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Degradation of Urban Green Spaces in Lagos, Nigeria: Evidence from Satellite and Demographic Data

机译:尼日利亚拉各斯城市绿地的退化:来自卫星和人口统计数据的证据

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The study aimed to assess the potential of using Remote Sensing (RS) da-ta to evaluate the changes of urban green spaces in Lagos, Nigeria. Land-sat Thematic Mapper and Landsat 8 (Operational Land Imager) data pair of May 4, 1986, December 12, 2002 and January 1, 2019 covering Lagos Government Authority (LGA) were used for this study. Supervised image classification technique using Maximum Likelihood Classifier (MLC) was used to create base map which was then used for ground truthing. Ran-dom Forest (RF) classification technique using RF classifier was utilized in this study to generate the final land use land cover map. RF is an en-semble learning method for classification that operates by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes (classification). Lagos census population data was also used in this study to model population projection. Extrapolation of the model was used to predict data for the years, 2020 and 2040. Re-sults of the study revealed a reduction of urban green spaces due to agri-culture and settlement. While the remote mapping revealed the gradual dispersion of ecosystem degradation indicators spread across the state, there exists clusters of areas vulnerable to environmental hazards across Lagos. To mitigate these risks, the paper offered recommendations rang-ing from the need for effective policy to green planning education for city managers, developers and risk assessment. These measures will go a long way in helping sustainability and management of land resources in Lagos.
机译:该研究旨在评估使用遥感(RS)DA-TA的潜力,以评估尼日利亚拉各斯城市绿地的变化。 1986年5月4日,2002年12月12日和2019年1月1日覆盖了Lagos政府权威(LGA)的土地定位主题映射器和Landsat 8(运营陆地成像仪)数据对被用于本研究。使用最大似然分类器(MLC)的监督图像分类技术用于创建基本映射,然后用于接地特征。使用RF分类器的RAN-DOM森林(RF)分类技术在本研究中使用了最终的土地使用陆地覆盖图。 RF是一种用于分类的en-Semble学习方法,其通过在训练时间构造多个决策树并输出作为类别的模式(分类)的类来操作。拉各斯人口普查人口数据也用于本研究以模拟人口投影。该模型的外推用于预测多年,2020年和2040年的数据。该研究的再见表明,由于农业文化和结算,城市绿地的减少了。虽然远程映射显示了生态系统退化指标的逐步分散,但在整个州传播的逐步分散,但存在易受拉各斯环境危害的区域集群。为了减轻这些风险,本文提出了建议,从需要为城市经理,开发商和风险评估的绿色规划教育提供有效政策。这些措施将有助于帮助拉各斯土地资源的可持续性和管理。

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