کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
4464589 1313835 2016 10 صفحه PDF ندارد دانلود رایگان
عنوان انگلیسی مقاله
Robust Change Vector Analysis (RCVA) for multi-sensor very high resolution optical satellite data
ترجمه فارسی عنوان
آنالیز برداری تغییر مقاوم (RCVA) برای داده های ماهواره ای نوری چندحسگر با وضوح بسیار بالا
کلمات کلیدی
سنسور متقاطع . تغییر تشخیص؛ محله پیکسل. دوزمانه؛ سنجش از دور؛ هندسه خورشید هدف سنسور
Cross-sensor; Change detection; Pixel neighborhood; Bi-temporal; Remote sensing; Sun-target-sensor geometry
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات کامپیوتر در علوم زمین
چکیده انگلیسی


• Variable sun position and sensor viewing geometry affect change detection results.
• We present the approach Robust Change Vector Analysis (RCVA).
• RCVA considers pixel neighborhood.
• The approach is robust against effects of sun and viewing geometry.
• RCVA allows for efficient cross-sensor change detection.

The analysis of rapid land cover/land use changes by means of remote sensing is often based on data acquired under varying and occasionally unfavorable conditions. In addition, such analyses frequently use data acquired by different sensor systems. These acquisitions often differ with respect to sun position and sensor viewing geometry which lead to characteristic effects in each image. These differences may have a negative impact on reliable change detection. Here, we propose an approach called Robust Change Vector Analysis (RCVA), aiming to mitigate these effects. RCVA is an improvement of the widely-used Change Vector Analysis (CVA), developed to account for pixel neighborhood effects. We used a RapidEye and Kompsat-2 cross-sensor change detection test to demonstrate the efficiency of RCVA. Our analysis showed that RCVA results in fewer false negatives as well as false positives when compared to CVA under similar test conditions. We conclude that RCVA is a powerful technique which can be utilized to reduce spurious changes in bi-temporal change detection analyses based on high- or very-high spatial resolution imagery.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Applied Earth Observation and Geoinformation - Volume 50, August 2016, Pages 131–140
نویسندگان
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