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Quantifying Changes of Villages in the Urbanizing Beijing Metropolitan Region: Integrating Remote Sensing and GIS Analysis

机译:定量化都市圈中乡村的变化:遥感与GIS分析相结合

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Rapid urbanization has resulted in great changes in rural landscapes globally. Using remote sensing data to quantify the distribution of rural settlements and their changes has received increasing attention in the past three decades, but remains a challenge. Previous studies mostly focused on the residential changes within a grid or administrative boundary, but not at the individual village level. This paper presents a new change detection approach for rural residential settlements, which can identify different types of rural settlement changes at the individual village level by integrating remote sensing and Geographic Information System (GIS) analyses. Using multi-temporal Landsat TM image data, this approach classifies villages into five types: “no change”, “totally lost”, “shrinking”, “expanding”, and “merged”, in contrast to the commonly used “increase” and “decrease”. This approach was tested in the Beijing metropolitan area from 1984 to 2010. Additionally, the drivers of such changes were investigated using multinomial logistic regression models. The results revealed that: (1) 36% of the villages were lost, but the total area of developed lands in existing villages increased by 34%; (2) Changes were dominated by the type of ‘expansion’ in 1984–1990 (accounted for 43.42%) and 1990–2000 (56.21%). However, from 2000 to 2010, 49.73% of the villages remained unchanged; (3) Both topographical factors and distance factors had significant effects on whether the villages changed or not, but their impacts changed through time. The topographical driving factors showed decreasing effects on the loss of rural settlements, while distance factors had increasing impacts on settlement expansion and merging. This approach provides a useful tool for better understanding the changes in rural residential settlements and their associations with urbanization.
机译:快速的城市化已导致全球农村景观发生了巨大变化。在过去的三十年中,使用遥感数据量化农村居民点的分布及其变化已受到越来越多的关注,但仍然是一个挑战。先前的研究主要集中在网格或行政边界内的住所变更,而不是在单个村庄一级。本文提出了一种新的农村居民点变化检测方法,该方法可以通过结合遥感和地理信息系统(GIS)分析来识别单个村庄级别的不同类型的农村居民点变化。与常用的“增加”和“增加”相比,这种方法利用多时态Landsat TM图像数据将村庄分为五种类型:“不变”,“完全丧失”,“萎缩”,“扩张”和“合并”。 “减少”。 1984年至2010年在北京都市区对该方法进行了测试。此外,使用多项逻辑回归模型研究了此类变化的驱动因素。结果表明:(1)失去了36%的村庄,但现有村庄的已开发土地总面积增加了34%; (2)在1984-1990年(占43.42%)和1990-2000年(56.21%)的“扩张”类型中,变化占主导地位。但是,从2000年到2010年,仍有49.73%的村庄保持不变; (3)地形因素和距离因素都对村庄是否改变有重大影响,但其影响随着时间而改变。地形驱动因素显示对农村居民点丧失的影响减小,而距离因素对居民点扩张和合并的影响增加。这种方法为更好地了解农村居民点的变化及其与城市化的联系提供了有用的工具。

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