DOI: 10.1016/j.jag.2015.06.001
Scopus记录号: 2-s2.0-84943608991
论文题名: Advances in remote sensing of vegetation function and traits
作者: Houborg R ; , Fisher J ; B ; , Skidmore A ; K
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2015
卷: 43 起始页码: 1
结束页码: 6
语种: 英语
英文关键词: Hyperspectral
; Multispectral
; Remote sensing
; Satellites
; Thermal
; Traits
; UAV
; Vegetation function
Scopus关键词: aerial survey
; functional role
; future prospect
; multispectral image
; remote sensing
; satellite data
; unmanned vehicle
; vegetation cover
英文摘要: Remote sensing of vegetation function and traits has advanced significantly over the past half-centuryin the capacity to retrieve useful plant biochemical, physiological and structural quantities across arange of spatial and temporal scales. However, the translation of remote sensing signals into mean-ingful descriptors of vegetation function and traits is still associated with large uncertainties due tocomplex interactions between leaf, canopy, and atmospheric mediums, and significant challenges in thetreatment of confounding factors in spectrum-trait relations. This editorial provides (1) a backgroundon major advances in the remote sensing of vegetation, (2) a detailed timeline and description of rel-evant historical and planned satellite missions, and (3) an outline of remaining challenges, upcomingopportunities and key research objectives to be tackled. The introduction sets the stage for thirteen Spe-cial Issue papers here that focus on novel approaches for exploiting current and future advancementsin remote sensor technologies. The described enhancements in spectral, spatial and temporal resolutionand radiometric performance provide exciting opportunities to significantly advance the ability to accu-rately monitor and model the state and function of vegetation canopies at multiple scales on a timelybasis. © 2015 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79507
Appears in Collections: 气候变化事实与影响
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作者单位: Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Saudi Arabia; Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA, United States; Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, Hengelosestraat 99, Enschede, Netherlands
Recommended Citation:
Houborg R,, Fisher J,B,et al. Advances in remote sensing of vegetation function and traits[J]. International Journal of Applied Earth Observation and Geoinformation,2015-01-01,43