Hyperspectral Remote Sensing of Vegetation Traits and Function

  in Special Issue   Posted on November 2, 2017

Information for the Special Issue

Submission Deadline: Sun 30 Sep 2018
Journal Impact Factor : 6.265
Journal Name : Remote Sensing of Environment
Journal Publisher:
Website for the Special Issue: https://www.journals.elsevier.com/remote-sensing-of-environment/call-for-papers/special-issue-on-hyperspectral-remote-sensing-of-vegetation
Journal & Submission Website: https://www.journals.elsevier.com/remote-sensing-of-environment

Special Issue Call for Papers:

Call for Papers

Special Issue on

Hyperspectral Remote Sensing of Vegetation Traits and Function

To understand carbon dynamics, we need to know how vegetation characteristics affect photosynthesis dynamics and ecosystem functions. Remote sensing has long been used to study terrestrial carbon and water cycles at regional and global scale. Remote sensing data have been shown to be useful for mapping vegetation structural parameters, such as leaf area index, clumping index and fractional vegetation cover. These parameters have been used as key inputs to terrestrial biosphere, ecological, hydrological and meteorological models.

In recent years, plant traits are increasingly recognized as a key role to understand and predict the adaptation of ecosystems to environmental changes. With the increased availability of trait data, the use of trait-based approaches are increasing to obtain an insight into the functional aspects of plant communities. Plant traits therefore provide a promising basis for a more quantitative and predictive global change science. In this regard, satellite remote sensing of terrestrial ecosystems has evolved from vegetation structural mapping to the retrievals of leaf and canopy traits and function, allowing for improved estimation of vegetation processes such as photosynthesis and its associated water and carbon cycles. More specifically, the recent advances of hyperspectral observations and sun-induced chlorophyll fluorescence from satellite and aircraft instruments provide a wide range of observational capability, in terms of spatial, temporal, and spectral resolutions. This provides new sources of information useful for studying terrestrial carbon and water cycles at regional and global scale.

In this Special Issue on “Hyperspectral Remote Sensing of Vegetation Traits and Function,” we will report remote sensing techniques and algorithms developed for retrieving plant functional traits, such as pigments (chlorophyll, xanthophyll, etc.) and nitrogen content, and functional parameters, such as the instantaneous light use efficiency (LUE) and the maximum carboxylation rate (Vcmax), etc. Topics may range from ground-based investigation on the processes of non-photochemical quenching that affect the photochemical reflectance index (PRI) and chlorophyll fluorescence at the leaf and canopy levels to regional and global mapping of leaf pigment contents, LUE and Vcmax. The ground-level investigation may make use of concurrent site-level measurements of leaf traits, functional parameters, and carbon and water fluxes in various ecosystems of the globe in conjunction with tower-based remote sensing monitoring. Methodologies are particularly welcome for retrieving leaf-level information from canopy-level remote sensing data through combined use of satellite and airborne sensors of various types including multispectral, hyperspectral, multi-angle, high spatial resolution, and LiDAR sensors. Modeling efforts are also welcome to demonstrate the potential of novel data streams for data assimilation or for the retrieval of relevant parameters for understanding carbon and water cycle estimation at site, regional and global scale.

Submissions are due by September 30, 2018. Submit your paper under the “ Plant Traits from RS Special Issue” using RSE’s online submission system. The authors should follow the RSE Author Guidelines for preparing and submitting their papers. The printed version of the Special Issue will be available in Fall 2019; however, accepted papers will be available online shortly after they have been accepted for publication.

Guest Editors:

Yongguang Zhang, International Institute for Earth System Science, Nanjing University, Nanjing, China

Mirco Migliavacca, Max Planck Institute for Biogeochemistry, Jena, Germany

Josep Peñuelas, Global Ecology Unit CREAF-CSIC-UB-UAB in CREAF -Universitat Autònoma de Barcelona, Spain

Weimin Ju, International Institute for Earth System Science, Nanjing University, Nanjing, China

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