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 33
Page vi
... evapotranspiration in the Songhua River Basin of China H. Chen, W.C. Zhang 107 Urban Green Land Water Consumption Analysis with Remote Sensing Technology in Beijing City Di Suchuang, Li Zhao-liang, Tang Ronglin, Pan Xingyao, Liu Honglu ...
... evapotranspiration in the Songhua River Basin of China H. Chen, W.C. Zhang 107 Urban Green Land Water Consumption Analysis with Remote Sensing Technology in Beijing City Di Suchuang, Li Zhao-liang, Tang Ronglin, Pan Xingyao, Liu Honglu ...
Page 32
... evapotranspiration, water stress, and species distribution (Prihodko and Goward, 1997). It can therefore be used, for example, as an input parameter in weather and climate models. Tair is usually measured at meteorological stations ...
... evapotranspiration, water stress, and species distribution (Prihodko and Goward, 1997). It can therefore be used, for example, as an input parameter in weather and climate models. Tair is usually measured at meteorological stations ...
Page 40
... evapotranspiration. IEEE Transaction on Geoscience and Remote Sensing, 28, 940-948. Carlson T. N., Gillies R. R., & Schmugge T. J., 1995, An interpretation of methodologies for indirect measurement of soil water content. Agricultural ...
... evapotranspiration. IEEE Transaction on Geoscience and Remote Sensing, 28, 940-948. Carlson T. N., Gillies R. R., & Schmugge T. J., 1995, An interpretation of methodologies for indirect measurement of soil water content. Agricultural ...
Page 47
... evapotranspiration , carbon cycle and water migration . What's more , SSM has great influence on the growth of crops , land degradation and vegetation cover , etc. Study on SSM of the Karst area is of great importance to the drought and ...
... evapotranspiration , carbon cycle and water migration . What's more , SSM has great influence on the growth of crops , land degradation and vegetation cover , etc. Study on SSM of the Karst area is of great importance to the drought and ...
Page 61
... evapotranspiration ( AET ) of vegetation ( agricultural crops as well as natural surfaces ) , a critical term of the water cycle . Water used by agriculture represents about 70 % of the water consumption at global scale . Many countries ...
... evapotranspiration ( AET ) of vegetation ( agricultural crops as well as natural surfaces ) , a critical term of the water cycle . Water used by agriculture represents about 70 % of the water consumption at global scale . Many countries ...
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