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首页> 外文期刊>Photogrammetric Engineering & Remote Sensing: Journal of the American Society of Photogrammetry >An Improved GPU-Based Parallel Computing Method for Landscape Index Calculation in Urban Area
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An Improved GPU-Based Parallel Computing Method for Landscape Index Calculation in Urban Area

机译：一种改进的基于GPU的平行计算方法，用于城市地区景观指数计算

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摘要

With the development of urbanization in the world, dealing with the problems caused by urban expansion is becoming more and more important. The data that need to be processed in urbanization studies have increased with the improvement of the spatial and temporal resolution of remote sensing satellites, exerting considerable pressure on traditional software used for landscape index computation. In this article, an improved landscape index-computing algorithm is proposed. Based on CULA, a pixel-group parallelization strategy is adopted to optimize the algorithm. The results show that the proposed algorithm increases the efficiency by more than a factor of three as the amount of data to be processed increases to 50 million pixels, thus providing a new way to calculate large-scale landscape index values on personal computers to study urbanization.
机译：随着世界城市化的发展，应对城市扩张带来的问题变得越来越重要。随着遥感卫星空间和时间分辨率的提高，城市化研究中需要处理的数据有所增加，对用于景观指数计算的传统软件造成了相当大的压力。本文提出了一种改进的景观指数计算算法。基于CULA，采用像素组并行化策略对算法进行优化。结果表明，当待处理的数据量增加到5000万像素时，该算法的效率提高了三倍以上，从而为在个人计算机上计算大规模景观指数值以研究城市化提供了一种新方法。

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