首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >SPATIOTEMPORAL CHANGE OF URBAN AGRICULTURE USING GOOGLE EARTH IMAGERY: A CASE OF MUNICIPALITY OF NAKHONRATCHASIMA CITY, THAILAND
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SPATIOTEMPORAL CHANGE OF URBAN AGRICULTURE USING GOOGLE EARTH IMAGERY: A CASE OF MUNICIPALITY OF NAKHONRATCHASIMA CITY, THAILAND

机译:谷歌地球影像对城市农业的时空变化:以泰国那空拉差沙玛市为例

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Presently, urban agriculture (UA) is an important part of the urban ecosystem and a key factor that can help in the urban environmental management. Therefore, this paper studies a spatial-temporal analysis of UA areas and types in Municipality of Nakhonratchasima City (MNC), Thailand. This UA types referred land use classification system of Land Development Department (LDD). Google Earth images acquired in the years of 2007, 2011, 2015 and 2018 were used to examine UA change with segmentation-based classification method in QGIS to classify Google Earth images into thematic maps. Moreover, this study showed different spatiotemporal change patterns, composition and rates in the study area and indicates the importance of analyzing UA change. Therefore, the results of this classification consisted of eleven classes – abandoned paddy field, rice paddy, abandoned field crop, mixed field crop, cassava, betel palm, mixed orchard, coconut, rose apple, truck crop, and fish farm. Truck crop had the greatest cover in study area while floricultural covered the minimal space over periods of study. The UA change analysis over time for entire study areas provides an overall picture of change trends. Furthermore, the UA change at census sector scale gives new insights on how human-induced activities (e.g., built-up areas and roads) affect UA change patterns and rates. This research indicates the necessity to implement change detection for better understanding the UA change patterns and rates.
机译:当前,城市农业(UA)是城市生态系统的重要组成部分,并且是有助于城市环境管理的关键因素。因此,本文研究了泰国那空拉差西玛市(MNC)市UA区域和类型的时空分析。此UA类型是指土地开发部(LDD)的土地使用分类系统。使用2007、2011、2015和2018年获取的Google Earth图像,通过QGIS中基于分段的分类方法检查UA变化,以将Google Earth图像分类为专题图。此外,这项研究显示了研究区域内不同的时空变化模式,组成和变化率,并表明了分析UA变化的重要性。因此,此分类的结果包括11个类别-废弃的稻田,稻田,废弃的田间作物,混合的田间作物,木薯,槟榔,混合果园,椰子,玫瑰苹果,卡车农作物和养鱼场。在研究期间,卡车农作物的覆盖面积最大,而花卉种植面积最小。整个研究领域的UA随时间变化的分析提供了变化趋势的总体情况。此外,在人口普查行业范围内的UA变更为人为活动(例如,建成区和道路)如何影响UA变更模式和比率提供了新见解。这项研究表明有必要实施变更检测以更好地了解UA变更模式和速率。

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