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 90
Page vii
... derived from Sentinel-3 SLSTR instrument 206 J. C. Jimenez, J. A. Sobrino, G. Soria, Y. Julien, D. Skokovic, J. Gomis-Cebolla, C. Mattar, A. Santamaría-Artigas, J. J. Pasapera-Gonzales Uncertainty Analysis of the Automated Radiometric ...
... derived from Sentinel-3 SLSTR instrument 206 J. C. Jimenez, J. A. Sobrino, G. Soria, Y. Julien, D. Skokovic, J. Gomis-Cebolla, C. Mattar, A. Santamaría-Artigas, J. J. Pasapera-Gonzales Uncertainty Analysis of the Automated Radiometric ...
Page ix
... derived from GGOS Atmosphere data with GNSS ZTD over China 407 Junyu Li, Lilong Liu, Liangke Huang, Shaofeng Xie, Fade Chen and Linbo Liu Vegetation dynamics in the Iberian Peninsula from GIMMS NDVI 3g 1982-2011 and its relation to the ...
... derived from GGOS Atmosphere data with GNSS ZTD over China 407 Junyu Li, Lilong Liu, Liangke Huang, Shaofeng Xie, Fade Chen and Linbo Liu Vegetation dynamics in the Iberian Peninsula from GIMMS NDVI 3g 1982-2011 and its relation to the ...
Page 2
... derived from synthetic aperture radar (SAR) images (Holecz et al., 2013). Similarly, LAI has been used assessment in the framework of the ERMES (an Earth obseRvation Model based RicE information Service) project (http://www.ermes ...
... derived from synthetic aperture radar (SAR) images (Holecz et al., 2013). Similarly, LAI has been used assessment in the framework of the ERMES (an Earth obseRvation Model based RicE information Service) project (http://www.ermes ...
Page 3
... derived from Sentinel-1A data were derived following a multi-temporal rule-based methodology (Nelson et al., 2014) and subsequently used as masking layer for LAI retrieval. 3 RESULTS Decametric LAI retrievals were obtained over the ...
... derived from Sentinel-1A data were derived following a multi-temporal rule-based methodology (Nelson et al., 2014) and subsequently used as masking layer for LAI retrieval. 3 RESULTS Decametric LAI retrievals were obtained over the ...
Page 7
... derived , T ̧ = T1 + A ( T1 – T1 ) + ∆T $ 1 + ∆T $ 2 S ΔΤ = α ( Τ – Τ ) τ Τ ( 1 - τ . ) 2 ( 3 ) where ai is the regression coefficient , which is 1.40 for CH10.8 and 1.21 for CH11.95 , respectively . ( a ) 0.40 0.35 Fitting line 0.30 ...
... derived , T ̧ = T1 + A ( T1 – T1 ) + ∆T $ 1 + ∆T $ 2 S ΔΤ = α ( Τ – Τ ) τ Τ ( 1 - τ . ) 2 ( 3 ) where ai is the regression coefficient , which is 1.40 for CH10.8 and 1.21 for CH11.95 , respectively . ( a ) 0.40 0.35 Fitting line 0.30 ...
Table des matières
RARQS2017p339 | 243 |
RARQS2017p341 | 248 |
RARQS2017p342 | 254 |
RARQS2017s1004 | 260 |
RARQS2017s105 | 265 |
RARQS2017s121 | 270 |
RARQS2017p404 | 276 |
RARQS2017p405 | 282 |
| 47 | |
| 51 | |
| 56 | |
| 61 | |
| 67 | |
| 73 | |
| 77 | |
| 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