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Predicting Land Cover Using a GIS-Based Markov Chain and Sea Level Inundation for a Coastal Area

Land(2024)

Univ North Carolina Wilmington

Cited 0|Views7
Abstract
New Hanover County, North Carolina, has been experiencing rapid population growth and is expected to continue this growth, leading to increased land use and development in the area. The county is also threatened by sea level rise (SLR) and its effects because of its coastal location and frequent occurrences of major storms and hurricanes. This study used a land change modeler to map the land cover change throughout the county over a period of 20 years, and predicted land cover distribution in the area in the years 2030 and 2050. Statistics revealed that the developed land in the area increased by 85 km2 between 2000 and 2010, and by 60 km2 between 2010 and 2020. Such land is predicted to increase by another 73 km2 by 2030, and 63 km2 by 2050. This increase in development is expected to occur mainly in the central area of the county and along the barrier islands. Modeling of SLR illustrated that the northwestern part of New Hanover County along the Cape Fear River, as well as the beach towns located on the barrier islands, are estimated be the most affected locations. Results indicate that sections of major highways throughout the county, including I-140 near downtown Wilmington and US-421 in Carolina Beach, may be inundated by SLR, which might delay residents during mandatory evacuations for emergency situations such as hurricanes. Some routes may be unusable, leading to traffic congestion on other routes, which may impede some residents from reaching safety before the emergency. Wrightsville Beach and Carolina Beach are estimated to have the highest levels of inundation, with 71.17% and 40.58% of their land being inundated under the most extreme SLR scenario of 3 m, respectively. The use of the present research approach may provide a practical, quick, and low-cost method in modeling rapidly growing urban areas along the eastern United States coastline and locating areas at potential risk of future SLR inundation.
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Key words
land cover,neural network,land change modeler,minimum noise fraction,digital elevation model,surface gradient,road network
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要点】:本研究使用基于GIS的马尔可夫链和海平面淹没预测北卡罗来纳州新汉诺威县的陆地覆盖变化,预测了2030年和2050年该地区的土地覆盖分布,为沿海地区快速发展的城市区域提供了一种实用、快速且成本低廉的预测方法,并确定了未来海平面上升淹没的风险区域。

方法】:本研究采用土地变化模型器,通过20年的土地覆盖变化数据,预测了2030年和2050年的土地覆盖分布。

实验】:研究使用新汉诺威县2000年至2020年的土地利用数据集,通过土地变化模型器预测未来20年的土地覆盖变化,发现2030年和2050年该地区将有额外的土地开发,主要集中在县中心和屏障岛屿上。同时,模拟海平面上升显示,沿卡佩菲尔河的新汉诺威县西北部以及位于屏障岛屿上的海滩城镇将是最受影响的地区。在极端海平面上升情景下,威尔明顿市附近的I-140和卡罗来纳海滩附近的US-421等重要高速公路可能会被淹没,导致居民在紧急情况下的强制疏散延迟,交通拥堵可能会阻碍一些居民在紧急情况前到达安全地带。