Forest Fragmentation for Binary and Continuous Forest Cover Rasters
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Updated
Aug 23, 2023 - R
Forest Fragmentation for Binary and Continuous Forest Cover Rasters
Forest cover type classification/detection using linear support vector machine implemented with gradient descent (from scratch)
ML, NN, NLP, ARIMA, clustering, classification, mapping
Combining and cutting spatial variables (tree cover and deforestation data from Global Forest Change) for the neotropical and Central Africa region using buffers in GRASS GIS.
Using the "landscapemetrics" R package to calculate metrics inside 5 km buffers.
We do forest analytics using GIS and data visualization, in the hope of saving the planet from the plight of climate change through reforestation by offering a means for citizen-scientists to monitor ongoing efforts
Kaagle Competition. Use cartographic variables to classify forest categories.
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