_site_template.Rmd

---
title: 'Site: `r params$site_name`'
params:
  site_id: usa-fkc
  site_name: "False Klamath Cove"
editor_options:
  chunk_output_type: console
---

```{r setup, include=F}
knitr::opts_chunk$set(echo = F, message = F, warning = F, python.reticulate = F)
```

```{r}
source(here::here("scripts/functions.R"))

if (!exists("params")) 
  params <- list(
  # site_name = "Kibesillah Hill",
  # site_id   = "usa-kib")
  site_name = "Mar del Plata - Faro",
  site_id   = "arg-mardelplata-faro")

site <- read_csv(here("data/sites.csv"), col_types=cols()) %>%
  filter(id == params$site_id)

site_photo_csv <- "https://docs.google.com/spreadsheets/d/1-1rIIiH9OV1C7vPzAH4R_PpC1fFj3ZoA6sV8J28Loxc/gviz/tq?tqx=out:csv&sheet=site_photos.csv"

photos <- read_csv(site_photo_csv, col_types=cols()) %>%
  filter(id == params$site_id)

sst   <- info('jplMURSST41mday'         , url = "https://upwell.pfeg.noaa.gov/erddap/")
chl   <- info("VIIRS_OC_NRT_7D"         , url = "https://cwcgom.aoml.noaa.gov/erddap/")
scape <- info("noaa_aoml_4729_9ee6_ab54", url = "https://cwcgom.aoml.noaa.gov/erddap/")
```

- Country: **`r str_to_upper(site$country)`**
- Organization: **`r site$org`**

## Photos

```{r}
if (nrow(photos) > 0){
  carousel <- bs_carousel(id = "photos", use_indicators = TRUE)

  for (i in 1:nrow(photos)){
    photo <- photos[i,]
    carousel <-  bs_append(
      carousel,
      content = bs_carousel_image(src = photo$url),
      caption = bs_carousel_caption(photo$caption))
  }

  carousel
} else {
  cat("No photos yet posted.")
}
```

## Maps {.tabset}

### Temperature

```{r}
# get most recent date
d <- get_dates(sst)[2]
```

Map of the most recent (`r format(d,"%Y-%m-%d")`) sea-surface temperature around the site. Data source: PFEG CoastWatch via ERDDAP.

```{r}
# box <- get_box(site$lon, site$lat, cells_wide=10)
# r   <- get_raster(sst, lon=box$lon, lat=box$lat, date="last", field="sst")
# map_raster(r, site_lon=site$lon, site_lat=site$lat, site_label=site$name, title="SST")

# bounding box offset around site marker for extent of map
b <- 3.0

leaflet(
  options = leafletOptions(
    crs = leafletCRS(crsClass = "L.CRS.EPSG4326"))) %>%
  # basemap from GBIF in 4326
  addTiles("//tile.gbif.org/4326/omt/{z}/{x}/{y}@1x.png?style=gbif-geyser") %>%
  # sst
  addWMSTiles(
    baseUrl = 'https://coastwatch.pfeg.noaa.gov/erddap/wms/jplMURSST41mday/request?',
    layers = "jplMURSST41mday:sst",
    options = WMSTileOptions(
      version = "1.3.0", format = "image/png", transparent = T, opacity = 0.7,
      time = format(d,"%Y-%m-%dT00:00:00Z")))  %>%
  addMarkers(lng = ~lon, lat = ~lat, label = ~name, data=site) %>%
  addMouseCoordinates() %>%
  fitBounds(site$lon - b, site$lat - b, site$lon + b, site$lat + b) %>%
  addLegend(
    position="bottomright",
    title = paste0("SST (°C)<br>", format(d,"%Y-%m-%d")),
    colorNumeric("Spectral", c(0,32), reverse=T), seq(0,32))
```

