Spatio-temporal monitoring of mangrove biodiversity using Landsat-8 imagery in Kendari Bay, Indonesia

¹ Department of Geophysics, Faculty of Mathematics and Natural Sciences, Hasanuddin University, Jalan Perintis Kemerdekaan 10, Makassar, Indonesia
² Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Papua, Jalan Gunung Salju, Manokwari, Indonesia
³ Department of Urban and Regional Planning, Faculty of Engineering, Hasanuddin University, Jalan Malino, Makassar, Indonesia
⁴ Department of Mathematics and Statistics, Faculty of Mathematics and Natural Sciences, Universitas Papua, Jalan Gunung Salju, Manokwari, Indonesia

^* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

Mangrove ecosystems are key biodiversity hotspots that provide critical habitats for various coastal species, enhance carbon sequestration, and contribute to the overall ecosystem resilience. However, these ecosystems are becoming increasingly vulnerable to anthropogenic pressures, leading to significant degradation. This study examined the spatio-temporal dynamics of mangrove ecosystems in Kendari Bay, Southeast Sulawesi, Indonesia, from 2020 to 2024, using multi-temporal Landsat-8 imagery. Normalized Difference Vegetation Index (NDVI) analysis was applied to assess vegetation health as a proxy for mangrove biodiversity and canopy vigor, and supervised classification was used to map land cover change. The results indicate a substantial increase in critically degraded mangrove areas, from 13.2% in 2020 to 31.7% in 2024. These changes signify a decline in habitat quality [and spatial fragmentation of biodiversity-rich zones] associated with mangrove ecosystems. These findings underscore the urgency of strengthening conservation measures, ecological zoning, and restoration efforts to maintain biodiversity and ensure sustainable coastal ecosystem services. The integration of NDVI, land-cover classification, and degradation mapping provides a reliable framework for monitoring mangrove biodiversity in rapidly urbanizing tropical coasts. Remote sensing analysis, as demonstrated in this study, offers valuable insights into monitoring mangrove health and supporting biodiversity conservation strategies.