基于Landsat 8 Oli的印尼巴厘省巴东县和登巴萨市红树林分布空间分析

P. Wiguna, Ni Wayan Ayu Sutari, Erik Febriarta, A. L. Permatasari, I. Suherningtyas, N. A. Pulungan, Tri Tanami Sukraini, Mutiara Gani
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引用次数: 3

摘要

巴厘岛是印度尼西亚群岛中的一个岛屿,拥有种植红树林的巨大潜力。利用遥感技术的进步,卫星图像,例如陆地卫星图像,可以用来分析红树林的分布和密度。本文对巴厘巴东县和登巴萨市红树林的分布进行了分析,为红树林生态系统的管理和保护提供依据。本研究利用Landsat 8 OLI图像和植被指数分析了该地区红树林的分布和密度。它首先使用RGB 564波段识别红树林,然后使用无监督分类继续区分红树林和非红树林目标,然后使用NDVI公式分析红树林密度。结果表明,2020年红树林面积为1269.20 ha,准确率为83%。红树林被发现在贝诺阿湾地区最深或最弯曲的海岸线上,在封闭的水域上。这种分布遵循下游的河网,沉积物较厚,不受大水流和波浪的影响。植被指数分析结果显示,红树林观测面积以中等密度为主,总面积为510.85 ha(40%),其次为高密度(413.15 ha/ 33%)和低密度(340.51 ha/ 27%)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial Analysis of Mangrove Distribution Using Landsat 8 Oli in Badung Regency and Denpasar City, Bali Province, Indonesia
Bali is an island situated among the Indonesian archipelago with huge potential to host mangrove forests. Using remote sensing technology advances, satellite images, such as Landsat images, might be employed to analyse mangrove forest distribution and density. This paper presents an analysis of mangrove distribution in Badung Regency and Denpasar City, Bali, as a basis for the management and conservation of mangrove ecosystems. This study used Landsat 8 OLI images and a vegetation index to analyse the mangrove forest distribution and density in this area. It started by identifying mangrove forests using the RGB 564 band and continued to distinguish between mangrove and non-mangrove objects using unsupervised classification, before analysing mangrove density using the NDVI formula. The results show that the mangrove forest area in 2020 was 1,269.20 ha, with an accuracy rate of 83%. Mangroves were found on the deepest or most curved coastline of the Benoa Bay area, on enclosed waters. This distribution follows the river network in the lower reach, which has thick deposits and is uninfluenced by large currents and waves. Based on the vegetation index analysis results, the mangrove forest area observed mainly had a moderate density, with a total area of 510.85 ha (40%), followed by high density (413.15 ha/ 33%) and low density (340.51 ha/ 27%).
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CiteScore
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