کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
4949181 1364221 2018 16 صفحه PDF ندارد دانلود رایگان
عنوان انگلیسی مقاله
Spatial data compression via adaptive dispersion clustering
ترجمه فارسی عنوان
فشرده سازی داده های مکانی از طریق خوشه بندی پراکندگی تطبیقی
کلمات کلیدی
فشرده سازی داده های فضایی؛ خوشه طیفی؛ خوشه های فضایی؛ تابع پراکندگی مکانی؛
Spatial data compression; Spectral clustering; Spatial clusters; Spatial dispersion function;
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
چکیده انگلیسی

Adaptive Spatial Dispersion Clustering (ASDC), a new method of spatial data compression, is specifically designed to reduce the size of a spatial dataset in order to facilitate subsequent spatial prediction. Unlike traditional data and image compression methods, the goal of ASDC is to create a new dataset that will be used as input into spatial-prediction methods, such as traditional kriging or Fixed Rank Kriging, where using the full dataset may be computationally infeasible. ASDC can be classified as a lossy compression method and is based on spectral clustering. It aims to produce contiguous spatial clusters and to preserve the spatial-correlation structure of the data so that the loss of predictive information is minimal. An extensive simulation study demonstrates the predictive performance of these adaptively compressed datasets for several scenarios. ASDC is compared to two other data-reduction schemes, one using local neighborhoods and one using simple binning. An application to remotely sensed sea-surface-temperature data is also presented, and computational costs are discussed.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 117, January 2018, Pages 138-153
نویسندگان
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