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List of Figures 3.18 Example of attributing atmospheric, sensor, and model uncertainties to a simulated spectrum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 3.19 Examples of predictive regression functions between best performing vegetation indices and Cw, LAI, and BS, based on RTM simulations . . . . . . . . . . . . . 70 4.1 Location of Waging-Taching test site . . . . . . . . . . . . . . . . . . . . . . . . . 80 4.2 Location of selected test fields and plots used for canopy characterization . . . . 82 4.3 The three different types of grassland sampled during first HyMap data campaign 82 4.4 Procedure followed for destructive sampling of LAI . . . . . . . . . . . . . . . . . 84 4.5 Comparison between LAI measured by LAI-2000 and destructive sampling . . . 87 4.6 Cdm and Cw based on directly (empirically) and indirectly (LAI-2000) measured LAI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 4.7 Georectified false color composite of three flightlines recorded at June 30, 2003 . 90 4.8 Comparison of 3 georectified and image matched subsets of the flightlines recorded at June 30, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 4.9 Comparison of average field spectrometer and atmospherically corrected HyMap reflectance data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 4.10 Average spectral signatures of MEA1, MEA2, and PAS for the campaigns HYM1 and HYM2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 4.11 Comparing modeled and measured reflectance for two sampling locations . . . . 96 4.12 Correlation between canopy reflectance and measured and modeled Cw, Cdm, and LAI for vigorous green grassland . . . . . . . . . . . . . . . . . . . . . . . . 98 4.13 Correlation between canopy reflectance and measured and modeled Cw, Cdm, and LAI for dry, cut meadows . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 4.14 RTM inversion results for Cw, Cdm, and LAI applying a global LUT and without using prior information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 4.15 RTM inversion results for Cw, Cdm, and LAI applying LUTs adjusted to SPECL classes, and without using prior information . . . . . . . . . . . . . . . . . . . . . 101 4.16 Effect of accounting for spectral covariance on estimates of Cab, LAI and ALA . 104 4.17 RTM inversion results for Cw, Cdm, and LAI using LUTs adjusted to SPECL classes and prior information based on field measurements . . . . . . . . . . . . . 105 4.18 RTM inversion results for Cw, Cdm, and LAI using LUTs adjusted to SPECL classes and including prior information and covariance between the variables based on field measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 4.19 RTM inversion results for Cw, Cdm, and LAI using LUTs adjusted to SPECL classes and prior information based on predictive equations . . . . . . . . . . . . 108 4.20 Influence of introducing a prior estimates based on predictive regression equations on Cab retrieval . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 4.21 Reducing ambiguity by accounting for covariance between the variables . . . . . 109 4.22 Comparing final RTM inversion results of Cw, Cdm, and LAI with prior estimates obtained by predictive regression equations . . . . . . . . . . . . . . . . . . . . . 110 4.23 RTM inversion results for canopy water and dry matter content, using the synthetic variables Cw × LAI and Cdm × LAI . . . . . . . . . . . . . . . . . . . . . 111 4.24 Mean and maximum absolute deviation between single estimated variables and the average result over 12 model runs . . . . . . . . . . . . . . . . . . . . . . . . 114 xx
List of Figures 4.25 Sensitivity of RTM inversion results to variable ranges used to construct the LUT for SPECL class 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 4.26 Sensitivity of RTM inversion results to variable ranges used to construct the LUT for SPECL class 6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 4.27 Spectral anisotropy factors for the HyMap scenes WAGING07, WAGING13, and WAGING14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 4.28 Relative spectral differences in red and NIR reflectance between three overlapping subsets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 4.29 Effect of spectral anisotropy on NDVI-based LAI estimates . . . . . . . . . . . . 125 4.30 Intercomparison of LAI estimated from different observation/sun constellations . 126 4.31 Comparison of leaf variable estimates from 3 HyMap scenes with varying view/sun geometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 4.32 Comparison of canopy variable estimates from 3 HyMap scenes with varying view/sun geometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 4.33 Results of automatic SPECL classification of nadir-normalized HyMap data of June 30, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 4.34 Correlation between biased classification results and deviations in LAI and Cw retrievals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 4.35 Example of effect of land cover classification and inclusion of local variance on prior estimates on LAI retrieval . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 4.36 Prior estimates of Cab, Cw, and LAI for flightline WAGING13 . . . . . . . . . . 131 4.37 Relationship between estimates of LAI and ALA for prior estimates and final RTM inversion results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 4.38 Spatial distribution at MEA1, MEA2, and PAS of leaf variables estimated from flightline WAGING07 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 4.39 Spatial distribution at MEA1, MEA2, and PAS of canopy variables estimated from flightline WAGING07 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 4.40 Estimated versus measured Cw, Cdm, and LAI, based on HyMap scenes with differing view/sun constellations . . . . . . . . . . . . . . . . . . . . . . . . . . . 136 4.41 Variables estimated from ASD field spectrometer data versus estimates based on HyMap scene WAGING07 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 5.1 Location of the Khorezm test site . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 5.2 Examples of cotton canopies encountered in the study area at the time of satellite overpass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 5.3 Regression fit between SPAD and laboratory measurements of chlorophyll a+b . 147 5.4 Spatial distribution of measured Cab and LAI . . . . . . . . . . . . . . . . . . . 149 5.5 View/sun constellation of CHRIS observations and overlay of georeferenced multiangular CHRIS images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 5.6 Green, red, and NIR HDRF for various fields at 5 different view angles . . . . . . 153 5.7 Anisotropy index (ANIX) and average nadir reflectance for six different fields . . 154 5.8 Influence of changing LAI on spectral anisotropy, simulated with PROSPECT and SAILh for green, red, and NIR reflectance . . . . . . . . . . . . . . . . . . . 156 5.9 Influence of changing ALA on spectral anisotropy, simulated with PROSPECT and SAILh for green, red, and NIR reflectance . . . . . . . . . . . . . . . . . . . 156 xxi
