The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume L-4/W1-2026
https://doi.org/10.5194/isprs-archives-L-4-W1-2026-235-2026
https://doi.org/10.5194/isprs-archives-L-4-W1-2026-235-2026
29 Aug 2026
 | 29 Aug 2026

Shared Landscapes, Shared Futures: Visual Landscape Evolution Modelling for Community Stewardship

Vinuri Piyathilake, Matthew W. Hughes, and Matthew Wilson

Keywords: Landscape evolution modelling, Indigenous land stewardship, Place-based Indigenous knowledge, Participatory modelling, Free and open-source software (FOSS)

Abstract. Landscapes are living systems whose long-term trajectories carry profound cultural, spiritual, and resource significance for Indigenous communities worldwide. Yet the tools capable of simulating long-term landscape change, such as numerical landscape evolution models, remain largely inaccessible outside specialist research communities, constraining their potential contribution to community-led stewardship and land management decision-making. This paper introduces LandEvolve, a landscape evolution modelling framework developed entirely within a free and open-source software ecosystem, designed to extend process-based geomorphic simulation into community-accessible settings. Built upon the Landlab platform, it integrates a Python-based graphical user interface developed using the Qt framework and supporting libraries, enabling users to configure and execute simulations such as fluvial incision, hillslope diffusion, and sediment transport without requiring programming expertise or specialist technical knowledge. The tool and its source code will be made publicly available to enable reuse, modification, and community-driven development. As a primary case study, LandEvolve is co-developed with M¯aori Indigenous communities of Aotearoa New Zealand through an iterative participatory process in which Indigenous knowledge directly informs scenario design and model configuration. This engagement is grounded in geoethical principles and data sovereignty frameworks, ensuring that culturally sensitive information remains under community governance and that communities retain meaningful agency throughout the modelling process. Interactive two-dimensional and three-dimensional visualisation capabilities further support accessible, dialogue-based exploration of landscape futures, illustrating how open-source geospatial tools can be repositioned as instruments of intergenerational stewardship that place long-term landscape futures in the hands of the communities who depend on, and hold responsibility for, them.

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