DOI: 10.1016/j.jag.2014.01.017
Scopus记录号: 2-s2.0-84897520306
论文题名: Aquatic vegetation indices assessment through radiative transfer modeling and linear mixture simulation
作者: Villa P ; , Mousivand A ; , Bresciani M
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 30, 期: 1 起始页码: 113
结束页码: 127
语种: 英语
英文关键词: NDAVI
; Radiative transfer models
; Remote sensing
; Sensitivity analysis
; Vegetation indices
; WAVI
Scopus关键词: aquatic environment
; environmental assessment
; modeling
; NDVI
; radiative transfer
; remote sensing
; sensitivity analysis
; vegetation cover
; vegetation type
; Italy
; Lake Garda
英文摘要: Although spectral vegetation indices (VIs) have been widely used for remote sensing of vegetation in general, such indices have been traditionally targeted at terrestrial, more than aquatic, vegetation. This study introduces two new VIs specifically targeted at aquatic vegetation: NDAVI and WAVI and assesses their performance in capturing information about aquatic vegetation features by comparison with pre-existing indices: NDVI, SAVI and EVI. The assessment methodology is based on: (i) theoretical radiative transfer modeling of vegetation canopy-backgrounds coupling, and (ii) spectral linear mixture simulation based on real-case endmembers. Two study areas, Lake Garda and Lakes of Mantua, in Northern Italy, and a multisensor dataset have been exploited for our study. Our results demonstrate the advantages of the new indices. In particular, NDAVI and WAVI sensitivity scores to LAI and LIDF parameters were generally higher than pre-existing indices' ones. Radiative transfer modeling and real-case based linear mixture simulation showed a general positive, non-linear correlation of vegetation indices with increasing LAI and vegetation fractional cover (FC), more marked for NDVI and NDAVI. Moreover, NDAVI and WAVI show enhanced capabilities in separating terrestrial from aquatic vegetation response, compared to pre-existing indices, especially of NDVI. The new indices provide good performance in distinguishing aquatic from terrestrial vegetation: NDAVI over low density vegetation (LAI < 0.7-1.0, FC < 40-50%), and WAVI over medium-high density vegetation (LAI > 1.0, FC > 50%). Specific vegetation indices can therefore improve remote sensing applications for aquatic vegetation monitoring. © 2014 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79717
Appears in Collections: 气候变化事实与影响
There are no files associated with this item.
作者单位: Institute for Electromagnetic Sensing of the Environment, National Research Council (IREA-CNR), Via Bassini 15, 20133 Milan, Italy; Department of Geoscience and Remote Sensing, Delft University of Technology (TUDelft), Delft, Netherlands
Recommended Citation:
Villa P,, Mousivand A,, Bresciani M. Aquatic vegetation indices assessment through radiative transfer modeling and linear mixture simulation[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,30(1)