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pro vyhledávání: '"Tree–grass ecosystem"'
Akademický článek
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Akademický článek
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Autor:
Vicente Burchard-Levine, Héctor Nieto, David Riaño, Mirco Migliavacca, Tarek S. El-Madany, Oscar Perez-Priego, Arnaud Carrara, M. Pilar Martín
Publikováno v:
Remote Sensing, Vol 12, Iss 6, p 904 (2020)
The thermal-based two-source energy balance (TSEB) model has accurately simulated energy fluxes in a wide range of landscapes with both remote and proximal sensing data. However, tree-grass ecosystems (TGE) have notably complex heterogeneous vegetati
Externí odkaz:
https://doaj.org/article/c327f4b5b471442998322be7e61ae229
Autor:
José Ramón Melendo-Vega, M. Pilar Martín, Javier Pacheco-Labrador, Rosario González-Cascón, Gerardo Moreno, Fernando Pérez, Mirco Migliavacca, Mariano García, Peter North, David Riaño
Publikováno v:
Remote Sensing, Vol 10, Iss 12, p 2061 (2018)
The 3-D Radiative Transfer Model (RTM) FLIGHT can represent scattering in open forest or savannas featuring underlying bare soils. However, FLIGHT might not be suitable for multilayered tree-grass ecosystems (TGE), where a grass understory can domina
Externí odkaz:
https://doaj.org/article/3570c1974a3b4079a0e3c384a5e95604
Autor:
Yunpeng Luo, Tarek S. El-Madany, Gianluca Filippa, Xuanlong Ma, Bernhard Ahrens, Arnaud Carrara, Rosario Gonzalez-Cascon, Edoardo Cremonese, Marta Galvagno, Tiana W. Hammer, Javier Pacheco-Labrador, M. Pilar Martín, Gerardo Moreno, Oscar Perez-Priego, Markus Reichstein, Andrew D. Richardson, Christine Römermann, Mirco Migliavacca
Publikováno v:
Remote Sensing, Vol 10, Iss 8, p 1293 (2018)
Tree–grass ecosystems are widely distributed. However, their phenology has not yet been fully characterized. The technique of repeated digital photographs for plant phenology monitoring (hereafter referred as PhenoCam) provide opportunities for lon
Externí odkaz:
https://doaj.org/article/3e3cb5473e0c47fa8b19722b93ddfe51
Publikováno v:
Remote Sensing; Volume 12; Issue 1; Pages: 28
Leaf pigment contents, such as chlorophylls a and b content (C a b ) or carotenoid content (Car), and the leaf area index (LAI) are recognized indicators of plants’ and forests’ health status that can be estimated through hyperspectral imagery. T
Autor:
Rosario Gonzalez-Cascon, Oscar Perez-Priego, Richard Nair, Marta Galvagno, Edoardo Cremonese, Yunpeng Luo, Yonatan Cáceres Escudero, Annette Menzel, Solveig Franziska Bucher, Christine Römermann, Tarek S. El-Madany, Martin Jung, Xuanlong Ma, Arnaud Carrara, Javier Pacheco-Labrador, Andrew D. Richardson, Gianluca Filippa, Gerardo Moreno, Markus Reichstein, Mirco Migliavacca, M. Pilar Martín, Ulrich Weber
Publikováno v:
Global Change Biology
Digital.CSIC. Repositorio Institucional del CSIC
instname
Digital.CSIC. Repositorio Institucional del CSIC
instname
Anthropogenic nitrogen (N) deposition and resulting differences in ecosystem N and phosphorus (P) ratios are expected to impact photosynthetic capacity, that is, maximum gross primary productivity (GPP). However, the interplay between N and P availab
Autor:
David Riaño, M. Pilar Martín, Hector Nieto, Tarek S. El-Madany, Oscar Perez-Priego, Vicente Burchard-Levine, Arnaud Carrara, Mirco Migliavacca
Publikováno v:
Remote Sensing, Vol 12, Iss 6, p 904 (2020)
Remote Sensing; Volume 12; Issue 6; Pages: 904
Remote Sensing
Digital.CSIC. Repositorio Institucional del CSIC
instname
Remote Sensing; Volume 12; Issue 6; Pages: 904
Remote Sensing
Digital.CSIC. Repositorio Institucional del CSIC
instname
© 2020 by the authors.
The thermal-based two-source energy balance (TSEB) model has accurately simulated energy fluxes in a wide range of landscapes with both remote and proximal sensing data. However, tree-grass ecosystems (TGE) have notably c
The thermal-based two-source energy balance (TSEB) model has accurately simulated energy fluxes in a wide range of landscapes with both remote and proximal sensing data. However, tree-grass ecosystems (TGE) have notably c
Autor:
Oscar Perez-Priego, Markus Reichstein, Xuanlong Ma, Yunpeng Luo, Rosario Gonzalez-Cascon, Arnaud Carrara, Tiana W. Hammer, Edoardo Cremonese, Gianluca Filippa, M. Pilar Martín, Mirco Migliavacca, Andrew D. Richardson, Javier Pacheco-Labrador, Tarek S. El-Madany, Marta Galvagno, Bernhard Ahrens, Gerardo Moreno, Christine Römermann
Publikováno v:
Digital.CSIC. Repositorio Institucional del CSIC
instname
Remote Sensing
Repositorio de Resultados de Investigación del INIA
Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria INIA
INIA: Repositorio de Resultados de Investigación del INIA
Remote Sensing; Volume 10; Issue 8; Pages: 1293
Remote Sensing, Vol 10, Iss 8, p 1293 (2018)
instname
Remote Sensing
Repositorio de Resultados de Investigación del INIA
Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria INIA
INIA: Repositorio de Resultados de Investigación del INIA
Remote Sensing; Volume 10; Issue 8; Pages: 1293
Remote Sensing, Vol 10, Iss 8, p 1293 (2018)
Tree–grass ecosystems are widely distributed. However, their phenology has not yet been fully characterized. The technique of repeated digital photographs for plant phenology monitoring (hereafter referred as PhenoCam) provide opportunities for lon
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e839164ff021f4fce8074ef868912bf
http://hdl.handle.net/10261/169023
http://hdl.handle.net/10261/169023
Autor:
Tarek S. El-Madany, Christine Römermann, Gianluca Filippa, Andrew D. Richardson, Markus Reichstein, Oscar Perez-Priego, Tiana W. Hammer, M. Pilar Martín, Marta Galvagno, Arnaud Carrara, Xuanlong Ma, Mirco Migliavacca, Edoardo Cremonese, Bernhard Ahrens, Yunpeng Luo, Gerardo Moreno, Javier Pacheco-Labrador, Rosario Gonzalez-Cascon
Publikováno v:
Remote Sensing, Vol 11, Iss 6, p 726 (2019)
Digital.CSIC. Repositorio Institucional del CSIC
instname
Digital.CSIC. Repositorio Institucional del CSIC
instname
Tree–grass ecosystems are widely distributed. However, their phenology has not yet been fully characterized. The technique of repeated digital photographs for plant phenology monitoring (hereafter referred as PhenoCam) provide opportunities for lon