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DEPARTMENT OF GEOMATIC ENGINEERING
MERIS land surface albedo: Production and Validation
Jan-Peter Muller*Professor of Image Understanding and Remote Sensing
MODIS & MISR Science Team Member (NASA EOS Project)HRSC Science Team Member (ESA Mars Express 2003)
Chair, CEOS-WGCV Terrain mapping sub-group
DEPARTMENT OF GEOMATIC ENGINEERING
Overview
ObjectivesBRDF/Albedo retrieval approachMoving vs Static time window issueValidation approachWish-list
DEPARTMENT OF GEOMATIC ENGINEERING
Objectives Derivation of a one-year land surface albedo from MERIS for
– 13 of the 15 MERIS wavelengths (2 inside O2 absorption bands)
– 2 broadband albedos (0.4-0.7µm, 0.7-1.0µm)
– MONTHLY time step (see later) for 2003
– Input Level 2 Rayleigh+O3 corrected
– 10km sinusoidal and 0.1º spatial resolutions
– Publication of MERIS albedo browse images (as Web Map Services layers) within CEOS-WGISS EO Data Portal (http://iceds.ge.ucl.ac.uk)
Main driver is to improve the retrieval of atmospheric parameters from MERIS. Hence, we need spectral albedos at the MERIS wavelengths
Extremely limited resources (JPM) for validation by inter-comparison with other EO sensors and BRSN data
DEPARTMENT OF GEOMATIC ENGINEERING
BRDF/albedo approach Novel algorithms developed at Freie Universität by
– Thomas Schröder for aerosol correction – Réné Preusker for cloud masking/detection
Brockmann Consult responsible for – algorithm coding, implementation and test (both production system and subsets
as part of a new release of BEAM)– Production processing of MERIS level 2– Previous experience in development of cal/val database for MERIS ocean
products BRDF retrieval will NOT be performed as sampling of the bi-
directional plane insufficient for most land surfaces given the narrower swath (1130km) and lower temporal sampling (every 3 days at the equator) of MERIS
Instead BRDF will be taken from MOD43C2 (0.05º) and magnitude inversion employed for each cloud-free pixel directional spectral reflectance sample and average taken over appropriate monthly period. Would like to test use of Maignan et al (RSE04) for months when sufficient POLDER-2 samples available
Unresolved issues with high reflectance areas: snow and desert
Albedo retrieval scheme Meris L2
SDRs
MOD43C2 BRDF (0.05º) + QA#1 flags
BIN/AVERAGE MERIS SDRs (0.05º)
DAILY MAGNITUDE INVERSION with MOD43C2
DAILY MERIS ALBEDO CALC.
MONTHLY/ SEASONAL AVERAGE RE-PROJECT TO 10KM
QA#2 Nsamps, ± stddev
CALCULATE MERIS NBAR 0.05º DAILY
CALCULATE <MERIS> NBAR OVER MODIS 16 DAY PERIOD
CALCULATE <MERIS> ALBEDO OVER 6 DAY
QA3 Nsamps, ± std.dev.
MERIS 0.05º 16- DAY NBAR
INTERCOMPARE WITH MOD43C3
DIFF STATS
MOD43C3 NBAR (0.05º)
MERIS 0.05º 16- DAY ALBEDOS
INTERCOMP-ARE WITH MOD43C1
MOD43C1 ALBEDO (0.05º)
INTERPOLATE ALBEDO VALUES AT 9 OTHER BANDS + INTEGRATE TO VIS AND NIR Broadband
MERIS 10KM 13- SPECTRAL +2 BROADBAND MONTHLY+ SEASONAL ALBEDOS
N.B. Status: ATBD completed, coding underway,production due to start in June, completed by MERISuser workshop in Sep05
DEPARTMENT OF GEOMATIC ENGINEERING
Moving vs Static window
Dr David Roy (MODIS Land QA/LDOPE Facility) has analysed global cloud statistics from Terra and Aqua separately and Terra+Aqua for fixed 16-day window and Terra-only (equivalent to Terra) with a moving 32-day window
Results indicate that a MOVING 32-day time-step with daily updated calculations will lead to MUCH higher retrievals of cloud-free pixels and many more FULL INVERSIONS of MOD43
Schaaf et al (BU) have shown that TERRA+AQUA will improve the number of FULL INVERSIONS of MOD43
Analysis by Roy using Terra+Aqua (fixed 16-day vs moving window) show excellent improvements in cloud-free samples
Plan to extend this to cloud statistics from MERIS to assess which approach will yield better statistics
N.B. POLDER-2 uses a 30-day moving window approach, reported at an unequal time interval (5th, 15th and 25th of each month)
Global mean annual probability = 0.636 (1 0.26) [computed over the illustrated 143 non-polar tiles containing >25% land]
Global 10 degree tile-level analysis of the mean annual probability of obtaining >=7 non-cloudy MODIS Terra observations in 16-day
windows moved in daily steps through 366 days of 2004
mean annual probability of obtaining >=7 non-cloudy observations 1.0 to 0.0 ≤≥ 4.0 to 3.0 ≤> 7.0 to 6.0 ≤> 0.1 to 9.0 ≤>6.0 to 5.0 ≤>2.0 to 1.0 ≤> 3.0 to 2.0 ≤> 5.0 to 4.0 ≤> 8.0 to 7.0 ≤> 9.0 to 8.0 ≤>
