کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6346597 | 1621245 | 2014 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Change detection of boreal forest using bi-temporal ALOS PALSAR backscatter data
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
کامپیوتر در علوم زمین
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Long-wavelength Synthetic Aperture Radar (SAR) satellite systems have the potential to increase the efficiency of forest mapping and monitoring, which today are based primarily on optical satellite systems. Here, we evaluate the effectiveness of using L-band SAR satellite images to detect and delineate clear-cuts in Swedish boreal forest. A set of computationally efficient techniques are combined in a fully automated unsupervised bi-temporal change detection approach that detects changes in SAR backscatter intensities. For radiometric normalization and initial change classification, we propose an iterative procedure consisting of successive polynomial based histogram matching and thresholding. Recently proposed methods for automatic SAR amplitude ratio thresholding and final change classification are adopted. The latter is a Markov random field based change detection method that exploits both spectral and spatial information from one or multiple SAR polarization channels. The change detection approach was applied to SAR images from the Japanese Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) acquired in Fine Beam Dual (FBD) mode (HH- and HV-polarizations) with a pixel size of 20Â m (path data). Clear-cuts that took place between image acquisitions were clearly detected, and most errors were due to imperfect delineations of clear-cut edges. Pixel-wise clear-cut detection accuracies above 90% could be reached, with false alarm rates of approximately 10% or less. The results indicate that ALOS PALSAR path data are well suited for operational clear-cut detection in Swedish boreal forest.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Remote Sensing of Environment - Volume 155, December 2014, Pages 120-128
Journal: Remote Sensing of Environment - Volume 155, December 2014, Pages 120-128
نویسندگان
Andreas Pantze, Maurizio Santoro, Johan E.S. Fransson,