BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//talks.osgeo.org//foss4g-2026//speaker//UDMRUT BEGIN:VTIMEZONE TZID:JST BEGIN:STANDARD DTSTART:20000101T000000 RRULE:FREQ=YEARLY;BYMONTH=1 TZNAME:JST TZOFFSETFROM:+0900 TZOFFSETTO:+0900 END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:pretalx-foss4g-2026-87ZRJH@talks.osgeo.org DTSTART;TZID=JST:20260902T160000 DTEND;TZID=JST:20260902T163000 DESCRIPTION:Understanding how landscapes evolve across decades to millennia is fundamental for environmental planning\, hazard mitigation\, infrastru cture management\, and heritage protection. Many environmental processes a ffecting land stability operate at timescales far exceeding typical planni ng horizons. Hillslope diffusion\, fluvial incision\, sediment transport\, and gradual terrain adjustment continuously reshape catchments and river networks\, influencing erosion risk\, water quality\, and the preservation of archaeological and culturally significant features. However\, contempo rary geospatial workflows are largely observational. Geographic Informatio n Systems (GIS) and remote sensing platforms excel at representing present conditions and monitoring short-term change\, yet provide limited capacit y to evaluate how landscapes may respond to long-term environmental or hum an disturbances. Consequently\, planners and land managers must often make decisions without accessible tools for understanding long-term terrain re sponse.\n\nNumerical landscape evolution models (LEMs) offer a framework f or investigating long-term terrain change. A LEM is a computational model that represents a landscape as a digital surface and simulates how its ele vation evolves over time according to governing physical relationships bet ween topography and environmental forcing. Rather than analysing a single snapshot of terrain\, the model iteratively updates the land surface acros s many time steps\, allowing users to explore how landscapes may respond t o natural variability or human intervention. Unlike conventional spatial a nalysis\, which evaluates patterns at a fixed moment\, LEMs simulate dynam ic landscape behaviour and enable both reconstruction of past terrain cond itions and exploration of potential future environmental states. For geomo rphologists\, they function as a virtual laboratory for examining Earth-su rface change over timescales that cannot be directly observed. \n\nDespite their scientific maturity\, LEMs remain largely absent from operational g eospatial practice\, and it is still unclear how they can be effectively a pplied in real-world decision-making contexts. To investigate this issue\, we conducted a comprehensive systematic review of landscape evolution mod elling studies focused on anthropogenic landforms. The review identifies a restricted scope of application. Existing implementations are concentrate d predominantly within mining-related environments\, particularly post-ext raction rehabilitation landscapes\, with comparatively little use in other human-modified terrains. While many studies simulate overall landscape ev olution\, they seldom examine the evolution of specific localized features within those landscapes that are directly relevant to management or plann ing. Furthermore\, stakeholder or community participation is largely absen t\; modelling activities are typically undertaken as research-driven acade mic exercises rather than collaborative decision-support tools.\n\nFollowi ng the review\, we suggest that the principal barrier preventing broader a doption of landscape evolution models is not scientific validity but geosp atial usability. Existing modelling frameworks provide physically robust p rocess simulation\, yet they remain inaccessible to most practitioners out side geomorphology and scientific computing. Configuration typically requi res scripting knowledge\, parameter editing through code\, and specialised understanding of numerical modelling workflows. Consequently planners\, h eritage practitioners\, and community stakeholders cannot meaningfully int eract with models even when the questions addressed are directly relevant to land management. The challenge\, therefore\, lies not in modelling capa bility but in translating simulation into a form usable within everyday ge ospatial practice.\n\nBuilding on this observation\, we propose an approac h centred on intuitive landscape evolution modelling. Rather than position ing numerical simulation as a specialised scientific activity\, the study extends landscape evolution modelling into an accessible interactive envir onment that communities can freely use and explore. The modelling backend is implemented using Landlab\, an open source Python library that provides modular components for representing Earth surface processes\, including h ydrological routing\, fluvial incision\, sediment transport\, and hillslop e diffusion. This modelling engine is connected to a graphical user interf ace (GUI) developed using Qt for Python\, allowing model configuration and execution to occur through direct visual interaction rather than scriptin g. Through the interface\, users can define the area to be simulated\, spe cify simulation duration and timestep structure\, and choose which geomorp hic processes to include\, all without modifying code. In this way\, proce ss-based geomorphic modelling is translated into a form that can be unders tood and used without scientific computing expertise.\n\nSimulation output s are presented through interactive two dimensional and three dimensional terrain visualisations\, elevation change maps\, and comparisons between i nitial and simulated topography. Rather than producing static results\, th e system allows landscape change to be observed progressively across exten ded timescales. Users can explore how environmental conditions influence g radual terrain development and examine how different assumptions alter lon g term outcomes. By visualising processes that normally occur over centuri es to millennia\, the model supports interpretation of environmental dynam ics that cannot be directly observed within human lifetimes and encourages discussion about potential future landscape states.\n\nFor participatory application\, the framework is applied to Indigenous landscapes in Aotearo a New Zealand\, where relationships with ancestral land emphasise continui ty across generations. The project seeks to undertake community engagement workshops with Māori communities in which participants interact directly with simulations and collectively examine possible environmental futures. Participants explore alternative scenarios and discuss the implications o f gradual environmental change for culturally significant landscape featur es. Through this collaborative process\, modelling becomes a shared interp retive activity that supports dialogue and understanding rather than a pur ely technical analysis conducted by researchers alone.\n\nThis engagement reveals an additional dimension often absent from numerical geomorphology. The study highlights the importance of geoethics within landscape evoluti on modelling by incorporating Indigenous knowledge and stewardship perspec tives into model interpretation. The simulations function as a medium for communication between scientific understanding and community knowledge\, s upporting culturally grounded responses to environmental change. By combin ing accessible modelling\, transparent workflows\, and participatory engag ement\, the work demonstrates how predictive environmental modelling can m ove beyond academic research and contribute to collaborative environmental stewardship and long term landscape care.\n\nFinally\, the study emphasis es methodological transparency through an explicitly open and reproducible workflow. The system is implemented entirely using freely available open- source geospatial software\, and the modelling code\, configuration files\ , and demonstration datasets will be publicly released under an open-sourc e licence. This allows independent verification of results\, replication o f simulations\, and adaptation of the framework to different environmental and planning contexts. By removing dependence on proprietary platforms\, the approach lowers practical barriers for practitioners and communities w hile supporting reproducible research standards. In doing so\, the work po sitions landscape evolution modelling as a transparent and transferable an alytical tool rather than a closed\, specialist research product. DTSTAMP:20260717T225753Z LOCATION:Cosmos2 SUMMARY:Shared Landscapes\, Shared Futures: Visual Landscape Evolution Mode lling for Community Stewardship - Vinuri Piyathilake URL:https://talks.osgeo.org/foss4g-2026/talk/87ZRJH/ END:VEVENT END:VCALENDAR