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Ecoclimates: Climate-Response Modelling of Vegetation

A simulator producing complex and realistic outdoor landscapes with vegetation growth and weather dynamics. With the ability to simulate more than 500,000 plants with individual geometries, the program can assist in predicting climate-response of vegetation to deforestation and changing weather patterns.

ACM Trans. Graph., Vol. 41, No. 4, Article 155

24 Jan 2024

Publication date: July 2022


A simulator producing complex and realistic outdoor landscapes with vegetation growth and weather dynamics. With the ability to simulate more than 500,000 plants with individual geometries, the program can assist in predicting climate-response of vegetation to deforestation and changing weather patterns.

Understanding the complex interconnection of plant ecosystems and their impact on the climate system plays a central role in predicting climate dynamics. While it is well understood that climatic variations cause changes in ecosystem distribution, structure and function, only recently it has been recognized that the composition of vegetation also impacts the development of weather, which – in turn – leads to the development of local climatic variation (microclimates) [Bastiaansen et al. 2020]. Researchers study the interconnection of plant ecosystems and their impact on the climate system as ecoclimates.

In this paper, we propose a method to capture feedback loops
between vegetation, soil, and the atmosphere at a local scale. We extend existing vegetation and atmosphere models and combine them with a novel soil model. This allows us to jointly simulate the hydrologic cycle, heat transfer, and light availability. We model tree growth interactively in response to gradients of water, temperature and light. As a result, we are able to capture a range of ecoclimate phenomena that have not been emergently modeled before, including geomorphic controls, forest edge effects, the Foehn effect and spatial vegetation patterning.

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WOJTEK PAŁUBICKI, UAM, Poland MIŁOSZ MAKOWSKI, UAM, Poland WERONIKA GAJDA, UAM, Poland TORSTEN HÄDRICH, KAUST, KSA DOMINIK L. MICHELS, KAUST, KSA SÖREN PIRK, Adobe Research*, USA



For more:

Machine Learning, LLM, 3D Visualisation, AI

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