### Chlorophyll

```{r}
# get most recent date
d_2 <- get_dates(chl)[2]
```

Map of the most recent (`r format(d_2, "%Y-%m-%d")`) Chlorophyll-a around the site. Data Source: PFEG CoastWatch via ERDDAP.

```{r}
# box_2 <- get_box(site$lon, site$lat, cells_wide=10)
# r_2   <- get_raster(chl, lon=box$lon, lat=box$lat, date="last", field="chl")
# map_raster(r, site_lon=site$lon, site_lat=site$lat, site_label=site$name, title="CHL")

# bounding box offset around site marker for extent of map
b_2 <- 3.0

leaflet(
  options = leafletOptions(
    crs = leafletCRS(crsClass = "L.CRS.EPSG4326"))) %>%
  # basemap from GBIF in 4326
  addTiles("//tile.gbif.org/4326/omt/{z}/{x}/{y}@1x.png?style=gbif-geyser") %>%
  # sst
  addWMSTiles(
    baseUrl = 'https://cwcgom.aoml.noaa.gov/erddap/wms/VIIRS_OC_NRT_7D/request?',
    layers = "VIIRS_OC_NRT_7D:chlor_a",
    options = WMSTileOptions(
      version = "1.3.0", format = "image/png", transparent = T, opacity = 0.7,
      time = format(d_2,"%Y-%m-%dT00:00:00Z")))  %>%
  addMarkers(lng = ~lon, lat = ~lat, label = ~name, data=site) %>%
  addMouseCoordinates() %>%
  fitBounds(site$lon - b_2, site$lat - b_2, site$lon + b_2, site$lat + b_2) %>%
  addLegend(
    position="bottomright",
    title = paste0("CHL (mg m^-3)<br>", format(d_2,"%Y-%m-%d")),
    colorNumeric("Spectral", c(0,4), reverse=T), seq(0,4))
```

### Seascape

```{r}
# get most recent date
d_2 <- get_dates(scape)[2]
```

Map of the most recent (`r format(d_2, "%Y-%m-%d")`) seascapes around the site. Data Source: AOML CWCGOM via ERDDAP.

```{r}
# box_2 <- get_box(site$lon, site$lat, cells_wide=10)
# r_2   <- get_raster(chl, lon=box$lon, lat=box$lat, date="last", field="chl")
# map_raster(r, site_lon=site$lon, site_lat=site$lat, site_label=site$name, title="CHL")

# bounding box offset around site marker for extent of map
b_2 <- 3.0

leaflet(
  options = leafletOptions(
    crs = leafletCRS(crsClass = "L.CRS.EPSG4326"))) %>%
  # basemap from GBIF in 4326
  addTiles("//tile.gbif.org/4326/omt/{z}/{x}/{y}@1x.png?style=gbif-geyser") %>%
  # sst
  addWMSTiles(
    baseUrl = 'https://cwcgom.aoml.noaa.gov/erddap/wms/noaa_aoml_4729_9ee6_ab54/request?',
    layers = "noaa_aoml_4729_9ee6_ab54:CLASS",
    options = WMSTileOptions(
      version = "1.3.0", format = "image/png", transparent = T, opacity = 0.7,
      time = format(d_2,"%Y-%m-%dT00:00:00Z")))  %>%
  addMarkers(lng = ~lon, lat = ~lat, label = ~name, data=site) %>%
  addMouseCoordinates() %>%
  fitBounds(site$lon - b_2, site$lat - b_2, site$lon + b_2, site$lat + b_2) %>%
  addLegend(
    position="bottomright",
    title = paste0("CLASS<br>", format(d_2,"%Y-%m-%d")),
    colorNumeric("Spectral", c(1,33), reverse=T), seq(1,33))
```

Read more about seascapes [here](https://coastwatch.noaa.gov/cw/satellite-data-products/multi-parameter-models/seascape-pelagic-habitat-classification.html){target="_blank"}.

## Timeseries {.tabset}

### Temperature, Satellite

```{r}
csv <- here(glue("data/sst/sst_{site$id}.csv"))
d   <- get_timeseries(sst, lon=site$lon, lat=site$lat, csv=csv, field="sst")
plot_timeseries(d, title="SST", color="red")
```