Global 10 degree tile-level analysis of the mean annual probability of obtaining >=7 non-cloudy MODIS Aqua observations in 16-day
windows moved in daily steps through 366 days of 2004
mean annual probability of obtaining >=7 non-cloudy observations
Global mean annual probability = 0.595 (1 0.26) [computed over the illustrated 143 non-polar tiles containing >25% land]
1.0 to 0.0 ≤≥ 4.0 to 3.0 ≤> 7.0 to 6.0 ≤> 0.1 to 9.0 ≤>6.0 to 5.0 ≤>2.0 to 1.0 ≤> 3.0 to 2.0 ≤> 5.0 to 4.0 ≤> 8.0 to 7.0 ≤> 9.0 to 8.0 ≤>
D. Roy UMD
Global mean annual probability = 0.895 (1 0.14) [computed over the illustrated 143 non-polar tiles containing >25% land]
Global 10 degree tile-level analysis of the mean annual probability of obtaining >=7 non-cloudy MODIS Terra and Aqua observations
in 16-day windows moved in daily steps through 366 days of 2004
mean annual probability of obtaining >=7 non-cloudy observations 1.0 to 0.0 ≤≥ 4.0 to 3.0 ≤> 7.0 to 6.0 ≤> 0.1 to 9.0 ≤>6.0 to 5.0 ≤>2.0 to 1.0 ≤> 3.0 to 2.0 ≤> 5.0 to 4.0 ≤> 8.0 to 7.0 ≤> 9.0 to 8.0 ≤>
D. Roy UMD
D. Roy UMD
Global analysis of the availability of >=7 non-cloudy MODIS Terra observations
32-day window moved in daily steps through 366 days of 2004
%19 to %0 %59 to %40 %100 to %80%39 to %20 %79 to %60
Percentage of windows over the year where the probability of obtaining >=7 non-cloudy observations is > 0.9
DEPARTMENT OF GEOMATIC ENGINEERING
Validation approach(1)
Difference statistics between MERIS-Albedo and MOD43C1 will be analysed
Overlapping MERIS swath NBARs (Nadir-equivalent BRDF Adjsuted Reflectance) will be used to assess how accurate the BRDF correction has performed as well as detect poorly corrected aerosol correction and poorly masked clouds
Inter-comparisons will be performed with– MISR 0.5º “true monthly” level-3 product (2003)
– POLDER2 0.1º resampled 6km sinusoidal gridded 30-day products reported on the 15th of each month (Apr03-to-Oct03
– MOD43C1 sampled for “best albedo value” of two 16-day time periods within the months of Jan, Feb, Sep, Oct, Nov-03
DEPARTMENT OF GEOMATIC ENGINEERING
Validation issue: finding temporal coincidences (MOD43)Date Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1 1 32 60 91 121 152 182 213 244 274 305 3352 2 33 61 92 122 153 183 214 245 275 306 3363 3 34 62 93 123 154 184 215 246 276 307 3374 4 35 63 94 124 155 185 216 247 277 308 3385 5 36 64 95 125 156 186 217 248 278 309 3396 6 37 65 96 126 157 187 218 249 279 310 3407 7 38 66 97 127 158 188 219 250 280 311 3418 8 39 67 98 128 159 189 220 251 281 312 3429 9 40 68 99 129 160 190 221 252 282 313 343
10 10 41 69 100 130 161 191 222 253 283 314 34411 11 42 70 101 131 162 192 223 254 284 315 34512 12 43 71 102 132 163 193 224 255 285 316 34613 13 44 72 103 133 164 194 225 256 286 317 34714 14 45 73 104 134 165 195 226 257 287 318 34815 15 46 74 105 135 166 196 227 258 288 319 34916 16 47 75 106 136 167 197 228 259 289 320 35017 17 48 76 107 137 168 198 229 260 290 321 35118 18 49 77 108 138 169 199 230 261 291 322 35219 19 50 78 109 139 170 200 231 262 292 323 35320 20 51 79 110 140 171 201 232 263 293 324 35421 21 52 80 111 141 172 202 233 264 294 325 35522 22 53 81 112 142 173 203 234 265 295 326 35623 23 54 82 113 143 174 204 235 266 296 327 35724 24 55 83 114 144 175 205 236 267 297 328 35825 25 56 84 115 145 176 206 237 268 298 329 35926 26 57 85 116 146 177 207 238 269 299 330 36027 27 58 86 117 147 178 208 239 270 300 331 36128 28 59 87 118 148 179 209 240 271 301 332 36229 29 88 119 149 180 210 241 272 302 333 36330 30 89 120 150 181 211 242 273 303 334 36431 31 90 151 212 243 304 365
DEPARTMENT OF GEOMATIC ENGINEERING
Validation issues wish-list (if time available)
Scaling issues for MERIS albedo validation using in situ (SURFRAD/BSRN)
Assessing the impact of topography (elevation and slope) from SRTM (ICEDS)
Assessing the impact of urban areas on visible albedo variations (ICEDS)
DEPARTMENT OF GEOMATIC ENGINEERING
Albedo over urban areasNile Delta (JD305 31.10.2000)
Distinctly higher albedo over urban areas in the Nile Delta
Can be hard to get full inversions over urban areas as they are frequently misidentified as cloudy
-0.25
-0.20
-0.15
-0.10
-0.05
-0
Albedo
DEPARTMENT OF GEOMATIC ENGINEERING
Night-time lights (1995-6):Cities around The Great Lakes
Senses light sources down to 10-9 W/cm2/sr/m (Elvidge et al., 1999)
Radiance: x 10-10 W.m-2.sr-1.μm-1
DEPARTMENT OF GEOMATIC ENGINEERING
Current ICEDS portal test area
