Browsing by Autor "Analy Baltodano"

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Exploring global remote sensing products for water quality assessment: Lake Nicaragua case study
(Elsevier BV, 2024) Analy Baltodano; Afnan Agramont; Katoria Lesaalon Lekarkar; Evangelos Spyrakos; I. Reusen; Ann van Griensven
This study explores the applicability of 13 globally-derived Chlorophyll-a (CHL) products from optical satellite remote sensing to support local water quality management in Lake Nicaragua. The temporal and spatial consistency between the products was analyzed, as well as their agreement with in-situ data collected from 2011 to 2016. The Climate Change Initiative (CCI) CHL product was identified as the most stable and reliable, suggesting its suitability for monitoring Lake Nicaragua. However, the correlation of this product with in-situ measurements was weak, attributed to the sparse and inconsistent nature of the available in-situ water quality data. The hotspots analysis identified critical areas around urban and agricultural zones with high CHL concentrations, providing valuable insights for targeted management interventions. This study emphasizes the need for improved global to local remote sensing strategies, including the selection of the appropriate algorithms for the region, continuous calibration and validation with in-situ data, and the development of a robust, publicly accessible local water quality database that includes both in-situ and remote sensing data, to support effective monitoring for local water management.
Exploring Trends and Variability of Water Quality over Lake Titicaca Using Global Remote Sensing Products
(Multidisciplinary Digital Publishing Institute, 2024) Vann Harvey Maligaya; Analy Baltodano; Afnan Agramont; Ann van Griensven
Understanding the current water quality dynamics is necessary to ensure that ecological and sociocultural services are provided to the population and the natural environment. Water quality monitoring of lakes is usually performed with in situ measurements; however, these are costly, time consuming, laborious, and can have limited spatial coverage. Nowadays, remote sensing offers an alternative source of data to be used in water quality monitoring; by applying appropriate algorithms to satellite imagery, it is possible to retrieve water quality parameters. The use of global remote sensing water quality products increased in the last decade, and there are a multitude of products available from various databases. However, in Latin America, studies on the inter-comparison of the applicability of these products for water quality monitoring is rather scarce. Therefore, in this study, global remote sensing products estimating various water quality parameters were explored on Lake Titicaca and compared with each other and sources of data. Two products, the Copernicus Global Land Service (CGLS) and the European Space Agency Lakes Climate Change Initiative (ESA-CCI), were evaluated through a comparison with in situ measurements and with each other for analysis of the spatiotemporal variability of lake surface water temperature (LSWT), turbidity, and chlorophyll-a. The results of this study showed that the two products had limited accuracy when compared to in situ data; however, remarkable performance was observed in terms of exhibiting spatiotemporal variability of the WQ parameters. The ESA-CCI LSWT product performed better than the CGLS product in estimating LSWT, while the two products were on par with each other in terms of demonstrating the spatiotemporal patterns of the WQ parameters. Overall, these two global remote sensing water quality products can be used to monitor Lake Titicaca, currently with limited accuracy, but they can be improved with precise pixel identification, accurate optical water type definition, and better algorithms for atmospheric correction and retrieval. This highlights the need for the improvement of global WQ products to fit local conditions and make the products more useful for decision-making at the appropriate scale.
Indigenous community-based approaches to environmental justice through citizen science
(Springer Science+Business Media, 2026) Afnan Agramont; Analy Baltodano; Mohammad Gharesifard; Leonardo Villafuerte Philippsborn; Liliana Lizarazo‐Rodríguez; Stuart Warner; Ann van Griensven
Land Cover Change and Water Quality: How Remote Sensing Can Help Understand Driver–Impact Relations in the Lake Titicaca Basin
(Multidisciplinary Digital Publishing Institute, 2022) Analy Baltodano; Afnan Agramont; I. Reusen; Ann van Griensven
The increase of human interventions and developments are modifying the land use/land cover (LULC) of the global landscape, thus severely affecting the water quality of rivers and lakes. Appropriate management and effective policy developments are required to deal with the problems of surface water contamination around the globe. However, spatiotemporal variations of water quality and its complex relation with land cover (LC) changes, challenge adequate water resources management. In this study, we explored the use of remote sensing to relate LC change in the Katari River Basin (KRB) located in the Bolivian Andes and water quality on the shores of Lake Titicaca, in order to support water management. An unsupervised classification of Landsat 7 satellite images and trajectory analysis was applied to understand the modifications of LC through time. In addition, water-quality indicators at the outlet of the basin were retrieved from remote-sensing images and its temporal behavior was analyzed. The results show that the expansion of urban areas is the predominant environmental driver in the KRB, which has great impact on the water quality of Lake Titicaca. We conclude that there is a strong link between the rapid growth of urban and industrial areas with the detriment of river and lake water quality. This case study shows how remote sensing can help understand driver–impact relations.