Development of a Rapid Mangrove Zonation Mapping Workflow Using Sentinel 2-Derived Indices and Biophysical Dataset

Abstract

Moderate to high resolution satellite imageries are commonly used in mapping mangrove cover from local to global scales. In addition to extent information, studies such as mangrove composition, ecology, and distribution analysis require further information on mangrove zonation. Mangrove zonation refers to unique sections within a mangrove forest being dominated by a similar family, genus, or species. This can be observed both in natural and planted mangrove forests. In this study, a mapping workflow was developed to detect zonation in test mangrove forest sites in Katunggan-It Ibajay (KII) Ecopark (Aklan), Bintuan (Coron), Bogtong, and Sagrada (Busuanga) in the Philippines and Fukido Mangrove Park (Ishigaki, Japan) using Sentinel-2 imagery. The methodology was then applied to generate a nationwide mangrove zonation map of the Philippines for year 2020. Combination of biophysical products, water, and vegetation indices were used as classification inputs including leaf area index (LAI), fractional vegetation cover (FVC), fraction of photosynthetically-active radiation (FAPAR), Canopy chlorophyll content (Cab), canopy water content (Cw), Normalized Difference Vegetation Index (NDVI), modified normalized difference water index (MNDWI), modified chlorophyll absorption in reflectance index (MCARI), and red-edge inflection point (REIP). Mangrove extents were first mapped using either the Maximum Likelihood Classification (MLC) algorithm or the Mangrove Vegetation Index (MVI)-based methodology. The biophysical and vegetation indices within these areas were stacked and transformed through Principal Component Analysis (PCA). Regions of Interest (ROIs) were selected on the PCA bands as training input to the MLC. Results show that mangrove zonation maps can highlight the major mangrove zones in the study sites, commonly limited up to genera level only except for genera with only one known species thriving in the area. Four zones were detected in KII Ecopark: Avicennia zone, Nypa zone, Avicennia mixed with Nypa zone, and mixed mangroves zones. For Coron and Busuanga, the mapped mangrove zones are mixed mangroves, Rhizophora zone and sparse/damaged zones. Three zones were detected in Fukido site: Rhizophora stylosa-dominant zone, Bruguiera gymnorrhiza-dominant zone, and mixed mangrove zones. The zonation maps were validated using field plot data and orthophotos generated from Unmanned Aerial System (UAS) surveys, with accuracies ranging from 75 to 100%.

Mangrove distribution to support biodiversity management in Teluk Bintuni District, West Papua, Indonesia

“…Species belonging to Acanthaceae and Lythraceae were found abundantly in the sea fringing zone. Genera from these families, such as Avicennia and Sonneratia, were more diverse and dominant in the sea fringing zone as other studies also mentioned the same result (Liu et al 2018;Nasrin et al 2020;Baloloy et al 2021). The areas are characterized as having high saline levels and exposed to waves.…”

“…We applied elevation as an independent variable to explain its relationship with the distribution of mangroves (Matthijs et al 1999;Fu et al 2018;Baloloy et al 2021). We found that the distribution of some mangrove families is likely affected by altitude which grows dominantly either in the sea fringing zone or the landward zone, while other families grow randomly in terms of elevation.…”

Changes in DIC/TA ratio by tidal asymmetry control <i>p</i>CO₂ over a spring-neap tidal cycle in a subtropical mangrove forest in Japan

“…Of these, the outwelling of DIC to the ocean is considered the most important (Maher et al, 2018;Reithmaier et al, 2023). The area of mangroves in the Fukido River estuary was estimated to be 20.04 ha (Baloloy et al, 2021). By combining the reported values of each flux with the results of this study, we investigated the fate of sequestered carbon in the Fukido River mangrove forest.…”

“…Rainfall is relatively abundant during the rainy season from May to June, and during the typhoon season from August to September (approximately 43% of the annual rainfall). A mangrove forest is dominated by Bruguiera gymnorrhiza and Rhizophora stylosa and is distributed over approximately 20.04 ha (Baloloy et al, 2021). The mangrove forest is considered mature; the maximum tree heights of B.gymnorrhiza and R.stylosa are 13.2 m and 11.6 m, respectively (Ohtsuka et al, 2019).…”

Spatio-Temporal Mapping and Monitoring of Mangrove Forests Changes from 1991 to 2021 in Panay Island, Philippines using Machine Learning

“…Despite data on mangrove extent in some areas of Panay Island, there's a critical deficiency in updated and accurate information on large-scale mangrove cover change over time [5]. To address this urgent need to understand the status of mangroves and the drivers of their forest loss and gain, rapid and accurate extent mapping must be done [6]. By harnessing the power of satellite technology as well as artificial intelligence, these ecosystems can be managed more effectively.…”