A. Darmawan, N. Setyaningrum, Afifuddin, S. Arfah, Muhammad Iqbal Habibie
{"title":"Is the Mangrove Restoration and Rehabilitation Program Successful in Riau Province, Indonesia?","authors":"A. Darmawan, N. Setyaningrum, Afifuddin, S. Arfah, Muhammad Iqbal Habibie","doi":"10.1109/AGERS56232.2022.10093595","DOIUrl":null,"url":null,"abstract":"Mangroves not only function as carbon sinks but also as food sources, wildlife habitats, and coastal protection. However, behind the enormous benefits, the information and data are still relatively minimal. In the context of the mangrove restoration and rehabilitation program in Indonesia, it is necessary to study the progress that has been achieved so far. One of the indicators assessed is the estimation of mangrove density in an area over a certain period. This study will calculate the density of mangroves in Riau Province, one of 9 priority provinces, using Sentinel 2 satellite data for 2016 and 2021. Estimation of mangrove density is carried out using vegetation indices approach, namely Modified Soil-Adjusted Vegetation Index-2 (MSAVI2), Soil-Adjusted Vegetation Index 2 (SAVI2), and Green Normalized Difference Vegetation Index-2 (GNDVI2). This vegetation index is an empirical mathematical model algorithm of the reflection of electromagnetic, visible, and near-infrared (NIR) waves. From the results of this study, the mangrove restoration and rehabilitation program in Riau Province is going as expected, and it can be seen from the change in the density level. The algorithm shows that the change in mangrove density in 2021 is about 20% for the very dense type compared to 2016.","PeriodicalId":370213,"journal":{"name":"2022 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AGERS56232.2022.10093595","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Mangroves not only function as carbon sinks but also as food sources, wildlife habitats, and coastal protection. However, behind the enormous benefits, the information and data are still relatively minimal. In the context of the mangrove restoration and rehabilitation program in Indonesia, it is necessary to study the progress that has been achieved so far. One of the indicators assessed is the estimation of mangrove density in an area over a certain period. This study will calculate the density of mangroves in Riau Province, one of 9 priority provinces, using Sentinel 2 satellite data for 2016 and 2021. Estimation of mangrove density is carried out using vegetation indices approach, namely Modified Soil-Adjusted Vegetation Index-2 (MSAVI2), Soil-Adjusted Vegetation Index 2 (SAVI2), and Green Normalized Difference Vegetation Index-2 (GNDVI2). This vegetation index is an empirical mathematical model algorithm of the reflection of electromagnetic, visible, and near-infrared (NIR) waves. From the results of this study, the mangrove restoration and rehabilitation program in Riau Province is going as expected, and it can be seen from the change in the density level. The algorithm shows that the change in mangrove density in 2021 is about 20% for the very dense type compared to 2016.