Estimación basada en Landsat 8 de sólidos suspendidos totales (1.3- 43 mg/L) usando los índices NDWI, MNDWI y AWEI en el Humedal Ramsar de Tecocomulco, México

This study integrates Landsat 8 multispectral imagery and three water segmentation indices (NDWI, MNDWI, AWEI) to estimate Total Suspended Solids (TSS) concentrations in Tecocomulco Lagoon, a Ramsar wetland in Hidalgo, Mexico. Using Google Earth Engine for image acquisition and Python-based processing with Rasterio and NumPy libraries, we applied the TSS algorithm: TSS = (RED/NIR) × F, where F=10 was calibrated against in-situ measurements. Eight spectral bands were processed from cloud-free images (<50% coverage) captured between January-December 2023. Results showed TSS concentrations ranging from 1.3 to 43 mg/L, with strong correlation (r=0.89, p<0.05) against CONAGUA reference data from three monitoring sites. Statistical validation yielded RMSE=4.2 mg/L, MAE=3.5 mg/L, and R2=0.79. The combined use of three indices improved water body segmentation accuracy compared to single-index approaches. This methodology provides cost-effective monitoring for the 1,769-ha wetland, supporting conservation efforts for 15 duck species and the endangered Ambystoma mexicanum. The approach offers a replicable framework for TSS monitoring in similar high-sedimentation wetlands.

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Magazine Portal Bibliotech Digital (Universidad Nacional de Colombia)
Published
2026-01-28
Primary Topic
Remote Sensing in Agriculture
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article
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article

Estimación basada en Landsat 8 de sólidos suspendidos totales (1.3- 43 mg/L) usando los índices NDWI, MNDWI y AWEI en el Humedal Ramsar de Tecocomulco, México

René Cruz Guerrero, German Cuaya-Simbro, Ismael Ortega-García
Magazine Portal Bibliotech Digital (Universidad Nacional de Colombia)
Remote Sensing in Agriculture
article

Estimación basada en Landsat 8 de sólidos suspendidos totales (1.3- 43 mg/L) usando los índices NDWI, MNDWI y AWEI en el Humedal Ramsar de Tecocomulco, México

René Cruz Guerrero, German Cuaya-Simbro, Ismael Ortega-García
article en

Abstract

This study integrates Landsat 8 multispectral imagery and three water segmentation indices (NDWI, MNDWI, AWEI) to estimate Total Suspended Solids (TSS) concentrations in Tecocomulco Lagoon, a Ramsar wetland in Hidalgo, Mexico. Using Google Earth Engine for image acquisition and Python-based processing with Rasterio and NumPy libraries, we applied the TSS algorithm: TSS = (RED/NIR) × F, where F=10 was calibrated against in-situ measurements. Eight spectral bands were processed from cloud-free images (<50% coverage) captured between January-December 2023. Results showed TSS concentrations ranging from 1.3 to 43 mg/L, with strong correlation (r=0.89, p<0.05) against CONAGUA reference data from three monitoring sites. Statistical validation yielded RMSE=4.2 mg/L, MAE=3.5 mg/L, and R2=0.79. The combined use of three indices improved water body segmentation accuracy compared to single-index approaches. This methodology provides cost-effective monitoring for the 1,769-ha wetland, supporting conservation efforts for 15 duck species and the endangered Ambystoma mexicanum. The approach offers a replicable framework for TSS monitoring in similar high-sedimentation wetlands.

Magazine Portal Bibliotech Digital (Universidad Nacional de Colombia)
Instituto Tecnológico Superior de Xalapa (MX)
Life in Land
Openalex Percentile: Top 72%
Remote Sensing in Agriculture
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