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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... imagery 10 Ahmed Elsharkawy, Mohamed Elhabiby, Naser El-Sheimy Clouds eliminated from AVHRR/2 images with cloud and snow 17 Zhu Ji, Chen Guizhu, Shang Guofei Towards a complete spectral reflectance uncertainty model for Field ...
... imagery 10 Ahmed Elsharkawy, Mohamed Elhabiby, Naser El-Sheimy Clouds eliminated from AVHRR/2 images with cloud and snow 17 Zhu Ji, Chen Guizhu, Shang Guofei Towards a complete spectral reflectance uncertainty model for Field ...
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... imagery for soil parameter estimation in arid regions Xiaodong Feng , Liping Yang , Fei Liu , Jing Liu , Xiaohui Sun 323 Photochemical Reflectance Index ( PRI ) as a proxy of Light use Efficiency ( LUE ) and transpiration in ...
... imagery for soil parameter estimation in arid regions Xiaodong Feng , Liping Yang , Fei Liu , Jing Liu , Xiaohui Sun 323 Photochemical Reflectance Index ( PRI ) as a proxy of Light use Efficiency ( LUE ) and transpiration in ...
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... imagery and regression kriging method in Hulunber, China 379 Lei Ding, Zhenwang Li, Beibei Shen, Xu Wang, Ruirui Yan, Xiaoping Xin Cirrus cloud removal in Sentinel-3 SLSTR images using an empirical algorithm in the Cirrus band 384 J.C. ...
... imagery and regression kriging method in Hulunber, China 379 Lei Ding, Zhenwang Li, Beibei Shen, Xu Wang, Ruirui Yan, Xiaoping Xin Cirrus cloud removal in Sentinel-3 SLSTR images using an empirical algorithm in the Cirrus band 384 J.C. ...
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... imagery in 2016 allowed to generate a very dense temporal data set of high resolution LAI maps, useful to monitor crop development at field level. The intercomparison between Sentinel-2A and Landsat-8 estimates showed high spatial ...
... imagery in 2016 allowed to generate a very dense temporal data set of high resolution LAI maps, useful to monitor crop development at field level. The intercomparison between Sentinel-2A and Landsat-8 estimates showed high spatial ...
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... imagery. Six Sentinel-2A surface reflectance spectral bands were used during the retrieval process: blue, green, red, near infrared and the two short wave infrared channels. These channels were selected to enhance the consistency with ...
... imagery. Six Sentinel-2A surface reflectance spectral bands were used during the retrieval process: blue, green, red, near infrared and the two short wave infrared channels. These channels were selected to enhance the consistency with ...
Table des matières
RARQS2017p339 | 243 |
RARQS2017p341 | 248 |
RARQS2017p342 | 254 |
RARQS2017s1004 | 260 |
RARQS2017s105 | 265 |
RARQS2017s121 | 270 |
RARQS2017p404 | 276 |
RARQS2017p405 | 282 |
| 47 | |
| 51 | |
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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