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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Page 1
... 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 consistency between estimates over the three areas ...
... 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 consistency between estimates over the three areas ...
Page 2
... temporal frequency of the campaigns was approximately 7–10 days starting from the very beginning of rice emergence (early June) up to the maximum green rice LAI development (mid-August). A range of 18–24 measurements over every ESU was ...
... temporal frequency of the campaigns was approximately 7–10 days starting from the very beginning of rice emergence (early June) up to the maximum green rice LAI development (mid-August). A range of 18–24 measurements over every ESU was ...
Page 4
... temporal evolution of two Sentinel-2A rice pixels (healthy and damaged). It can be seen the anomalous temporal LAI evolution over the same field which is related with rice crop disease. Figure 4. Sentinel-2 LAI evolution within a rice ...
... temporal evolution of two Sentinel-2A rice pixels (healthy and damaged). It can be seen the anomalous temporal LAI evolution over the same field which is related with rice crop disease. Figure 4. Sentinel-2 LAI evolution within a rice ...
Page 17
... temporal resolution . 2 STUDY AREA AND DATA 2.1 Study Area The study area is Qinghai – Tibet Plateau in southwest China , with a latitude and longitude of about 26☐ 40 and 73 105☐ respectively , and an area and altitude of about ...
... temporal resolution . 2 STUDY AREA AND DATA 2.1 Study Area The study area is Qinghai – Tibet Plateau in southwest China , with a latitude and longitude of about 26☐ 40 and 73 105☐ respectively , and an area and altitude of about ...
Page 37
... temporal and spatial variation of soil moisture in the study area was also analysed. The results show that the accuracy of the nonlinear interpolation method is significantly higher than the linear interpolation method. The Root mean ...
... temporal and spatial variation of soil moisture in the study area was also analysed. The results show that the accuracy of the nonlinear interpolation method is significantly higher than the linear interpolation method. The Root mean ...
Table des matières
RARQS2017p339 | 243 |
RARQS2017p341 | 248 |
RARQS2017p342 | 254 |
RARQS2017s1004 | 260 |
RARQS2017s105 | 265 |
RARQS2017s121 | 270 |
RARQS2017p404 | 276 |
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RARQS2017p225 | 107 |
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RARQS2017p231 | 118 |
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RARQS2017p235 | 128 |
RARQS2017p241 | 138 |
RARQS2017s604 | 144 |
RARQS2017p304 | 151 |
RARQS2017p307 | 157 |
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RARQS2017p311 | 174 |
RARQS2017p315 | 180 |
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RARQS2017p335 | 232 |
RARQS2017p337 | 238 |
RARQS2017p406 | 287 |
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RARQS2017p412 | 303 |
RARQS2017p417 | 312 |
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RARQS2017p519 | 407 |
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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