کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4464722 1621823 2015 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Sub-footprint analysis to uncover tree height variation using ICESat/GLAS
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات کامپیوتر در علوم زمین
پیش نمایش صفحه اول مقاله
Sub-footprint analysis to uncover tree height variation using ICESat/GLAS
چکیده انگلیسی


• We proposed a sub-footprint analysis concept for large footprint GLAS data.
• We developed a refined Levenberg–Marquardt method for Gaussian decomposition.
• We achieved high accuracy to characterize tree heights’ variation in a footprint.

Detailed forest height data are an indispensable prerequisite for many forestry and earth science applications. Existing research of using Geoscience Laser Altimeter System (GLAS) data mainly focuses on deriving average or maximum tree heights within a GLAS footprint, i.e. an ellipse with a diameter of 65 m. However, in most forests, it is likely that the tree heights within such ellipse are heterogeneous. Therefore, it is desired to uncover detailed tree height variation within a GLAS footprint. To the best of our knowledge, no such methods have been reported as of now. In this study, we aim to characterize tree heights’ variation within a GLAS footprint as different layers, each of which corresponds to trees with similar heights. As such, we developed a new method that embraces two steps: first, a refined Levenberg–Marquardt (LM) algorithm is proposed to decompose raw GLAS waveform into multiple Gaussian signals, within which it is hypothesized that each vegetation signal corresponds to a particular tree height layer. Second, for each layer, three parameters were first defined: Canopy Top Height (CTH), Crown Length (CL), and Cover Proportion (CP). Then we extracted the three parameters from each Gaussian signal through a defined model. In order to test our developed method, we set up a study site in Ejina, China where the dominant specie is Populus euphratica. Both simulated and field tree height data were adopted. With regard to the simulation data, results presented a very high agreement for the three predefined parameters between our results and simulation data. When our methods were applied to the field data, the respective R2 become 0.78 (CTH), CL (R2 = 0.76), CP (R2 = 0.74). Overall, our studies revealed that large footprint GLAS waveform data have the potentials for obtaining detailed forest height variation.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Applied Earth Observation and Geoinformation - Volume 35, Part B, March 2015, Pages 284–293
نویسندگان
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