Cloud Processing for Simultaneous Mapping of Seagrass Meadows in Optically Complex and Varied Water

Abstract

Improved development of remote sensing approaches to deliver timely and accurate measurements for environmental monitoring, particularly with respect to marine and estuarine environments is a priority. We describe a machine learning, cloud processing protocol for simultaneous mapping seagrass meadows in waters of variable quality across Moreton Bay, Australia. This method was adapted from a protocol developed for mapping coral reef areas. Georeferenced spot check field-survey data were obtained across Moreton Bay, covering areas of differing water quality, and categorized into either substrate or ≥25% seagrass cover. These point data with coincident Landsat 8 OLI satellite imagery (30 m resolution; pulled directly from Google Earth Engine’s public archive) and a bathymetric layer (30 m resolution) were incorporated to train a random forest classifier. The semiautomated machine learning algorithm was applied to map seagrass in shallow areas of variable water quality simultaneously, and a bay-wide map was created for Moreton Bay. The output benthic habitat map representing seagrass presence/absence was accurate (63%) as determined by validation with an independent data set.

Mapping the National Seagrass Extent in Seychelles Using PlanetScope NICFI Data

“…Reference data were pooled across fieldwork and included snorkel and diving transect surveys, sediment coring sites, historical field observations, and an expert knowledge annotated dataset. While the dataset was collected for a range of purposes, it was the best available dataset and thus was used for the mapping of seagrass and other benthic classes [49]. Our study built on previous mapping efforts in the region to define a shallow (0-10 m) and deep subclass (>10 m to maximum optical depth), using the benthic classes of the Allen Coral Atlas [50] as a spatial filter for the aforementioned depth subclasses [50,51].…”

“…Following, the land was masked using a Normalised Difference Water Index (NDWI) adapted from Landsat 8 [54] and proven useful in Sentinel-2 Surface Reflectance Products [53]. Deep water masking was performed using an adapted true colour HSV approach owing to the band limitations of PlanetScope [55], as well as manual masking for the pixels that were easily confused [41,49]. Owing to the limited number of spectral bands and the use of variable importance downstream to retain only the most useful features, the N band was retained for the downstream feature generation phase rather than removed by standard atmospheric correction.…”

“…Despite its potential, the NICFI basemaps face challenges with their four-band spectral resolution. Furthermore, the lack of reference data designed for remote sensing research would introduce more uncertainties in the results [49]. In conjunction, it would naturally stress the image processing, which again leads to more uncertainties.…”

“…It is costly to organise field surveys in less accessible places, and even citizen science is susceptible to spatio-temporal clustering bias related to accessibility or popularity [66]. To illustrate, the low availability of deeper seagrass spatial data came from a reuse of data designed for other purposes, such as coring at deeper depths [49]. Processing the reference data to fit remote sensing research introduces its own uncertainties, even as it alleviates other issues, such as anomalous values or comparability between different classes [21].…”

Mangrove ghost forests provide opportunities for seagrass

“…Mangrove ghost forests were identified through a combination of past studies (Duke et al, 2010;Baltais, 2014), and inspection of satellite images where areas of defoliated mangroves can clearly be identified (Google Earth Pro 7.3.6.9345, 2023) followed by ground-truthing at each site. Adjacent live mangroves and seagrass sites were selected using local maps [for mangroves using Accad et al (2016)] and seagrass using maps of Kovacs et al (2022). Maps of global seagrass (Short, 2021) were used for the area around South Stradbroke Island where there is no local mapping.…”