We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
ImaMPs: Extensive image dataset of microplastics in freshwater from tourist areas in the State of Mexico, Mexico.
Summary
Researchers compiled an extensive image dataset of microplastics collected from freshwater bodies in tourist areas of the State of Mexico, providing a visual reference resource to support automated identification and classification of microplastic particles in Mexican aquatic ecosystems.
ImaMPs: Extensive image dataset of microplastics in freshwater from tourist areas in the State of Mexico, Mexico. In Mexico, tourism represents one of the main economic and cultural activities, with more than 177 Pueblos Mágicos [1] and various natural areas recognized as tourist destinations. However, these areas, mainly water bodies, face environmental issues related to microplastic pollution, particles of synthetic polymers ranging from 5 mm to 1 μm in size, which enter aquatic ecosystems and affect both biota and fishing and tourism activities. To contribute to the identification and classification of microplastics in water bodies, the creation of a dataset called Images of Microplastics (ImaMPs) is presented, consisting of 6,000 images in TIFF format. These images were generated from water samples collected in situ at three tourist sites in the State of Mexico, Mexico: the “Miguel Alemán” dam, in the municipality of Valle de Bravo; the Chalma Sanctuary, in the municipality of Ocuilan; and the “Las Ciénegas de Lerma” wetlands, in the municipality of Lerma. The water samples underwent a filtration process using cellulose membranes, which were analyzed with a stereoscopic optical microscope (Velab VE-S5C [2]), adjusting the RGB bands and zoom variation (0.7x–4.5x) to improve image quality and facilitate analysis. The cellulose membranes used in the filtration process have the following characteristics: Diameter: 0.47 mm Grid: 170–225 squares Pore size: 0.22 μm Color: white The dataset is organized into two classes: 3,000 images with microplastics (MP), located in the CLASE_1 folder, and 3,000 without microplastics (NMP), located in the CLASE_0 folder. All images are identified by a consecutive number and have resolutions of 2040x1528 and 1016x760 pixels, with a distribution of 4,262 images in the first resolution and 1,738 in the second. In addition to the image set, a comma-separated values file (DATA_ImaMPs.cvs) is included with the following information: ID of each image. File name. Place where the sample was taken. Date of capture of the sample. Label (with or without microplastics). Image size. The ImaMPs database constitutes an innovative and scientifically relevant resource by offering a standardized and accessible set for the identification and classification of microplastics in images. Its potential applications range from environmental research to the use of machine learning techniques and optical analysis, contributing to the understanding of synthetic polymer pollution and the development of technological strategies aimed at mitigating its impacts on ecosystems and tourism economies. Reference [1] Núñez Camarena, G. M. (2016, May). Los pueblos mágicos de México: mecanismo de la SECTUR para poner en valor el territorio. In VIII Seminario Internacional de Investigación en Urbanismo, Barcelona-Balneário Camboriú, Junio 2016. Departament d’Urbanisme i Ordenació del Territori. Universitat Politècnica de Catalunya. [2] Tinoco, V. B., Moreno, F. M., & Moreno, S. M. (2023). Comportamiento y desarrollo del sector turístico en México. Ciencia Latina Revista Científica Multidisciplinar, 7(2), 8988-9003.
Sign in to start a discussion.
More Papers Like This
ImaMPs: Extensive image dataset of microplastics in freshwater from tourist areas in the State of Mexico, Mexico.
Researchers compiled an extensive image dataset of microplastics collected from freshwater bodies in tourist areas of the State of Mexico, providing a visual reference resource to support automated identification and classification of microplastic particles in Mexican aquatic ecosystems.
Spatiotemporal assessment of microplastic incidence in the Atoyac basin — a key watershed in Mexico
This spatiotemporal study quantified and characterized microplastics in freshwater and sediments across the Atoyac sub-basin in Mexico, documenting MP types, shapes, and sizes at sites impacted by urban, agricultural, and industrial activity over multiple sampling periods.
Morphological Detection and Classification of Microplastics and Nanoplastics Emerged from Consumer Products by Deep Learning
Researchers created a new open-source dataset of microscopy images for training AI models to automatically detect and classify micro- and nanoplastics. The dataset fills an important gap in available tools for microplastic research and provides a foundation for developing faster, more efficient methods to identify plastic contamination across environmental samples.
Deep Learning-Based Image Recognition System for Automated Microplastic Detection and Water Pollution Monitoring
This study developed a deep learning image recognition system to automate the detection and classification of microplastics from microscopy images of water samples. The system achieved high accuracy across particle types and sizes, offering a scalable and less labor-intensive alternative to manual microscopy for large-scale water pollution monitoring.
Identification of Microplastics in Aquatic Environments Using Oxidative Treatment and Automated Image Analysis
Researchers developed a cost-effective and replicable method for detecting microplastics in freshwater environments using oxidative treatment to digest organic matter from water samples, enabling cleaner isolation and more accurate identification of MP particles without requiring expensive instrumentation.