Comparing image-based classification and field sampling methods for beach litter quantification in Can Gio, Southern...

Area of Science:

• Environmental Science
• Marine Biology
• Conservation Science

Background:

• Coastal areas like Can Gio District face significant marine plastic pollution.
• Effective monitoring is crucial for managing this growing environmental threat.

Purpose of the Study:

• To compare the efficacy of smartphone-based image analysis versus traditional field surveys for monitoring beach litter.
• To evaluate Mergin Maps as a rapid, low-cost tool for marine litter assessment.

Main Methods:

• Utilized Mergin Maps app for georeferenced quadrat image capture via smartphone.
• Compared image analysis results with in situ manual collection across four sandy beaches.
• Analyzed litter densities, item types (predominantly plastics), and detection accuracy.

Main Results:

• Both methods recorded high litter densities (>10 items m⁻²), with plastics comprising over 96%.
• Image-based analysis showed a high error percentage (mean 43.15%) mainly due to buried or obscured items.
• Despite errors, statistical analysis found no significant difference in litter counts between methods (p > 0.05).

Conclusions:

• Mergin Maps provides a statistically equivalent and significantly faster alternative to conventional quadrat sampling for marine litter monitoring.
• This smartphone-based GIS platform is a feasible solution for resource-limited coastal settings.