Research project
A Python based kernel to perform spatial (environmental) impact assessment
Complementary repository with data and code for Wolf & Tollefsen, 2021.
Spatiotemporal Gaussian process modeling for environmental data: non-stationary PDE prior, deep kernels, multi-fidelity fusion, and A-optimal sampling.非稳态 PDE + 核深度学习 + 多保真 Co-Kriging + 主动采样的物理约束克里金方法，用于复杂时空环境建模与预测
Enhanced Rock Weathering Analysis using USGS Alaska Geochemical Database
A pioneering methodological framework for environmental modeling in the LIFE A_GreeNET project using ENVI-met. This protocol integrates Rhinoceros, Grasshopper, and the Morpho plugin to create a standardized approach for urban environmental simulations.
This model is use to assess the suitability of current and future locations for commercial wind farm construction across the Conterminous United States (CONUS). Aggregated datasets have been prepared for all states and the CONUS. Model script: "LR_Equation_Code.py", "CA_Model_Code.py". Model instructions: "Model Description and Instructions.pdf".
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