Trait-Driven Models of Ecology and Evolution 🌲
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Updated
May 27, 2024 - C++
Trait-Driven Models of Ecology and Evolution 🌲
A multi-purpose dataset for data-driven wildfire modeling in the Mediterranean. Deep Learning models for wildfire modeling, e.g. danger forecasting, burned area prediction, etc
Detection and analysis of insect defoliators in tree rings
Compute arboricity and forest decomposition of graphs.
Jupyter notebooks to bulk download KML files from the Forest clearance portal, Ministry of Environment and Forests, India.
We estimate the potential carbon store of different ecosystems of the world
A quantum puzzle and adventure into Native Language decolonization; features an introduction to the master quantum plane and the truthful history of indigenous peoples on Turtle Island. Not G-rated.
Code, data and manuscript for "Fernández-Pascual (2021) SylvanSeeds, a seed germination database for temperate deciduous forests. Journal of Vegetation Science." https://doi.org/10.1111/jvs.12960
Deforestation amplifies flood risk and severity in the developing world
This repository provides the code and data to model fire and drought effects in the Mediterranean forests, as in the paper Baudena et al 2020, New Phytologist
EDA and ML Models for Kaggle Competitions
Product Landing Page/Save the Forests
Code for Sales et al 2021
This code repository contains implementations of Decision Trees and Random Forests in Kotlin for both classification and regression tasks. Decision Trees and Random Forests are powerful machine learning algorithms for decision-making and prediction problems. The code is written in Kotlin, a modern and concise programming language.
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