Remote sensing monitoring of mangrove growth AUTHORS: rate at selected planted sites in Mauritius

Abstract

Mangroves are highly productive and rich ecosystems that thrive at the interface of land and sea. They provide a wide range of essential goods and services, contribute highly to coastal protection and the livelihood of coastal communities, and are also carbon-rich biomes contributing to carbon sequestration. Mangroves are primarily threatened by anthropogenic activities; a loss in biodiversity has been observed in the past years in many countries including Mauritius. Given their value to the ecosystem, it is important to have effective continuous monitoring of mangrove dynamics. We studied the rate of increase of canopy coverage of planted Rhizophora mucronata forests in two selected sites (Le Morne and Grande Rivière Noire) on a southern African island – Mauritius – using Google Earth Pro historical Landsat 7 and Landsat 8 images. Data were processed using ImageJ software. To our knowledge, this technique has not yet been applied for monitoring mangrove growth. The mangrove sites were classified into four zones based on water level and tidal variations. On average, the rate of increase of canopy coverage expressed by a coefficient ‘b’ at Le Morne (b = 1.901) was higher than that at Grande Rivière Noire (b = 1.823). The coefficient ‘b’ positively correlated with the zonations (r ~ 0.8). Higher ‘b’ values (2.319–2.886) were observed in Zone 1, where the substrate is always covered with water at low tide. The use of remote sensing data along with image processing analysis proved to be an effective tool to obtain relevant information, not only for mapping mangroves but also for monitoring the canopy growth rates of planted mangroves.

Significance:
• We describe a novel technique whereby remote sensing data are processed through image processing using ImageJ software, to effectively monitor planted mangrove canopy growth by pixel count.
• This study highlights the successful application of the technique to obtain relevant information for
mapping and monitoring the canopy growth rates of planted mangroves.
• This technique can be further extended to identify potential areas for mangrove propagation worldwide based on tidal level variations.