Review of optical-based remote sensing for plant trait mapping

被引:328
作者
Homolova, Lucie [1 ,2 ]
Maenovsky, Zbynek [3 ]
Clevers, Jan G. P. W. [2 ]
Garcia-Santos, Glenda [1 ]
Schaeprnan, Michael E. [1 ]
机构
[1] Univ Zurich, Dept Geog, Remote Sensing Labs, CH-8057 Zurich, Switzerland
[2] Wageningen Univ, Lab Geo Informat Sci & Remote Sensing, NL-6700 AA Wageningen, Netherlands
[3] Univ Tasmania, Sch Geog & Environm Studies, Hobart, Tas 7001, Australia
关键词
Plant traits; Remote sensing; Plant ecology; Accuracy; Scaling; LEAF-AREA INDEX; LIGHT-USE EFFICIENCY; PHOTOCHEMICAL REFLECTANCE INDEX; GROSS PRIMARY PRODUCTION; DRY-MATTER CONTENT; TERRESTRIAL CHLOROPHYLL FLUORESCENCE; FOREST CANOPY REFLECTANCE; FUEL MOISTURE-CONTENT; NITROGEN CONCENTRATION; HYPERSPECTRAL DATA;
D O I
10.1016/j.ecocom.2013.06.003
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Plant trait data have been used in various studies related to ecosystem functioning, community ecology, and assessment of ecosystem services. Evidences are that plant scientists agree on a set of key plant traits, which are relatively easy to measure and have a stable and strong predictive response to ecosystem functions. However, the field measurements of plant trait data are still limited to small area, to a certain moment in time and to certain number of species only. Therefore, remote sensing (RS) offers potential to complement or even replace field measurements of some plant traits. It offers instantaneous spatially contiguous information, covers larger areas and in case of satellite observations profits from their revisit capacity. In this review, we first introduce RS concepts of light-vegetation interactions, RS instruments for vegetation studies, RS methods, and scaling between field and RS observations. Further we discuss in detail current achievements and challenges of optical RS for mapping of key plant traits. We concentrate our discussion on three categorical plant traits (plant growth and life forms, flammability properties and photosynthetic pathways and activity) and on five continuous plant traits (plant height, leaf phenology, leaf mass per area, nitrogen and phosphorous concentration or content). We review existing literature to determine the retrieval accuracy of the continuous plant traits. The relative estimation error using RS ranged between 10% and 45% of measured mean value, i.e. around 10% for plant height of tall canopies, 20% for plant height of short canopies, 15% for plant nitrogen, 25% for plant phosphorus content/concentration, and 45% for leaf mass per area estimates. The potential of RS to map plant traits is particularly high when traits are related to leaf biochemistry, photosynthetic processes and canopy structure. There are also other plant traits, i.e. leaf chlorophyll content, water content and leaf area index, which can be retrieved from optical RS well and can be of importance for plant scientists. We underline the need that future assessments of ecosystem functioning using RS should require comprehensive and integrated measurements of various plant traits together with leaf and canopy spectral properties. By doing so, the interplay between plant structural, physiological, biochemical, phenological and spectral properties can be better understood. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:1 / 16
页数:16
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