Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/36238
Appears in Collections:Biological and Environmental Sciences Journal Articles
Peer Review Status: Refereed
Title: Exploring Global Remote Sensing Products for Water Quality Assessment: Lake Nicaragua case study
Author(s): Baltodano, Analy
Agramont, Afnan
Lekarkar, Katoria
Spyrakos, Evangelos
Reusen, Ils
van Griensven, Ann
Contact Email: evangelos.spyrakos@stir.ac.uk
Keywords: Remote sensing
Water quality
Lake Nicaragua
Chlorophyll-a
Issue Date: Nov-2024
Date Deposited: 27-Sep-2024
Citation: Baltodano A, Agramont A, Lekarkar K, Spyrakos E, Reusen I & van Griensven A (2024) Exploring Global Remote Sensing Products for Water Quality Assessment: Lake Nicaragua case study. <i>Remote Sensing Applications: Society and Environment</i>, 36, Art. No.: 101331. https://doi.org/10.1016/j.rsase.2024.101331
Abstract: 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.
DOI Link: 10.1016/j.rsase.2024.101331
Rights: This article is available under the Creative Commons CC-BY-NC license and permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
Licence URL(s): http://creativecommons.org/licenses/by-nc/4.0/

Files in This Item:
File Description SizeFormat 
1-s2.0-S2352938524001952-main.pdfFulltext - Published Version6.87 MBAdobe PDFView/Open



This item is protected by original copyright



A file in this item is licensed under a Creative Commons License Creative Commons

Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved https://creativecommons.org/publicdomain/zero/1.0/

If you believe that any material held in STORRE infringes copyright, please contact library@stir.ac.uk providing details and we will remove the Work from public display in STORRE and investigate your claim.