Spatial Dependence: Weighting Schemes and Statistics
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Dec 19, 2024 - R
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spatial-autocorrelation
Here are 18 public repositories matching this topic...
📦🐍 Python package to model and forecast the risk of deforestation
python forecasting spatial-analysis roads protected-areas deforestation redd ipcc ipbes co2-emissions spatial-autocorrelation land-use-change spatial-modelling tropical-forests biodiversity-scenario forest-cover-change deforestation-risk
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Jul 17, 2024 - Python
🌍 📝 Modelling and forecasting deforestation in the tropics
forecasting spatial-analysis roads climate-change protected-areas deforestation redd ipcc ipbes co2-emissions spatial-autocorrelation land-use-change spatial-modelling tropical-forests biodiversity-scenario forest-cover-change deforestation-risk
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Dec 4, 2023 - R
Data, code and manuscript for 'Spatial occupancy models for data collected on stream networks'
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Nov 20, 2024 - TeX
Machine learning analysis & visualisation of cellular spatial point patterns
spatial-data-analysis spatial-statistics knn-classification random-forest-classifier spatial-visualizations spatial-autocorrelation
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Jul 19, 2024 - R
Scripts to create tree species classification models from NEON Science hyperspectral and vegetation data. Created as part of my master's thesis in GeoInformatics at Hunter College, 2023.
machine-learning deep-learning annotation random-forest vegetation pca geography hyperspectral geoinformatics spatial-autocorrelation surfing-dogs
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Apr 17, 2023 - Python
The R Shiny App for machine learning analysis and visualization of cellular spatial point patterns under hypercaloric diet shifts.
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Sep 30, 2024 - R
Analysis of palaeoecological records across South-East Asia to determine the evidence for regime shifts between open savannas and dense tropical forests occurred since the Last Glacial Maximum
correlation biome resampling south-east-asia palynology spatial-autocorrelation standardisation savanna last-glacial-maximum savanna-corridor ecological-resilience
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Nov 25, 2023 - R
Geospatial data analysis, street network analysis, spatial autocorrelation, maps
geospatial-data street-networks geopandas geospatial-analysis spatial-autocorrelation cloropleth-maps geospatial-visualization folium-maps
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Apr 8, 2021 - Jupyter Notebook
The goal is to develop a method that automates the generation of large-scale, spatial DEVS simulation models from GIS data
simulation gis spatial-analysis spatial-data simulation-modeling geospatial-analysis spatial-autocorrelation
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Nov 2, 2020 - Jupyter Notebook
Determining the most important predictors of diarrhoea in children under five in South and Southeast Asia by exploring the spatiotemporal association between diarrhoeal incidence and various behavioural, socio-demographic, and environmental factors.
machine-learning health india nepal resampling myanmar bangladesh climate-change pakistan philippines cambodia southeast-asia spatial-autocorrelation timor-leste child-mortality child-health boosted-regression-trees diarrhoea low-and-middle-income-countries south-asia
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Dec 6, 2024 - R
Spatial Statistical analyses created using R and RStudio for an "Advanced Statistics for Urban Applications" at Temple University
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Mar 18, 2019 - R
This tutorial uses Global Moran’s I and Local Interpretation of Spatial Autocorrelation (LISA) testing methods to determine the spatial correlation between median total income and the percentage of French knowledge speakers in Kelowna, British Columbia.
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Oct 21, 2024
Classifying Travel Mode choice in the Netherlands using KNN, XGBoost, RF and TabNet
travel geospatial-data spatial-data lime oversampling undersampling random-forest-classifier explainable-ai knn-algorithm spatial-autocorrelation shap optuna weight-matrix tabnet xgboost-classifier moran-i train-validation-test mode-choice smote-tomek
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May 20, 2024 - Jupyter Notebook
Calculating global and local spatial autocorrelation of income noted per each polish county in 2022 based on Moran's I and LISA statistics. Calculations were conducted using the following packages: pySAL, splot.esda, geopandas.
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Jan 11, 2024 - Jupyter Notebook
Code developed for the paper "The Impact of Public Transport on the Diffusion of the COVID-19 Pandemic in Lombardy during 2020".
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Oct 7, 2023 - R
A groundwater level spatiotemporal prediction model based on graph convolutional networks with a long short-term memory
graph-convolutional-networks long-short-term-memory spatial-autocorrelation groundwater-level spatiotemporal-prediction temporal-dependency
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Oct 11, 2024 - Python
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