18. Bibliografía#
Jerome S. Bruner. Toward a Theory of Instruction. Harvard University Press, Cambridge, MA, 1966.
Roger M. Downs and David Stea. Maps in Minds: Reflections on Cognitive Mapping. Harper & Row, New York, 1977. ISBN 0060417331.
Marta Fernández García. ¿por qué los modelos de ia suelen utilizar la similitud coseno? June 2024. LinkedIn Top Voice 2024. Publicado el 11 de junio de 2024. URL: https://www.linkedin.com/pulse/por-qu%C3%A9-los-modelos-de-ia-suelen-utilizar-la-coseno-fern%C3%A1ndez-garc%C3%ADa-shwlf/ (visited on 2025-10-19).
John R. Firth. A synopsis of linguistic theory, 1930–1955. In Studies in Linguistic Analysis, pages 1–32. Basil Blackwell, Oxford, 1957.
Michael F. Goodchild. Twenty years of progress: GIScience in 2010. Journal of Spatial Information Science, 1:3–20, 2010. doi:10.5311/JOSIS.2010.1.2.
Michael F. Goodchild and Paul A. Longley. Geographic information science. In Handbook of Regional Science, pages 1597–1614. Springer, 2021. doi:10.1007/978-3-662-60723-7_61.
Zellig S. Harris. Distributional structure. Word, 10(2-3):146–162, 1954. doi:10.1080/00437956.1954.11659520.
Patrick Helber, Benjamin Bischke, Andreas Dengel, and Damian Borth. Introducing eurosat: a novel dataset and deep learning benchmark for land use and land cover classification. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium, 204–207. IEEE, 2018.
Patrick Helber, Benjamin Bischke, Andreas Dengel, and Damian Borth. Eurosat: a novel dataset and deep learning benchmark for land use and land cover classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019.
CODATA. Open science for a global transformation: codata coordinated submission to the unesco open science consultation. Technical Report, Committee on Data of the International Science Council, 2020. URL: https://doi.org/10.5281/zenodo.3935461, doi:10.5281/zenodo.3935461.
Earth Science Literacy Initiative. Earth science literacy principles: the big ideas and supporting concepts of earth science. 2009.
Google Earth Engine and Google DeepMind. Satellite embedding v1. Google Earth Engine Data Catalog. Documentacion del conjunto de datos Google Satellite Embedding. La clave BibTeX conserva 2024, pero no representa el ano de publicacion. URL: https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_SATELLITE_EMBEDDING_V1_ANNUAL.
High-Level Expert Group on Artificial Intelligence. Ethics guidelines for trustworthy ai. Technical Report, European Commission, 2019. URL: https://doi.org/10.2759/346720, doi:10.2759/346720.
National Research Council. IT Roadmap to a Geospatial Future. The National Academies Press, Washington, DC, 2003. URL: https://doi.org/10.17226/10661, doi:10.17226/10661.
National Research Council. Learning to Think Spatially: GIS as a Support System in the K–12 Curriculum. The National Academies Press, Washington, DC, 2006.
National Research Council. Advancing Strategic Science: A Spatial Data Infrastructure Roadmap for the U.S. Geological Survey. The National Academies Press, Washington, DC, 2012. URL: https://doi.org/10.17226/13506, doi:10.17226/13506.