Using_LIO_maps.Rmd

---
title: "Using LIO background imagery for mapping in R"
author: "Erica Newton"
date: "`r format(Sys.Date(), '%b %d, %Y')`"
output:
  html_document:
    df_print: paged
  pdf_document: default
---
```{r, setup, include=FALSE}
knitr::opts_chunk$set(message = FALSE)
knitr::opts_chunk$set(warning = FALSE)
```


# Use a georeferenced TIF as a background

- I created the .TIF by using the LIO topographic map as my baselayer in ArcGIS Pro, then exporting it as a georeferenced .TIF in ArcGIS Pro.
- Tip - use a custom large size in ArcGIS Pro and ensure output resolution is high; consider using Map Series for multiple backgrounds

```{r}
# install/load required libraries
#if (!require("pacman")) install.packages("pacman")
#pacman::p_load(raster, tidyverse, sf, RStoolbox)
library(tidyverse)
library(raster)
library(sf)
```

## Bring in georeferenced tif
```{r}
basemap <- brick("PeterboroughMap.tif")
# get the coordinate reference system 
mycrs <- st_crs(basemap)
```

## Create some example spatial data to map on top
```{r}
# Choose a few random locations in Peterborough
my_points <- tibble(latitude = c(44.305907, 44.307612, 44.314083, 44.282756847),
                    longitude = c(-78.333753, -78.336279, -78.325517, -78.32322240),
                    name = c("point 1", "point 2", "point 3", "point 4"),
                    value = c("good", "best", "best", "satisfactory"))

# Convert to spatial points df
my_points <- st_as_sf(my_points,                         
           coords = c("longitude", "latitude"),
           crs = "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0")

# Make sure crs is the same as my base layer
my_points <- st_transform(my_points, mycrs)

area_of_interest <- st_buffer(st_as_sfc(st_bbox(dplyr::filter(my_points, value != "satisfactory"))), 250)
```


```{r}
# map in a ggplot2 framework
ggRGB(basemap, r = 1, g = 2, b = 3) +
  geom_sf(data = my_points, aes(fill = value), size = 5, shape = 21) +
  scale_fill_manual(values = c("mediumorchid3", "deeppink3", "dodgerblue4"), 
                    breaks = c("best", "good", "satisfactory"), name = "Rating") +
  geom_sf(data = area_of_interest, fill = NA, colour = "orange", size = 2) +
  theme_void(base_size = 15) +
  theme(legend.position = c(0.8, 0.8))
```

## Clip basemap to extent of points buffered by 200 m, then map again  

```{r}
small_basemap <- crop(basemap, extent(st_buffer(my_points, 200)))

ggRGB(small_basemap, r = 1, g = 2, b = 3) +
  geom_sf(data = my_points, aes(color = value), size = 5) +
  theme_void(base_size = 15)
```

# For using rasters with leaflet:  

- https://rstudio.github.io/leaflet/raster.html


# Extract backgrounds from an image service hosted on ArcGIS Online

- I'm currently waiting for help on getting this to work   
- See https://github.com/R-ArcGIS/r-bridge/issues/54  
- Note that you must have an installation of ArcGIS Pro + ArcGIS Online account for this + install r-ArcGIS bridge.

```{r arcbinding, eval=FALSE}
library(arcgisbinding)
arc.check_product()

## Read in a District Polygon from D.C.
r.bound <- arc.data2sf(arc.select(arc.open('https://maps2.dcgis.dc.gov/dcgis/rest/services/DCGIS_DATA/Planning_Landuse_and_Zoning_WebMercator/MapServer/31')))

## Choose the smallest zone
Blagdon <- r.bound %>% filter(NAME == "Blagden Alley Residential Transition Area")

## Set Boundary to Image Service
r.obj <- arc.open('https://imagery.dcgis.dc.gov/dcgis/rest/services/Ortho/Ortho_2019/ImageServer')
r.arc <- arc.raster(r.obj, extent = extent(Blagdon))

# NOT WORKING
#r.R <- as.raster(r.arc)
#plotRGB(r.R)
```


```{r}
mylake <- brick("lakeontario.tif")

gfsgn <- read.csv("gfsgn_sites.csv")
gfsgn <- gfsgn %>% filter(!is.na(LAT))
gn_points <- st_as_sf(gfsgn,                         
           coords = c("LON", "LAT"),
           crs = "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0")


# Make sure crs is the same as my base layer
gn_points <- st_transform(gn_points, mycrs)
ggRGB(mylake, r = 1, g = 2, b = 3) +
  geom_sf(data = gn_points) +
  theme_void(base_size = 15) +
  theme(legend.position = c(0.8, 0.8))
```

```{r}
##crop to zoom in on lower bay and plot Fall 2018 sites
load(file="Allgear.Rdata")
CSMI_points <- st_as_sf(allgear,                         
           coords = c("LONGITUDE", "LATITUDE"),
           crs = "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0")
CSMI_points <- st_transform(CSMI_points, mycrs)

crop_mylake <- crop(mylake, extent(st_buffer(CSMI_points, 400)))

ggRGB(crop_mylake, r = 1, g = 2, b = 3) +
  geom_sf(data = CSMI_points, size = 5) +
  theme_void(base_size = 15)
```

```{r}
# Best places in Bruce County
BC <- brick("BruceCounty.tif")
ggRGB(BC, r = 1, g = 2, b = 3) +
  theme_bw(base_size = 15)
```