尼日利亚科吉州Lokoja洪水淹没的空间和季节格局

Usman Umar Jimoh
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引用次数: 1

摘要

该研究调查了尼日利亚科吉州Lokoja的洪水淹没的空间模式。利用监督土地利用/覆被分类技术中的最大似然分类算法。分析结果用于估计洪水淹没事件的震级和可视化的季节和空间格局。从美国地质调查局门户网站(2018年)获取8幅陆地卫星图像,每年(旱季和雨季)两组。Landsat图像被划分为土地覆盖类,如建筑物、植被和水体。在完成土地覆盖分类后,确定每个类别的面积,并将其转换为湿季和旱季的平方公里和百分比。根据分类,棕色代表建成区,蓝色代表水体,绿色代表植被。最后,使用历史Google Earth图像、已知区域知识和GPS坐标进行精度评估。arcmap10.5用于制作研究期间的土地利用/覆盖地图。结果表明,洪涝灾害对植被的影响更为强烈。1999年、2009年、2012年和2018年的植被损失率分别为1.62%、4.60%、23.05%和6.43%。因此,应鼓励努力提高对多变天气、洪水淹没和季节性不确定性的抵御能力。
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Spatial and Seasonal Patterns of Flood Inundation in Lokoja, Kogi State, Nigeria
The study examines spatial patterns of flood inundation in Lokoja, Kogi state, Nigeria. Maximum Likelihood Classifier algorithm of the supervised land use/cover classification technique was utilized. The results obtained from the analysis were used to estimate the magnitude and visualize the seasonal and spatial pattern of flood inundation event. Eight Landsat Images comprising of two sets for each year (dry and wet seasons) were acquired from the portal of United States Geological Survey (2018). The Landsat images were classified into land cover classes such as Built Up, Vegetation and Water Body. After completing the land cover classification, the area of each class was determined and converted to square kilometers and percentages for both wet and dry seasons. Based on the classification, the brown colour depicts the built-up areas, blue for water body, and green for vegetation. Finally, accuracy assessment was carried out using historical Google Earth images, informed knowledge of the area, and GPS coordinates. ArcMap 10.5 was used to produce land use/cover maps for the study period. The result overall, revealed the effect of flood inundation to be more intense on vegetation. 1.62%, 4.60%, 23.05% and 6.43% of vegetated land was lost in 1999, 2009, 2012 and 2018, respectively.  Therefore, efforts to improve resilience against variable weather, flood inundation and seasonal uncertainties should be encouraged.
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来源期刊
CiteScore
0.10
自引率
0.00%
发文量
11
审稿时长
15 weeks
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