Hauptseite > Publikationsdatenbank > Remote sensing of plant-water relations: An overview and future perspectives > print |
001 | 852604 | ||
005 | 20210129235143.0 | ||
024 | 7 | _ | |a 10.1016/j.jplph.2018.04.012 |2 doi |
024 | 7 | _ | |a 0176-1617 |2 ISSN |
024 | 7 | _ | |a 1618-1328 |2 ISSN |
024 | 7 | _ | |a pmid:29735177 |2 pmid |
024 | 7 | _ | |a WOS:000439100400002 |2 WOS |
024 | 7 | _ | |a altmetric:49642694 |2 altmetric |
037 | _ | _ | |a FZJ-2018-05508 |
041 | _ | _ | |a English |
082 | _ | _ | |a 580 |
100 | 1 | _ | |a Damm, A. |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
245 | _ | _ | |a Remote sensing of plant-water relations: An overview and future perspectives |
260 | _ | _ | |a München |c 2018 |b Elsevier |
336 | 7 | _ | |a article |2 DRIVER |
336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1539238448_30019 |2 PUB:(DE-HGF) |
336 | 7 | _ | |a ARTICLE |2 BibTeX |
336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
520 | _ | _ | |a Vegetation is a highly dynamic component of the Earth surface and substantially alters the water cycle. Particularly the process of oxygenic plant photosynthesis determines vegetation connecting the water and carbon cycle and causing various interactions and feedbacks across Earth spheres. While vegetation impacts the water cycle, it reacts to changing water availability via functional, biochemical and structural responses. Unravelling the resulting complex feedbacks and interactions between the plant-water system and environmental change is essential for any modelling approaches and predictions, but still insufficiently understood due to currently missing observations. We hypothesize that an appropriate cross-scale monitoring of plant-water relations can be achieved by combined observational and modelling approaches. This paper reviews suitable remote sensing approaches to assess plant-water relations ranging from pure observational to combined observational-modelling approaches. We use a combined energy balance and radiative transfer model to assess the explanatory power of pure observational approaches focussing on plant parameters to estimate plant-water relations, followed by an outline for a more effective use of remote sensing by their integration into soil-plant-atmosphere continuum (SPAC) models. We apply a mechanistic model simulating water movement in the SPAC to reveal insight into the complexity of relations between soil, plant and atmospheric parameters, and thus plant-water relations. We conclude that future research should focus on strategies combining observations and mechanistic modelling to advance our knowledge on the interplay between the plant-water system and environmental change, e.g. through plant transpiration. |
536 | _ | _ | |a 582 - Plant Science (POF3-582) |0 G:(DE-HGF)POF3-582 |c POF3-582 |f POF III |x 0 |
588 | _ | _ | |a Dataset connected to CrossRef |
700 | 1 | _ | |a Paul-Limoges, E. |0 P:(DE-HGF)0 |b 1 |
700 | 1 | _ | |a Haghighi, E. |0 P:(DE-HGF)0 |b 2 |
700 | 1 | _ | |a Simmer, C. |0 P:(DE-HGF)0 |b 3 |
700 | 1 | _ | |a Morsdorf, F. |0 P:(DE-HGF)0 |b 4 |
700 | 1 | _ | |a Schneider, F. D. |0 P:(DE-HGF)0 |b 5 |
700 | 1 | _ | |a van der Tol, C. |0 P:(DE-HGF)0 |b 6 |
700 | 1 | _ | |a Migliavacca, M. |0 P:(DE-HGF)0 |b 7 |
700 | 1 | _ | |a Rascher, U. |0 P:(DE-Juel1)129388 |b 8 |e Last author |u fzj |
773 | _ | _ | |a 10.1016/j.jplph.2018.04.012 |g Vol. 227, p. 3 - 19 |0 PERI:(DE-600)2029184-X |p 3 - 19 |t Journal of plant physiology |v 227 |y 2018 |x 0176-1617 |
856 | 4 | _ | |u https://juser.fz-juelich.de/record/852604/files/1-s2.0-S0176161718301172-main.pdf |y Restricted |
856 | 4 | _ | |u https://juser.fz-juelich.de/record/852604/files/1-s2.0-S0176161718301172-main.pdf?subformat=pdfa |x pdfa |y Restricted |
909 | C | O | |o oai:juser.fz-juelich.de:852604 |p VDB |
910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 8 |6 P:(DE-Juel1)129388 |
913 | 1 | _ | |a DE-HGF |b Key Technologies |l Key Technologies for the Bioeconomy |1 G:(DE-HGF)POF3-580 |0 G:(DE-HGF)POF3-582 |2 G:(DE-HGF)POF3-500 |v Plant Science |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |
914 | 1 | _ | |y 2018 |
915 | _ | _ | |a Nationallizenz |0 StatID:(DE-HGF)0420 |2 StatID |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0310 |2 StatID |b NCBI Molecular Biology Database |
915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b J PLANT PHYSIOL : 2015 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |
915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Thomson Reuters Master Journal List |
915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0110 |2 StatID |b Science Citation Index |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |
915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0111 |2 StatID |b Science Citation Index Expanded |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1060 |2 StatID |b Current Contents - Agriculture, Biology and Environmental Sciences |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1030 |2 StatID |b Current Contents - Life Sciences |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |
915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |
920 | _ | _ | |l yes |
920 | 1 | _ | |0 I:(DE-Juel1)IBG-2-20101118 |k IBG-2 |l Pflanzenwissenschaften |x 0 |
980 | _ | _ | |a journal |
980 | _ | _ | |a VDB |
980 | _ | _ | |a I:(DE-Juel1)IBG-2-20101118 |
980 | _ | _ | |a UNRESTRICTED |
Library | Collection | CLSMajor | CLSMinor | Language | Author |
---|