data_processing.Rmd

---
title: "data_processsing"
date: "2023-04-02"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

## Import the Dataset

```{r}
# install.packages(c("rgbif", "plyr"))
library(rgbif)
# For single species
lck <- occ_search(scientificName = "Lynx canadensis Kerr, 1792", limit = 10164)
```


```{r}
lc.data <- lck$data
# Export data as csv file
write.csv(lc.data, "datasets/raw/lc_raw.csv", row.names = FALSE)
```

```{r}
lc.data <- read.csv("datasets/raw/lc_raw.csv")
```

```{r}
colnames(lc.data)
```

```{r}
# percentage of missing values in each column in training dataset
p <- function(x) {sum(is.na(x))/length(x)*100}
sort(apply(lc.data, 2, p)) # marmin = 2 means function will be applied in each column 
```

```{r}
# Provinces
unique(lc$stateProvince)
```


```{r}
lc <- lc.data[, c('countryCode', 'stateProvince', 'higherClassification', 'month', 'locality', 'higherGeography', 'sex', 'decimalLatitude', 'decimalLongitude', 'dateIdentified', 'coordinateUncertaintyInMeters', 'footprintWKT', 'country')]

lc <- lc[lc$stateProvince == 'British Columbia' & !is.na(lc$stateProvince) & !is.na(lc$decimalLatitude) & !is.na(lc$decimalLongitude),]
```


```{r}
# Load required libraries
library(sp)
library(rgdal)

# Create a SpatialPointsDataFrame object using the lc df
lc_sp <- SpatialPointsDataFrame(coords = lc[, c("decimalLongitude", "decimalLatitude")],
                                       data = lc)

# Assign the WGS84 CRS (EPSG:4326) to the lc_sp object
proj4string(lc_sp) <- CRS("+proj=longlat +datum=WGS84")

# Transform the coordinates to match the CRS of the BC_win object
bc_crs <- "+proj=aea +lat_0=45 +lon_0=-126 +lat_1=50 +lat_2=58.5 +x_0=1000000 +y_0=0 +datum=NAD83 +units=m +no_defs"
lc_transformed <- spTransform(lc_sp, CRS(bc_crs))

# extract the transformed coordinates and assign them to lc df
lc$decimalLongitude <- lc_transformed@coords[, 1]
lc$decimalLatitude <- lc_transformed@coords[, 2]
```


```{r}
write.csv(lc, "datasets/processed/lc.csv", row.names = FALSE)
```