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Thermal Analysis of Climate Regions Using Remote Sensing and Grid Computing

机译:利用遥感和网格计算对气候区域进行热分析

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The analysis of climate regions is very important for designers and architects, because the increase in density and built up spaces and reduction in open spaces and green lands induce the increase of heat, especially in an urban area, deteriorating the environment and causing health problems. This study analyzes the Land Surface Temperature (LST) differences in the region of Dobrogea, Romania, and compares with the land use and land cover types using TM and ETM+ data of 1989 and 2000. As the analysis is performed on large data sets, we used Grid Computing to implement a service for using on Computational Grids with a Web-based client interface, which will be greatly useful and convenient for those who are studying the ground thermal environment and heat island effects by using Landsat TM/ETM+ bands, and have typical workstations, with no special computing and storing resources for computationally intensive satellite image processing and no license for a commercial image processing tool. Based on the satellite imagery, the paper also addresses a Supervised Classification algorithm and the computation of two indices of great value in water resources management, Normalized Difference Vegetation Index (NDVI), respectively Land Surface Emissivity (LSE).
机译:对气候区域的分析对于设计师和建筑师而言非常重要,因为密度和建成空间的增加以及开放空间和绿地的减少会导致热量增加,尤其是在城市地区,从而使环境恶化并造成健康问题。这项研究分析了罗马尼亚Dobrogea地区的地表温度(LST)差异,并使用1989年和2000年的TM和ETM +数据与土地利用和土地覆盖类型进行了比较。由于对大数据集进行了分析,因此我们使用Grid Computing来实现具有基于Web的客户端界面的计算网格上使用的服务,这对于那些使用Landsat TM / ETM +波段研究地面热环境和热岛效应的人来说将是非常有用和方便的,并且具有典型的工作站,没有用于计算密集型卫星图像处理的特殊计算和存储资源,也没有商业图像处理工具的许可证。在卫星图像的基础上,本文还提出了一种监督分类算法和两个在水资源管理中具有重要价值的指标(归一化植被指数(NDVI)和地表发射率(LSE))的计算方法。

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