Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Hongxiao Jin"'
Publikováno v:
Sensors, Vol 11, Iss 8, Pp 7678-7709 (2011)
We present a network of sites across Fennoscandia for optical sampling of vegetation properties relevant for phenology monitoring and satellite data calibration. The network currently consists of five sites, distributed along an N-S gradient through
Externí odkaz:
https://doaj.org/article/fb957c9ab53f48a299cef02a3a4c6731
Autor:
Stefano Manzoni, Christian Josef Köppl, Ana María Durán-Quesada, Benjamin Fischer, Laura Morillas, Johanna Rojas-Conejo, Steve W. Lyon, Hongxiao Jin, Mark S. Johnson, Andrea Suarez-Serrano, Monica Garcia
Publikováno v:
Remote Sensing; Volume 13; Issue 10; Pages: 1866
Remote Sensing, Vol 13, Iss 1866, p 1866 (2021)
Jin, H, Köppl, C J, Fischer, B M C, Rojas-Conejo, J, Johnson, M S, Morillas, L, Lyon, S W, Durán-Quesada, A M, Suárez-Serrano, A, Manzoni, S & Garcia, M 2021, ' Drone-Based Hyperspectral and Thermal Imagery for Quantifying Upland Rice Productivity and Water Use Efficiency after Biochar Application ', Remote Sensing, vol. 13, no. 10, 1866 . https://doi.org/10.3390/rs13101866
Remote Sensing, vol.13 (10), pp.1-22.
Kérwá
Universidad de Costa Rica
instacron:UCR
Remote Sensing vol.13 no.10 1-22 2021
Repositorio UNA
Universidad Nacional de Costa Rica
instacron:UNA
Remote Sensing, Vol 13, Iss 1866, p 1866 (2021)
Jin, H, Köppl, C J, Fischer, B M C, Rojas-Conejo, J, Johnson, M S, Morillas, L, Lyon, S W, Durán-Quesada, A M, Suárez-Serrano, A, Manzoni, S & Garcia, M 2021, ' Drone-Based Hyperspectral and Thermal Imagery for Quantifying Upland Rice Productivity and Water Use Efficiency after Biochar Application ', Remote Sensing, vol. 13, no. 10, 1866 . https://doi.org/10.3390/rs13101866
Remote Sensing, vol.13 (10), pp.1-22.
Kérwá
Universidad de Costa Rica
instacron:UCR
Remote Sensing vol.13 no.10 1-22 2021
Repositorio UNA
Universidad Nacional de Costa Rica
instacron:UNA
Se seleccionó la licencia Creative Commons para este envío. El documento trae lo siguiente: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access articledistributed under the terms and conditions of the Creative
Publikováno v:
International Journal of Biometeorology. 63:763-775
Recent climate warming has altered plant phenology at northern European latitudes, but conclusions regarding the spatial patterns of phenological change and relationships with climate are still challenging as quantitative estimates are strongly diver
Autor:
Zhanzhang Cai, Xiaoye Tong, Roel Van Hoolst, Eva Ivits, Koen Hufkens, Kasper Bonte, Jonas Ardö, Torbern Tagesson, Bruno Smets, Hongxiao Jin, Helfried Scheifinger, Lars Eklundh, Feng Tian
Publikováno v:
Tian, F, Cai, Z, Jin, H, Hufkens, K, Scheifinger, H, Tagesson, T, Smets, B, Van Hoolst, R, Bonte, K, Ivits, E, Tong, X, Ardö, J & Eklundh, L 2021, ' Calibrating vegetation phenology from Sentinel-2 using eddy covariance, PhenoCam, and PEP725 networks across Europe ', Remote Sensing of Environment, vol. 260, 112456 . https://doi.org/10.1016/j.rse.2021.112456
Remote Sensing of Environment
Remote Sensing of Environment, Elsevier, 2021, 260, pp.1-15. ⟨10.1016/j.rse.2021.112456⟩
Remote Sensing of Environment
Remote Sensing of Environment, Elsevier, 2021, 260, pp.1-15. ⟨10.1016/j.rse.2021.112456⟩
