Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Hongxiao Jin"'
Autor:
Hongxiao Jin, Christian Josef Köppl, Benjamin M. C. Fischer, Johanna Rojas-Conejo, Mark S. Johnson, Laura Morillas, Steve W. Lyon, Ana M. Durán-Quesada, Andrea Suárez-Serrano, Stefano Manzoni, Monica Garcia
Publikováno v:
Remote Sensing, Vol 13, Iss 10, p 1866 (2021)
Miniature hyperspectral and thermal cameras onboard lightweight unmanned aerial vehicles (UAV) bring new opportunities for monitoring land surface variables at unprecedented fine spatial resolution with acceptable accuracy. This research applies hype
Externí odkaz:
https://doaj.org/article/78c1cf090bd3454abc51b4474e34464d
Autor:
Zhanzhang Cai, Sofia Junttila, Jutta Holst, Hongxiao Jin, Jonas Ardö, Andreas Ibrom, Matthias Peichl, Meelis Mölder, Per Jönsson, Janne Rinne, Maria Karamihalaki, Lars Eklundh
Publikováno v:
Remote Sensing, Vol 13, Iss 3, p 469 (2021)
The high-resolution Sentinel-2 data potentially enable the estimation of gross primary productivity (GPP) at finer spatial resolution by better capturing the spatial variation in a heterogeneous landscapes. This study investigates the potential of 10
Externí odkaz:
https://doaj.org/article/baaeb6f7abe64abab12f38d655c4dbf4
Publikováno v:
Remote Sensing, Vol 9, Iss 12, p 1271 (2017)
Many time-series smoothing methods can be used for reducing noise and extracting plant phenological parameters from remotely-sensed data, but there is still no conclusive evidence in favor of one method over others. Here we use moderate-resolution im
Externí odkaz:
https://doaj.org/article/b1b4dc22b06f4e80a251b1d30c82e737
Publikováno v:
Remote Sensing, Vol 9, Iss 12, p 1271 (2017)
Remote Sensing; Volume 9; Issue 12; Pages: 1271
Remote Sensing; Volume 9; Issue 12; Pages: 1271
Many time-series smoothing methods can be used for reducing noise and extracting plant phenological parameters from remotely-sensed data, but there is still no conclusive evidence in favor of one method over others. Here we use moderate-resolution im