Implementasi Hyper Spectral of Remote Sensing untuk Analisis Kawasan Ekowisata Mangrove Potensial di Kecamatan Tobelo Timur Menggunakan NDVI, SAVI, dan EVI

Yerik Afrianto Singgalen
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引用次数: 1

Abstract

Studies on the resilience of mangrove forest areas are becoming popular in Indonesia, despite the implementation of the Hyper Spectral of Remote Sensing method in identifying changes in vegetation index values based on the Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI) and Enhanced Vegetation Index models (EVI) in unreached areas need to be done to add to the database so that it becomes a reference for further research. Considering this, this study uses the hyperspectral method of remote sensing through the following stages: data collection; data processing; radiometric calibration; dimension reduction; data analysis; interpretation of results. Meanwhile, the bands used have been adjusted to NDVI, SAVI, and EVI models at the dimension reduction stage. The results of this study show that the overall average value of the calculation results of NDVI, SAVI, and EVI based on Zone 1, Zone 2, Zone 3, and Zone 4 of the mangrove area of East Tobelo District indicates the condition of medium or sufficient category density and dense or dense. Thus, it can be known that the location is feasible to be developed as a tourist attraction through a community-based mangrove ecotourism area development model.
印度尼西亚红树林恢复力的研究正在兴起,但需要在未到达地区实施基于归一化植被指数(NDVI)、土壤调整植被指数(SAVI)和增强植被指数模型(EVI)的高光谱遥感方法来识别植被指数值的变化,以增加数据库,使其成为进一步研究的参考。考虑到这一点,本研究采用遥感高光谱方法,通过以下几个阶段:数据收集;数据处理;辐射校准;降维;数据分析;对结果的解释。同时,在降维阶段,将使用的波段调整为NDVI、SAVI和EVI模型。本研究结果表明,东托贝洛区红树林区1、2、3、4区的NDVI、SAVI和EVI计算结果的总体平均值表明,类别密度为中等或足够、密集或密集的状态。由此可知,通过以社区为基础的红树林生态旅游区开发模式,将该区位开发为旅游景点是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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