کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5428535 1508682 2014 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Monitoring the broadleaf fraction and canopy cover of boreal forests using spectral invariants
ترجمه فارسی عنوان
نظارت بر پوشش کرتهای عرضی و سایبان جنگلهای بیرونی با استفاده از روشهای طیفی
موضوعات مرتبط
مهندسی و علوم پایه شیمی طیف سنجی
چکیده انگلیسی


- Spectrally invariant Directional Area Scattering Factor describes canopy structure.
- DASF tested for a boreal forest setting for the first time.
- Results support DASF as useful for monitoring mixed forests.

A recent method based on the spectral invariants theory to retrieve physically-based information on forest properties from remotely sensed hyperspectral imagery was tested in a southern boreal setting in central Finland. An atmospherically corrected Hyperion image and ground measurements from 66 forest stands were used. First, the novel concept of transformed green leaf single scattering spectral albedos was tested against leaf (needle) albedo measurements on Scots pine, Norway spruce and Silver birch from the study area. We found the transformed Beaked hazel albedo applied in previous studies could be used as reference also for the boreal tree species. Second, we derived a newly suggested spectrally invariant variable, the directional area scattering factor (DASF), to estimate the broadleaf fraction of forest stands. Based on our results, DASF seems highly promising as a potential new hyperspectral satellite product for change monitoring of broadleaf fraction over different vegetation zones. Finally, we plotted our results in the spectral invariants space, and suggest a new interpretation for the reference-dependent structural parameter pR. We propose this parameter is an indicator of canopy cover and suffers less from saturation problems than vegetation indices.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Quantitative Spectroscopy and Radiative Transfer - Volume 133, January 2014, Pages 482-488
نویسندگان
, , ,