Fifth recent advances in quantitative remote sensingJosé Antonio Sobrino Rodríguez Universitat de València, 14 déc. 2018 - 481 pages
The Fifth International Symposium on Recent Advances in Quantitative Remote Sensing was held in Torrent, Spain from 18 to 22 September 2018. It was sponsored and organized by the Global Change Unit (GCU) from the Image Processing Laboratory (IPL), University of Valencia (UVEG), Spain. This Symposium addressed the scientific advances in quantitative remote sensing in connection with real applications. Its main goal was to assess the state of the art of both theory and applications in the analysis of remote sensing data, as well as to provide a forum for researcher in this subject area to exchange views and report their latest results. In this book 89 of the 262 contributions presented in both plenary and poster sessions are arranged according to the scientific topics selected. The papers are ranked in the same order as the final programme. |
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Résultats 1-5 sur 26
Page 6
... temperature (SST) is a key geophysical parameter at the ocean–atmosphere boundary. One commonly used method to ... brightness temperature Ti , atmospheric equivalent temperature Tai and the SST in the radiative transfer model (RTM) ...
... temperature (SST) is a key geophysical parameter at the ocean–atmosphere boundary. One commonly used method to ... brightness temperature Ti , atmospheric equivalent temperature Tai and the SST in the radiative transfer model (RTM) ...
Page 7
... temperature ( SST ) , AT is the error in Ti caused by linearizing the Planck function . In the published literature ... brightness temperature can be obtained by inverting the Planck function . The atmospheric equivalent ...
... temperature ( SST ) , AT is the error in Ti caused by linearizing the Planck function . In the published literature ... brightness temperature can be obtained by inverting the Planck function . The atmospheric equivalent ...
Page 9
... brightness temperatures with the surface temperatures ranging from T0 – 5 K, T0– 2 K, T0 K, T0 + 2 K and T0 + 5 K. Based on 115 simulated situations (23 profiles * 5 surface temperatures), the SST was calculated using Eq. (6). A RMSE of ...
... brightness temperatures with the surface temperatures ranging from T0 – 5 K, T0– 2 K, T0 K, T0 + 2 K and T0 + 5 K. Based on 115 simulated situations (23 profiles * 5 surface temperatures), the SST was calculated using Eq. (6). A RMSE of ...
Page 18
... brightness temperature of NO.4 channel was lower than 250K, that is, T4 < 250K. 3.2 The detection of medium clouds using NO.1, NO.3 and NO.4 channels Medium clouds are mainly comprised of little ice crystal and supercooled water, and ...
... brightness temperature of NO.4 channel was lower than 250K, that is, T4 < 250K. 3.2 The detection of medium clouds using NO.1, NO.3 and NO.4 channels Medium clouds are mainly comprised of little ice crystal and supercooled water, and ...
Page 19
... brightness temperature differences between NO.4 channel and NO.5 channel (Yamanouchi, 1987). In his research, the differences between NO.4 and NO.5 were used to identify the thin clouds. The results of experiments indicate that if the ...
... brightness temperature differences between NO.4 channel and NO.5 channel (Yamanouchi, 1987). In his research, the differences between NO.4 and NO.5 were used to identify the thin clouds. The results of experiments indicate that if the ...
Table des matières
RARQS2017p339 | 243 |
RARQS2017p341 | 248 |
RARQS2017p342 | 254 |
RARQS2017s1004 | 260 |
RARQS2017s105 | 265 |
RARQS2017s121 | 270 |
RARQS2017p404 | 276 |
RARQS2017p405 | 282 |
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| 73 | |
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| 82 | |
| 90 | |
RARQS2017p212 | 95 |
RARQS2017p217 | 104 |
RARQS2017p225 | 107 |
RARQS2017p226 | 112 |
RARQS2017p231 | 118 |
RARQS2017p234 | 123 |
RARQS2017p235 | 128 |
RARQS2017p241 | 138 |
RARQS2017s604 | 144 |
RARQS2017p304 | 151 |
RARQS2017p307 | 157 |
RARQS2017p308 | 162 |
RARQS2017p309 | 168 |
RARQS2017p311 | 174 |
RARQS2017p315 | 180 |
RARQS2017p318 | 186 |
RARQS2017p319 | 191 |
RARQS2017p322 | 197 |
RARQS2017p323 | 202 |
RARQS2017p324 | 206 |
RARQS2017p327 | 211 |
RARQS2017p330 | 217 |
RARQS2017p331 | 223 |
RARQS2017p332 | 227 |
RARQS2017p335 | 232 |
RARQS2017p337 | 238 |
RARQS2017p406 | 287 |
RARQS2017p407 | 292 |
RARQS2017p408 | 296 |
RARQS2017p412 | 303 |
RARQS2017p417 | 312 |
RARQS2017p420 | 318 |
RARQS2017p424 | 323 |
RARQS2017p427 | 327 |
RARQS2017p428 | 332 |
RARQS2017p434 | 337 |
RARQS2017p437 | 342 |
RARQS2017p440 | 346 |
RARQS2017p441 | 351 |
RARQS2017p501 | 356 |
RARQS2017p503 | 362 |
RARQS2017p504 | 368 |
RARQS2017p506 | 374 |
RARQS2017p508 | 379 |
RARQS2017p509 | 384 |
RARQS2017p510 | 387 |
RARQS2017p511 | 391 |
RARQS2017p512 | 396 |
RARQS2017p514 | 402 |
RARQS2017p519 | 407 |
RARQS2017p524 | 412 |
RARQS2017p525 | 418 |
RARQS2017p527 | 425 |
RARQS2017p528 | 430 |
RARQS2017p532 | 436 |
RARQS2017p535 | 443 |
RARQS2017p538 | 449 |
RARQS2017p539 | 454 |
RARQS2017p540 | 460 |
RARQS2017 | 464 |
Expressions et termes fréquents
accuracy Agricultural albedo algorithm analysis angle applications atmospheric average backscatter band Beijing brightness temperature C-band calculated calibration China classification climate coefficient comparison computed correlation crop datasets derived detection emissivity error estimation evaluate evapotranspiration FAPAR field Figure FPGA Geoscience and Remote global GNSS grass production grassland greenup date Guangxi hyperspectral IEEE imagery images infrared interpolation inversion Journal land surface temperature Landsat landslide leaf area index linear Livingston Island MAIAC mapping maximum measurements meteorological method MODIS monitoring multispectral NDVI obtained optimized parameters pixels polarization precipitation processing radar radiance radiation reflectance region Remote Sensing remote sensing data Research retrieval rice RMSE sampling satellite data scale Sciences Sensing of Environment sensor shows signal simulated soil moisture solar spatial resolution spectral study area temporal thermal infrared Tibetan Plateau trend TWSA uncertainty validation values variables variation vegetation index Zhang