Monitoring the Land Cover Changes in Mangrove Areas and Urbanization using Normalized Difference Vegetation Index and Normalized Difference Built-up Index in Krabi Estuary Wetland, Krabi Province, Thailand

Q3 Environmental Science
K. Waiyasusri
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引用次数: 0

Abstract

Krabi Estuary Wetland (KEW) is an outstanding wetland with an estuary environment. At present, the tourism industry has rapidly grown, resulting in the impact of land cover changes. This research aims to assess the changes that have occurred in the KEW from 1999 to 2020 using NDVI and NDBI for monitoring changes in mangrove areas and urbanization in Krabi Province, Thailand. Landsat satellite images in years 1999, 2009 and 2020 were classified by using a band ratio to create land cover maps. The results show that NDVI between 0.41–1.00 clearly shows the mangrove forest area, while NDBI between 0.01–0.40 shows urban and built-up land, and 0.41–1.00 appears as bare land. The NDVI overall accuracy assessment is 82.88%, 97.46% and 88.25% with Kappa values of 0.64, 0.92, and 0.85 for year 1999, 2009 and 2020, respectively. The NDBI overall accuracy assessment is 92.81%, 77.11% and 64% with Kappa values of 0.93, 0.77, and 0.63 for year 1999, 2009 and 2020, respectively. In addition, areas that are sensitive to land-cover change appear around the Chi rat River, Pak Nam Krabi River, and Yuan River, which are tourist areas close to the Krabi and Ao Nang communities. Therefore, it is necessary to speed up the problem solving and find measures to prevent mangrove forest degradation in these 3 mangrove forest areas so that the mangrove forest areas will not decrease rapidly in the future. This research can be valuable for land-cover management in the KEW by policy and decision makers.
基于归一化植被指数和归一化建筑指数的泰国甲米河口湿地红树林土地覆盖变化与城市化
甲米河口湿地(KEW)是一个具有河口环境的优秀湿地。目前,旅游业迅速发展,导致土地覆盖变化的影响。本研究旨在利用NDVI和NDBI监测泰国甲米省红树林面积和城市化的变化,评估1999 - 2020年KEW的变化。1999年、2009年和2020年的陆地卫星图像使用波段比进行分类,以创建土地覆盖图。结果表明:NDVI在0.41 ~ 1.00之间清晰地表示红树林区域,NDBI在0.01 ~ 0.40之间清晰地表示城市和建设用地,而在0.41 ~ 1.00之间清晰地表示裸地。1999年、2009年和2020年NDVI总体准确度分别为82.88%、97.46%和88.25%,Kappa值分别为0.64、0.92和0.85。1999年、2009年和2020年NDBI的总体准确率分别为92.81%、77.11%和64%,Kappa值分别为0.93、0.77和0.63。此外,对土地覆盖变化敏感的地区出现在赤鼠河、北南甲米河和元河周围,这些地区是靠近甲米和奥南社区的旅游区。因此,有必要加快解决问题,并找到防止这3个红树林区域红树林退化的措施,使红树林面积在未来不会迅速减少。该研究对政策制定者和决策者进行土地覆盖管理具有一定的参考价值。
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来源期刊
Applied Environmental Research
Applied Environmental Research Environmental Science-Environmental Science (all)
CiteScore
2.00
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