Data-Driven Modelling of Freshwater Ecosystems: A Multiscale Framework Based on Global Geospatial Data

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)
69 Downloads (Pure)

Abstract

Freshwater ecosystems are primarily impacted by climate, land use and land cover changes, and over-abstraction. Satellite Earth observation (SEO) data and technologies are key in environmental modelling and support decisions. These technologies combined with machine learning (ML) are a powerful approach for modelling freshwater ecosystems at a multiscale level. The goal of this study is to present a set of reference data and guidelines that can be used to estimate the water and wetness probability index (WWPI) in different spatial and temporal scales. To find the best model’s predictors, sensitivity analyses were carried out in a predictive ML model implemented in a transnational river basin district (Portugal – Spain), the Tagus Basin. Satellite imagery, satellite-derived data, biophysical variables, and landscape characteristics were the explanatory variables evaluated in the sensitivity analyses, and some of them were included in the framework as a reference source of spatial data.
Original languageEnglish
Title of host publicationProceedings of the 9th International Conference on Geographical Information Systems Theory, Applications and Management
Subtitle of host publicationGISTAM 2023
EditorsCédric Grueau, Armanda Rodrigues, Lemonia Ragia
PublisherSciTePress - Science and Technology Publications
Pages104-111
Number of pages8
Volume1
ISBN (Print)978-989-758-649-1
DOIs
Publication statusPublished - 1 May 2023
Event9th International Conference on Geographical Information Systems Theory, Applications and Management: GISTAM 2023 - Prague, Czech Republic, Prague, Czech Republic
Duration: 25 Apr 202327 Apr 2023
Conference number: 9

Conference

Conference9th International Conference on Geographical Information Systems Theory, Applications and Management
Abbreviated titleGISTAM
Country/TerritoryCzech Republic
CityPrague
Period25/04/2327/04/23

Keywords

  • Remote Sensing
  • Ecosystem Services
  • Water Modelling
  • Machine Learning
  • Geographical Information Systems

Fingerprint

Dive into the research topics of 'Data-Driven Modelling of Freshwater Ecosystems: A Multiscale Framework Based on Global Geospatial Data'. Together they form a unique fingerprint.

Cite this