# Cristián Vergara Fernández Portfolio
Project data science
[Project 1: Finding patterns in spanish cities based on land use and spatial configuration. (https://github.com/cristianvergaraf/Location-factors-of-tree-plantation-expansion-)
- We used hierarchical clustering model to find group of cities based on land use, spatial congifuguration and
- Statistics model using logistic regression to assess relative importance of location factors in the expansion of forest plantations in south-central Chile.
- Relative importance of variables was performed using a multimodel inference approach in R.
[Project 2: Finding patterns in spanish cities based on land use and spatial configuration. (https://github.com/cristianvergaraf/Location-factors-of-tree-plantation-expansion-)
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We used hierarchical clustering model to find group of cities based on land use, spatial congifuguration and
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Statistics model using logistic regression to assess relative importance of location factors in the expansion of forest plantations in south-central Chile.
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Relative importance of variables was performed using a multimodel inference approach in R.
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[Project 3: Land use cover classification using landsat images for the lingue basin in south central Chile (https://github.com/cristianvergaraf/Location-factors-of-tree-plantation-expansion-)
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Download landsat images using google earth engine
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Classify land use cover applying machine learning algorthms as random forest, sopport vector machine,
- Statistics model using logistic regression to assess relative importance of location factors in the expansion of forest plantations in south-central Chile.
- Relative importance of variables was performed using a multimodel inference approach in R.