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Assessment of land use and land cover change using spatiotemporal analysis of landscape: case study in south of Tehran

机译:利用景观的时空分析评估土地利用和土地覆被变化:以德黑兰南部为例

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In the recent years, dust storms originating from local abandoned agricultural lands have increasingly impacted Tehran and. Karaj air quality. Designing and implementing mitigation plans are necessary to study land use/land cover change (LUCC). Land use/cover classification is particularly relevant in arid areas. This study aimed to map land use/cover by pixel- and object-based image classification methods, analyse landscape fragmentation and determine the effects of two different classification methods on landscape metrics. The same sets of ground data were used for both classification methods. Because accuracy of classification plays a key role in better understanding LUCC, both methods were employed. Land use/cover maps of the southwest area of Tehran city for the years 1985, 2000 and 2014 were obtained from Landsat digital images and classified into three categories: built-up, agricultural and barren lands. The results of our LUCC analysis showed that the most important changes in built-up agricultural land categories were observed in zone B (Shahriar, Robat Karim and Eslamshahr) between 1985 and 2014. The landscape metrics obtained for all categories pictured high landscape fragmentation in the study area. Despite no significant difference was evidenced between the two classification methods, the object-based classification led to an overall higher accuracy than using the pixel-based classification. In particular, the accuracy of the built-up category showed a marked increase. In addition, both methods showed similar trends in fragmentation metrics. One of the reasons is that the object-based classification is able to identify buildings, impervious surface and roads in dense urban areas, which produced more accurate maps.
机译:近年来,源自当地废弃农业土地的沙尘暴对德黑兰的影响越来越大。卡拉伊空气质量。设计和实施缓解计划对于研究土地使用/土地覆被变化(LUCC)是必要的。土地用途/覆盖物分类在干旱地区特别重要。这项研究旨在通过基于像素和对象的图像分类方法来绘制土地使用/覆盖图,分析景观破碎化并确定两种不同分类方法对景观指标的影响。两种分类方法均使用相同的地面数据集。由于分类的准确性在更好地了解LUCC中起着关键作用,因此两种方法都被采用。德黑兰市西南地区1985、2000和2014年的土地利用/覆盖图是从Landsat数字图像中获得的,分为三类:人为,耕地和荒地。我们的LUCC分析结果表明,在1985年至2014年之间,B区(Shahriar,Robat Karim和Eslamshahr)观察到了农业用地类别中最重要的变化。学习区。尽管两种分类方法之间没有明显差异,但基于对象的分类比使用基于像素的分类总体上具有更高的准确性。特别是,组合类别的准确性显着提高。此外,这两种方法在碎片度量方面都显示出相似的趋势。原因之一是基于对象的分类能够识别密集城市区域中的建筑物,不透水的地面和道路,从而生成更准确的地图。

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