Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Hongxiao Jin"'
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:
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:
Abdulhakim M. Abdi, Veiko Lehsten, Niklas Boke-Olén, Jonas Ardö, Torbern Tagesson, Lars Eklundh, Hongxiao Jin
The importance of semi-arid ecosystems in the global carbon cycle as sinks for CO2 emissions has recently been highlighted. Africa is a carbon sink and nearly half its area comprises arid and semi-arid ecosystems. However, there are uncertainties reg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35381fc0a3aff964811561e6c397e1b7
http://arxiv.org/abs/1902.08058
http://arxiv.org/abs/1902.08058
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