International audience; Vegetation phenology obtained from time series of remote sensing data is relevant for a range of ecological applications. The freely available Sentinel-2 imagery at a 10 m spatial resolution with a similar to 5-day repeat cycl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::349b7db86d905f7204c63cdb6dd6e675
https://orbit.dtu.dk/en/publications/b4df7fc4-1343-458b-be9e-65acc2f6620f
https://orbit.dtu.dk/en/publications/b4df7fc4-1343-458b-be9e-65acc2f6620f
Autor:
Ursula S. McKnight, Peter Bauer-Gottwein, Hongxiao Jin, Radu Malureanu, Rafael Muñoz-Carpena, Sheng Wang, Mark S. Johnson, Ana María Durán-Quesada, Juan M. Serrano Sandí, Monica Garcia, Stefano Barchiesi, Christian Josef Köppl, Carsten Dam-Hansen
Publikováno v:
Köppl, C J, Malureanu, R, Dam-Hansen, C, Wang, S, Jin, H, Barchiesi, S, Serrano Sandí, J M, Muñoz-Carpena, R, Johnson, M, Durán-Quesada, A M, Bauer-Gottwein, P, McKnight, U S & Garcia, M 2021, ' Hyperspectral reflectance measurements from UAS under intermittent clouds : Correcting irradiance measurements for sensor tilt ', Remote Sensing of Environment, vol. 267, 112719 . https://doi.org/10.1016/j.rse.2021.112719
Remote Sensing of Environment, vol.267, pp.1-15
Kérwá
Universidad de Costa Rica
instacron:UCR
Remote Sensing of Environment, vol.267, pp.1-15
Kérwá
Universidad de Costa Rica
instacron:UCR
One great advantage of optical hyperspectral remote sensing from unmanned aerial systems (UAS) compared to satellite missions is the possibility to fly and collect data below clouds. The most typical scenario is flying below intermittent clouds and u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8460ec66ba4d7013e86b7c5825ef25b1
https://orbit.dtu.dk/en/publications/59d27ce9-1438-420d-929f-88cc7d82d4a1
https://orbit.dtu.dk/en/publications/59d27ce9-1438-420d-929f-88cc7d82d4a1
Publikováno v:
Remote Sensing of Environment. 198:203-212
Land surface phenology is frequently derived from remotely sensed data. However, over regions with seasonal snow cover, remotely-sensed land surface phenology may be dominated by snow seasonality, rather than showing true plant phenology. Overlooking
Autor:
Javier Pacheco-Labrador, Micol Rossini, Albert Porcar-Castell, Loris Vescovo, Caroline Nichol, Hongxiao Jin, Karen Anderson, Tommaso Julitta, Andreas Hueni, Enrico Tomelleri, Manuela Balzarolo, A. Mac Arthur, Lars Eklundh, M.P. Martín, Karolina Sakowska, Sofia Cerasoli
Publikováno v:
Biogeosciences. 12:6103-6124
Resolving the spatial and temporal dynamics of gross primary productivity (GPP) of terrestrial ecosystems across different scales remains a challenge. Remote sensing is regarded as the solution to upscale point observations conducted at the ecosystem
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
Autor:
Hongxiao Jin, Lars Eklundh
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 53:3405-3416
Light sensors are increasingly used to monitor vegetation growing status by measuring reflectance or transmittance in multispectral or photosynthetically active radiation (PAR) bands. The measurements are then used to estimate vegetation indices or t
Publikováno v:
Sensors (Basel, Switzerland)
Sensors; Volume 11; Issue 8; Pages: 7678-7709
Sensors, Vol 11, Iss 8, Pp 7678-7709 (2011)
Sensors; Volume 11; Issue 8; Pages: 7678-7709
Sensors, Vol 11, Iss 8, Pp 7678-7709 (2011)
We present a network of sites across Fennoscandia for optical sampling of vegetation properties relevant for phenology monitoring and satellite data calibration. The network currently consists of five sites, distributed along an N-S gradient through