examine_point.qmd

---
title: "Examine Point & Create Habitat Record"
author: "Tylar Murray"
editor: source
execute: 
  echo: false
  warning: false
---
Use this protocol to examine a lat,lon point and create a classification record.

```{r}
#| include: false

#remotes::system_requirements("ubuntu", "20.04", package = "geojsonio")
install.packages("librarian")
librarian::shelf(
  "geojsonio",
  "ggplot2",
  "r-spatial/rgee",
  "tidyverse",
)
rgee::ee_install()
```

Auth GEE:
```{r}
#| eval: false
# rgee::ee_Authenticate()
rgee::ee_Initialize()
```

```{r}
# Define the location (latitude and longitude)
lat <- 27.63615563874265
lon <-  -80.99341033321342

# Define the time period (e.g., start and end dates)
start_date <- "2020-01-01"
end_date <- "2024-01-01"

ic_id = "IDAHO_EPSCOR/TERRACLIMATE"
```

```{r}
# Define the collection
terraclimate <- ee$ImageCollection(ic_id) %>%
  ee$ImageCollection$filterDate(start_date, end_date) %>%
  ee$ImageCollection$filterBounds(ee$Geometry$Point(lon, lat))

print(terraclimate$getInfo())

# Do extraction ----
ee_nc_rain <- ee_extract(
  x = terraclimate, 
  y = ee$Geometry$Point(lon,lat),
  sf = FALSE,
  scale = 1000,  # meters
)

# extraction comes back as a wide df with columns like X{img_id}_{band_id}
# convert it to a long df
long_df <- ee_nc_rain %>%
  pivot_longer(everything(), names_to = "column") %>%
  separate(col = column, into = c("img_id", "band_id"), sep = "_", remove = FALSE) %>%
  select(-column) %>%
  rename(value = value) %>%
  mutate(img_id = str_replace(img_id, "X", ""))

# add the dates of the images
image_dates <- ee_get_date_ic(terraclimate) %>%
  mutate(
    id = str_replace(id, ".*/", ""),   # cut the ic_id out
    time_start = as.Date(time_start)
  ) 
long_df <- long_df %>%
  left_join(image_dates, by = c("img_id" = "id"))
  
# plot the ts
ggplot(long_df, aes(x = time_start, y = value, color = band_id)) +
  geom_line() +
  labs(x = "Date", y = "Value") +
  ggtitle("Time Series Plot by Band") +
  theme_minimal()
```