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Temporal Assessment of Mangrove Restoration Success Using NDVI from Remote Sensing Data (2021-2023)
Luisa Febrina Amalo (a*), Tarisa Fadilah (a), Novia Ramadhani (b), and Luluk Dwi Wulan Handayani (a)

a) Center for Environmental Research, IPB University, Indonesia
b) Conservation of Forest Resources and Ecotourism Study Program, Faculty of Forestry and Environment, IPB University, Indonesia
*luisafebrina[at]gmail.com


Abstract

Remote sensing technologies enable successful mangrove restoration monitoring because they allow the tracking of vegetation changes across large areas at affordable costs with reliable results. The Normalized Difference Vegetation Index (NDVI) serves as a reliable remote sensing index that monitors vegetation health and density, as well as ecosystem recovery. The study aims to examine the changes in NDVI values at a mangrove restoration area over three years, from 2021 to 2023, as the plants developed from seedlings into saplings. The study results demonstrated that NDVI values increased throughout the research duration, indicating successful vegetation growth and restoration. The early growth phase of 2021 showed NDVI readings between 0.077 and 0.258, which indicated that sparse vegetation was beginning to develop its canopy. The 2022 sapling stage began with NDVI values ranging from 0.134 to 0.567, indicating the onset of plant structure development and increasing vegetation density. The NDVI values in 2023 for the advanced sapling stage increased substantially from 0.261 to 0.868, indicating the formation of dense and fully developed mangrove vegetation. The research demonstrates that NDVI serves as a quantitative tool, enabling scientists to measure the progress of mangrove restoration efforts and track their growth patterns. Remote sensing technology becomes vital for maintaining long-term mangrove ecosystem monitoring systems because NDVI values increase from year to year, indicating successful ecological growth.

Keywords: Mangrove restoration- NDVI- Remote sensing- Vegetation index-

Topic: Topic B: Applications of Remote Sensing

Plain Format | Corresponding Author (Luisa Febrina Amalo)

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