Download data: [`r basename(csv)`](https://raw.githubusercontent.com/marinebon/p2p/master/data/sst/`r basename(csv)`){target="_blank"}

```{python, eval=F}
# transform something like
#    https://marinebon.github.io/home/travis/build/marinebon/p2p/data/sst/sst_wi-maracas.csv
# into
#    https://raw.githubusercontent.com/marinebon/p2p/master/data/sst/sst_wi-maracas.csv
csv = str(r.csv).replace("/marinebon/p2p/data/", "/marinebon/p2p/master/data/")
csv_link = "https://raw.githubusercontent.com/" + csv.split("/marinebon/p2p/")[1]
```

```{r, results='asis'}
# source("scripts/functions.R")
if (!exists("params")) 
  params <- list(
  site_name = "Arraial do Cabo - Fortaleza",
  site_id   = "bra-arraialdocabo-fortaleza")

temp_csv <- here(glue("data/temperature_in-situ/{params$site_id}.csv"))
meta_yml <- here(glue("data/temperature_in-situ/{params$site_id}_meta.yml"))
site_url <- glue("https://raw.githubusercontent.com/marinebon/p2p/master/data/temperature_in-situ/{basename(temp_csv)}")

has_temp_insitu <- all(file.exists(c(temp_csv, meta_yml)))
```

```{r, child=if (has_temp_insitu) '_temperature_in-situ.Rmd'}
```

### Chlorophyll

```{r}
csv   <- here(glue("data/chl/chl_{site$id}.csv"))

# TODO: fix get_timeseries() -> griddap() -> erd_up_GET()
d_chl <- get_timeseries(chl, lon=site$lon, lat=site$lat, csv=csv, field="chlor_a")
plot_timeseries(d_chl, title="CHL", color="green")
```

Download data: [`r basename(csv)`](https://raw.githubusercontent.com/marinebon/p2p/master/data/chl/`r basename(csv)`){target="_blank"}

## Taxonomic records in [OBIS](https://obis.org/){target="_blank"} {.tabset}

### Time Series

```{r, eval = T}
library(readr)
library(sf)
library(ggplot2)

# obis_taxa_hist_png <- here(glue("images/sites/{params$site_id}_obis_taxa_hist.png"))
obis_data_csv      <- here("data/obis/obis_data.csv")

# read in OBIS data ----
# previously fetched OBIS data by scripts/obis_download.R
obis_data  <- read_csv(obis_data_csv, col_types = cols()) %>% 
  st_as_sf(
    coords = c("decimalLongitude", "decimalLatitude"),
    crs = 4326,
    remove = F)
obis_sites <- read_sf(here("data/obis/obis_sites.geojson"))

# get obis data for site ----
# params <- list(site_id = "arg-puertomadryn2")
obis_site <- obis_sites %>% 
  filter(id == params$site_id)

d_obis_site <- obis_data[st_intersects(obis_data, obis_site, sparse = F),] %>% 
  mutate(
    taxa = ifelse(
      kingdom == "Plantae", 
      "Kingdom:\n Plantae", 
      glue("Phylum:\n  {phylum}", .trim = F))) %>% 
  rename(year = date_year)

## Plot the data ----
g <- d_obis_site %>% 
  st_drop_geometry() %>% 
  plot_obis_hist(year, taxa)
  # ggsave(filename = obis_taxa_hist_png)

# knitr::include_graphics(obis_taxa_hist_png)

# TODO: title <- glue("Data source: https://obis.org/area/{site$area_code}")
# TODO: get institution field since institutionID is blank
#       plot_obis_hist(d_obis_site, year, institutionID)

plotly::ggplotly(g)
```

### Maps

**Mollusca**
```{r, echo=FALSE, message=FALSE, warning=FALSE}
d_obis_site %>% 
  filter(phylum == "Mollusca") %>% 
  map_obis_pts(obis_site)
```

**Echinodermata**
```{r, echo=FALSE, message=FALSE, warning=FALSE}
d_obis_site %>% 
  filter(phylum == "Echinodermata") %>% 
  map_obis_pts(obis_site)
```

**Annelida**
```{r, echo=FALSE, message=FALSE, warning=FALSE}
d_obis_site %>% 
  filter(phylum == "Annelida") %>% 
  map_obis_pts(obis_site)
```

**Plantae**
```{r, echo=FALSE, message=FALSE, warning=FALSE}
d_obis_site %>% 
  filter(kingdom == "Plantae") %>% 
  map_obis_pts(obis_site)
```

## Data source:
Data shown here is extracted using the [occurrence](https://www.rdocumentation.org/packages/robis/versions/1.0.1/topics/occurrence){target="_blank"} function of the [robis](https://www.rdocumentation.org/packages/robis/versions/1.0.1){target="_blank"} package within a 0.25 x 0.25 degrees box centered at monitoring sites.