Reproducible GIS Analysis in R

I’m midway through an R Markdown project that combines both vector and raster data, and I need a seasoned R programmer with solid GIS chops to help me wrap it up quickly. The repo already holds raw shapefiles, GeoTIFFs and a skeleton `project.Rmd`; what’s missing is the refined workflow that cleans, analyses, and visualises everything in a fully reproducible way.

Here’s what you’ll jump into:
• Data input spans points, lines, polygons, plus several raster layers.
• Tasks still outstanding include rigorous data cleaning (CRS harmonisation, clipping, re-projection), exploratory spatial analysis/modeling, and clear mapping logic.
• Final visual output must lean on custom graphs and charts that illustrate key spatial patterns—think `ggplot2`, `tmap`, or `plotly`-ready objects embedded straight in the document.

I’m looking for tidy, well-commented chunks that use packages like `sf`, `terra/raster`, `tidyverse`, and preferably `here` for portable paths. By the end, I should be able to clone the repo, run **knit**, and obtain:

• `final_report.html` – polished narrative with maps, charts, and concise spatial findings
• `project.Rmd` – the readable, reproducible source that generates the report in one click

If that workflow-first approach sounds like your normal day in RStudio, let’s get this finished.