0 05 Final Proof page 124 3.9.2007 2:06pm Compositor Name: JGanesan124 Image Processing for Remote Sensing © 2008 by ... Section 5. 2 defines the change-detectionproblem in multi-temporal remote- sensing images and focuses attention on unsupervisedtechniques for multi-temporal SAR images. Section 5. 3 presents a multi-scale...
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Signal Processing for Remote Sensing - Chapter 5 pdf

Signal Processing for Remote Sensing - Chapter 5 pdf

... HOSVD 85 5 .5. 1.1 HOSVD Definition 85 5 .5. 1.2 Computation of the HOSVD 86 5. 5.1.3 The (rc, rx, rt)-rank 87 5. 5.1.4 Three-Mode Subspace Method 88 5. 5.2 HOSVD and Unimodal ICA 88 5. 5.2.1 HOSVD ... 77 5. 3.2.3 Subspace Method Using SVD–ICA 79 5. 3.3 Application 80 5. 4 Multi-Way Array Data Sets 83 5. 4.1 Multi-Way Acquisition 84 5. 4.2 Multi-Way Model 84 5. 5 Multi-Way Array Processing 85 5 .5. 1 ... (sensors)1234 5 6780 50 100 150 200 250 300Time (samples) 350 400 450 50 0(a) Original signal subspace SDistance (sensors)1234 5 6780 50 100 150 200 250 300Time (samples) 350 400 450 50 0(b)...
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Signal Processing for Remote Sensing - Chapter 9 potx

Signal Processing for Remote Sensing - Chapter 9 potx

... LLC. for each 9- by -9 pixel group, it is equivalent to simply filling the regions of missing data with 9- by -9 identical v alues t hat are the same as the corresponding SRTM DEM (Figure 9. 6b). 9. 5.5 ... Constraint 178 9. 5.2 SRTM DEM Constraint 1 79 9.5.3 Inversion with Two Constraints 1 79 9.5.4 Optimal Weighting 1 79 9.5.5 Simulation of the Interpolation 181 9. 6 Interpolation Results 181 9. 7 Effect ... LLC. 9 Use of a Prediction-Error Filter in MergingHigh- and Low-Resolution ImagesSang-Ho Yun and Howard ZebkerCONTENTS 9. 1 Image Descriptions 172 9. 1.1 TOPSAR DEM 172 9. 1.2 SRTM DEM 173 9. 2...
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Image Processing for Remote Sensing - Chapter 10a potx

Image Processing for Remote Sensing - Chapter 10a potx

... all images for better visualization.C.H. Chen /Image Processing for Remote Sensing 66641_C010 Final Proof page 232 3.9.2007 2:13pm Compositor Name: JGanesan232 Image Processing for Remote Sensing © ... computed fromC.H. Chen /Image Processing for Remote Sensing 66641_C010 Final Proof page 238 3.9.2007 2:13pm Compositor Name: JGanesan238 Image Processing for Remote Sensing © 2008 by Taylor ... to that class.C.H. Chen /Image Processing for Remote Sensing 66641_C010 Final Proof page 236 3.9.2007 2:13pm Compositor Name: JGanesan236 Image Processing for Remote Sensing © 2008 by Taylor...
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