Satellite data, extreme weather, trees, soil data and AI
Title: Satellite data, extreme weather, trees, soil data and AI
DNr: NAISS 2024/22-679
Project Type: NAISS Small Compute
Principal Investigator: Zhicong Xie <>
Affiliation: Göteborgs universitet
Duration: 2024-06-20 – 2025-07-01
Classification: 10599


1. Urban tree project -- processing satellite data This is a subproject of my PhD study. The main aim is to predict summer soil hydraulic levels by analyzing vegetation state, water, and weather conditions, and identify the importance of different factors using satellite data (Landsat, 30m resolution and Data from Planet, 3m resolution). The results will inform the selection of fieldwork locations and strategies for the urban tree project. This analysis provides a preliminary overview for more detailed simulations and field studies. Future extensions of this work are possible if innovative ideas and data are adequately prepared (e.g., image processing and neural networks). 2. Ecosystem modelling Process-based model will be used to study the effects of extreme weather on trees' functioning and services. The parameter settings require a lot of computation and time. 3. Processing large dataset Process global scale dataset with 1 degree or 0.25 degree scale.