Landscapes in the Critical Zone: Towards Geo(Morphic) Large Language Models in the Digital Earth

Abstract

Geomorphology lies at the center of the ‘Critical Zone’ (CZ) that hosts the complex interactions of weathering, soils, and the organisms in and on landscapes, reflecting geology, hydrology, slope behavior, erosion, and denudation. Many disciplines, including economics and planning, require extensive information about the CZ. This paper presents some first steps towards developing models for landscape and CZ descriptions for use within a Digital Earth framework, with the aim of promoting FAIR (findable, accessible, interoperable, and reusable) data. Fundamental to this approach is the appendage of geolocating information to digital object identifiers (DOIs) using decimal latitude–longitude ([dLL]) tuples. This enables information and data to be made digitally accessible across disciplines, as illustrated through the use of [dLL] geolocation examples of this protocol using Google Earth images. Data and image metadata are appended to a [dLL] location, creating ‘geomorphic information fields’. This schema can be easily implemented within published papers, reports, and books (Article+) using the POLE+O ontology. Appended ‘geomorphic information surfaces’ can be used to report events (such as soil loss and slope failures) that occur on these surfaces. Points with a [dLL] tuple can act as token identifiers in language/data models, as well as improve statistical analysis and the use of knowledge graphs. This paper also demonstrates ways in which data can be configured to address specific geomorphic and ecological problems and ways that digital information surfaces might contribute to the amalgamation of data from DEMs, maps, GIS, and emerging LLMs and World View Models.