Page 1: Retrieving canopy variables by radi
Page 5: German Aerospace Center - German Re
Page 8 and 9: Abstract The performance and stabil
Page 10 and 11: Zusammenfassung zu berechnen. Die a
Page 12 and 13: Zusammenfassung x
Page 14 and 15: xii in Uzbekistan and sharing the d
Page 16 and 17: Contents 2.5.1 Leaf optical models
Page 18 and 19: Contents 4.4.2 Influence of land co
Page 20 and 21: Contents xviii
Page 24 and 25: List of Figures 5.10 Influence of c
Page 26 and 27: List of Tables 5.4 Observation and
Page 28 and 29: LIDF LUT MERIS MODIS MISR MIR NIR O
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Page 32 and 33: 1.2. User requirements on remote se
Page 34 and 35: 1.3. The challenge of providing rob
Page 36 and 37: 1.5. Research objectives et al., 20
Page 38 and 39: 1.5. Research objectives • The al
Page 40 and 41: 1.6. Structure of the thesis 10
Page 42 and 43: 2.1. Principles of solar-reflective
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Page 52 and 53: 2.2. Canopy reflectance ARTICLE IN
Page 54 and 55: 2.3. Retrieving canopy variables by
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3.2. Choosing an appropriate radiat
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3.3. The inversion approach Figure
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3.3. The inversion approach LAI Fig
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3.4. The optimization algorithm Fig
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3.4. The optimization algorithm (a)
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3.4. The optimization algorithm pra
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3.4. The optimization algorithm (a)
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3.4. The optimization algorithm Tab
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3.5. Conclusions and preface to Cha
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3.5. Conclusions and preface to Cha
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4.1. Introduction 4.1.1 Preceding g
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4.2. Study site and data Figure 4.1
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4.2. Study site and data (a) (b) 80
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4.2. Study site and data Table 4.1:
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4.3. Exploring algorithm potential
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4.4. RTM inversion applied to HyMap
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-30° 3° -30° 3° 0° 31° 4.4
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4.5. Conclusions Figure 4.40: Estim
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4.5. Conclusions Generally, radiati
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4.5. Conclusions 140
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5.1. Introduction surface propertie
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5.2. Study site and data 5.1.4 Obje
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5.3. Quantifying spectral anisotrop
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5.4. RTM inversion using the fully
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5.5. RTM inversion including measur
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5.6. Conclusions 5.6 Conclusions Th
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5.6. Conclusions 168
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6.2. Resuming the performance of th
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6.3. Conclusions data. The large di
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6.4. Outlook models, and ground bas
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Class name Decision rules snow b4/b
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B.2. SPECL class 3: Average vegetat
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B.4. SPECL class 5: Yellow vegetati
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B.5. SPECL class 6: Mixed vegetatio
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B.7. SPECL class 13: Sparse vegetat
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B.7. SPECL class 13: Sparse vegetat
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(continued) Vegetation Index Equati
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VIS NIR SWIR1 SWIR2 Band λ FWHM Ba
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Table E.1: Results of canopy measur
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200
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Band nr. λ (nm) FWHM (nm) 1 442.5
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Bibliography Bacour, C. (2001). Con
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Bibliography Borel, C. C., Gerstl,
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Bibliography Combal, B., Baret, F.,
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Bibliography Garrigues, S., Allard,
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Bibliography Hapke, B. (1981). Bidi
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Bibliography Kaufman, Y. and Tanré
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Bibliography LICOR (2000). LAI-2000
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Bibliography Proceedings of the 8th
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Bibliography Rondeaux, G., Steven,
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Bibliography Suits, G. (1983). The
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Bibliography Weiss, M., Baret, F.,
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Bibliography 226
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Rischbeck, P., Schneider, W., Suppa
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Wouter Dorigo Date and place of bir
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