کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4459439 1621288 2011 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Estimating zero-plane displacement height and aerodynamic roughness length using synthesis of LiDAR and SPOT-5 data
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات کامپیوتر در علوم زمین
پیش نمایش صفحه اول مقاله
Estimating zero-plane displacement height and aerodynamic roughness length using synthesis of LiDAR and SPOT-5 data
چکیده انگلیسی

In this study, a combination of low and high density airborne LiDAR and satellite SPOT-5 HRG data were used in conjunction with ground measurements of forest structure to parameterize four models for zero-plane displacement height d(m) and aerodynamic roughness length z0m(m), over cool-temperate forests in Heihe River basin, an arid region of Northwest China. For the whole study area, forest structural parameters including tree height (Ht) (m), first branch height (FBH) (m), crown width (CW) (m) and stand density (SD)(trees ha− 1) were derived by stepwise multiple linear regressions of ground-based forest measurements and height quantiles and fractional canopy cover (fc) derived from the low density LiDAR data. The high density LiDAR data, which covered a much smaller area than the low density LiDAR data, were used to relate SPOT-5's reflectance to the effective plant area index (PAIe) of the forest. This was done by linear spectrum decomposition and Li–Strahler geometric–optical models. The result of the SPOT-5 spectrum decomposition was applied to the whole area to calculate PAIe (and leaf area index LAI). Then, four roughness models were applied to the study area with these vegetation data derived from the LiDAR and SPOT-5 as input. For validation, measurements at an eddy covariance site in the study area were used. Finally, the four models were compared by plotting histograms of the accumulative distribution of modeled d and z0m in the study area. The results showed that the model using by frontal area index (FAI) produced best d estimate, and the model using both LAI and FAI generated the best z0m. Furthermore, all models performed much better when the representative tree height was Lorey's mean height instead of using an arithmetic mean.

Research highlights
► Reasonable forest parameters were obtained by using LiDAR and SPOT-5 data.
► Four roughness models were applied to estimate the area-wide d and z0m maps.
► Using Lorey's tree height, all models outperformed those using the mean height.
► The validities of four roughness models were tested by EC measurements.
► The performances of these models were cross-compared.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Remote Sensing of Environment - Volume 115, Issue 9, 15 September 2011, Pages 2330–2341
نویسندگان
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