首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >LAND USE/LAND COVER CHANGE DETECTION USING MULTI–TEMPORAL SATELLITE DATASET: A CASE STUDY IN ISTANBUL NEW AIRPORT
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LAND USE/LAND COVER CHANGE DETECTION USING MULTI–TEMPORAL SATELLITE DATASET: A CASE STUDY IN ISTANBUL NEW AIRPORT

机译:基于多时相卫星数据集的土地利用/土地覆盖变化检测:以伊斯坦布尔新机场为例

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In recent years, especially in metropolitan cities such as Istanbul, the emerging needs of the increasing population and demand for better air transportation capacity have led to big environmental changes. One of them is originated due to the construction of the new airport (Istanbul Grand Airport – IGA), located on the Black Sea coast on the European side of Turkey and expected as “The biggest hub in Europe” by the early 2020s. The construction has five phases and first construction phase is scheduled to finish up by the end of 2018. With an advanced space technologies including remote sensing, environmental consequences due to Land Use/Land Cover changes (LULC) can be monitored and determined efficiently. The aim of this paper is to analyse LULC changes especially in the forest areas and water bodies by using two different satellite image dataset. In this context, supervised classification method and different spectral indices are applied to both Landsat-8 (2013–2017) and Sentinel 2A (2015–2017) image datasets to demonstrate the total and annual changes during the construction of the first phase. The efficiency of two datasets is outlined by comparison of the output thematic map accuracies.
机译:近年来,尤其是在伊斯坦布尔这样的大城市中,不断增长的人口需求和对更好的航空运输能力的需求导致了巨大的环境变化。其中一个起源于新机场的建设(伊斯坦布尔大机场– IGA),该机场位于土耳其欧洲一侧的黑海沿岸,预计到2020年代初将成为“欧洲最大的枢纽”。该建设分为五个阶段,第一阶段计划于2018年底完成。借助包括遥感在内的先进太空技术,可以有效地监测和确定土地用途/土地覆被变化(LULC)所造成的环境后果。本文的目的是通过使用两个不同的卫星图像数据集来分析LULC的变化,尤其是在森林地区和水体中。在这种情况下,将监督分类方法和不同的光谱指数应用于Landsat-8(2013–2017)和Sentinel 2A(2015–2017)图像数据集,以展示第一阶段施工期间的总体和年度变化。通过比较输出专题图的准确性,概述了两个数据集的效率。

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