Monitoreo de la calidad del agua del lago Chinchaycocha, mediante técnicas de teledetección espacial.

Christian Ayala Jesús; Marco Antonio Herrera Díaz

doi:10.46380/rias.v2i2.46

Authors

Christian Ayala Jesús Esterd Consultores S.A.C., Peru
Marco Antonio Herrera Díaz Esterd Consultores S.A.C., Peru

DOI:

https://doi.org/10.46380/rias.v2i2.46

Keywords:

lake, operational land imager, reflectivity, trophic state

Abstract

The remote sensing technique or remote perception can be used to estimate the water quality variables, such as chlorophyll, total suspended matter and water clearness. This article presents empiric algorithms for its estimation which use the Operational Land Imager (OLI) sensor data from the satellite Landsat 8/LCDM. The data were taken from the Chinchaycocha lake, because it has nutritive substances that improve the algae production and other aquatic plants that deteriorate the water quality. We obtain empiric equations to estimate chlorophyll on the relation of reflectivity values with the Chavez method, between 3 and 5 OLI sensor bands; the transparency through the disco de secchi, the influence on the 3 and 4 bands; and the total suspended matter influence on band 5; shows as a result, maps of Chinchaycocha lake were the values of this parameters can be seen. This investigation supports the techniques used.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

References

Ariza, A. (2013). Descripción y Corrección de Productos Landsat 8 LDCM (Landsat Data Continuity Misssion). Instituto Geográfico Agustín Codazzi. https://cutt.ly/JyPRoFF

Brizuela, A., Aguirre, C. y Velasco, I. (2007). Aplicación de métodos de corrección atmosférica de datos Landsat 5 para seguir análisis multitemporal. CONICET.

Domínguez, J.A., Chuvieco, E. y Sastre, A. (2009). Monitoring transparency in inland water bodies using multispectral images. International Journal of Remote Sensing, 30(6), 1567–1586. https://doi.org/10.1080/01431160802513811

Doña, C., Sanchez, J., Caselles, V., Domínguez, J. y Camacho A. (2014). Empirical Relationships for Monitoring Water Quality of Lakes and Reservoirs Through Multispectral Images. IEEE Journal of selected topics in applied earth observation and remote sensing, 7(5), 1632-1641. https://ieeexplore.ieee.org/document/6730928

Duan, H., Zhang, Y., Zhang, B., Song, K. y Wang, Z. (2006). Assessment of Chlorophyll-a concentration and trophic state for Lake Chagan using Landsat TM and ?eld spectral data. Environ Monit Assess, 129(1-3), 295?308. https://doi.org/10.1007/s10661-006-9362-y

Lim, J. y Choi, C. (2015). Assement of water quality based on Landsat 8 operational land imager associated with human activities in Korea. Environ Monit Assess, 187(6), 384. https://doi.org/10.1007/s10661-015-4616-1

López-García, M. J. y Caselles, V. (1987). Use of Thematic Mapper data to assess water quality in Albufera lagoon of Valencia (Spain). Proc.13th Ann. Conf. of Remote Sensing Society. Nottingham, 510-519. https://cutt.ly/pyPRVqT

Moncayo, R., y Bueno M. (2016). Evaluación Espacio-Temporal del estado trófico de un lago de grandes dimensiones usando imágenes MOD09GA. Revista Ciencia e Ingeniería Neogranadina, 7(1), 27-42. https://doi.org/10.18359/rcin.1893

Organización para la Cooperación y el Desarrollo Económicos. (1982). Eutrophisation des Eaux. Methodes de surveillance, d´evaluation et de lute.

Servicio Nacional de Áreas Naturales Protegidas por el Estado. (2015). Humedales en Áreas Naturales Protegidas, fuentes de vida y desarrollo. Ministerio del Ambiente del Perú. https://cutt.ly/JyPR5Ct