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 43
Page vi
... multispectral TIR data 95 Li Ni, WangminYing, Wan Li, Hua Wu Determining spatial resolution variability of hyperspectral pushbroom sensors 101 Agata Orych, Agnieszka Jenerowicz, Diana Zach Fair comparison of NDVI time series ...
... multispectral TIR data 95 Li Ni, WangminYing, Wan Li, Hua Wu Determining spatial resolution variability of hyperspectral pushbroom sensors 101 Agata Orych, Agnieszka Jenerowicz, Diana Zach Fair comparison of NDVI time series ...
Page 10
... multi-spectral satellite imagery using a non-linear bathymetric inversion model (Stumpf et al. 2003). According to ... multispectral, passive sensors. In the next section a brief summary of these two properties and how they can be ...
... multi-spectral satellite imagery using a non-linear bathymetric inversion model (Stumpf et al. 2003). According to ... multispectral, passive sensors. In the next section a brief summary of these two properties and how they can be ...
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... Multi - spectral Imagery According to ( Jensen 2007 ) , the total upwelling radiance ( Lt ) recorded by the remote sensor consists of four components , as shown in Figure 1 . Lt = Lb + Lv + Ls + Lp Eq . 1 Where , ( Lp ) , atmospheric ...
... Multi - spectral Imagery According to ( Jensen 2007 ) , the total upwelling radiance ( Lt ) recorded by the remote sensor consists of four components , as shown in Figure 1 . Lt = Lb + Lv + Ls + Lp Eq . 1 Where , ( Lp ) , atmospheric ...
Page 12
... multispectral imagery (Su et al. 2008). In this research the relative depths of part of the water way of the Suez Canal and the over polluted Temsah Lake will be derived from the worldview-2 imagery, using the non- linear bathymetric ...
... multispectral imagery (Su et al. 2008). In this research the relative depths of part of the water way of the Suez Canal and the over polluted Temsah Lake will be derived from the worldview-2 imagery, using the non- linear bathymetric ...
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... multi-spectral bands. and 4.2 Conversion to Top-of-Atmosphere Spectral reflectance Right now we have the ToA ... multispectral data into reflectance before performing spectral analysis techniques such as band ratios, Normalized ...
... multi-spectral bands. and 4.2 Conversion to Top-of-Atmosphere Spectral reflectance Right now we have the ToA ... multispectral data into reflectance before performing spectral analysis techniques such as band ratios, Normalized ...
Table des matières
RARQS2017p339 | 243 |
RARQS2017p341 | 248 |
RARQS2017p342 | 254 |
RARQS2017s1004 | 260 |
RARQS2017s105 | 265 |
RARQS2017s121 | 270 |
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RARQS2017p241 | 138 |
RARQS2017s604 | 144 |
RARQS2017p304 | 151 |
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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