1. Reproject data#
Many of the functions in airbornegeo require coordiantes in meters. We can use the function reproject to convert from geogrpahic coordinates (lat/lon) to projected coordinates, or between two different projected coordinates reference systems.
[3]:
%load_ext autoreload
%autoreload 2
import pandas as pd
import plotly.io as pio
import airbornegeo
pio.renderers.default = "notebook"
The autoreload extension is already loaded. To reload it, use:
%reload_ext autoreload
[5]:
data_df = pd.read_csv("data/AGAP_magnetic_survey.csv")
data_df = data_df[["Lon", "Lat", "MagL", "line", "unixtime"]]
data_df.head()
[5]:
| Lon | Lat | MagL | line | unixtime | |
|---|---|---|---|---|---|
| 0 | 75.635600 | -84.104393 | -22.30 | 1 | 1.229500e+09 |
| 1 | 75.636138 | -84.103897 | -23.06 | 1 | 1.229500e+09 |
| 2 | 75.636699 | -84.103403 | -23.81 | 1 | 1.229500e+09 |
| 3 | 75.637282 | -84.102910 | -24.57 | 1 | 1.229500e+09 |
| 4 | 75.637876 | -84.102417 | -25.32 | 1 | 1.229500e+09 |
1.1. Plot the data in projected units#
[6]:
airbornegeo.plotly_points(
data_df[::10], color_col="MagL", robust=True, size=2, coord_names=("Lon", "Lat")
)
1.2. Reproject#
Since the original data is in lat / lon, the input CRS will be EPSG:4326, and we can reproject the data to EPSG 3031 - South Polar Stereographic, since the data is located in Antarctica.
[8]:
data_df["easting"], data_df["northing"] = airbornegeo.reproject(
data_df.Lon,
data_df.Lat,
input_crs="EPSG:4326",
output_crs="EPSG:3031",
)
data_df.head()
[8]:
| Lon | Lat | MagL | line | unixtime | easting | northing | |
|---|---|---|---|---|---|---|---|
| 0 | 75.635600 | -84.104393 | -22.30 | 1 | 1.229500e+09 | 621072.177354 | 159052.962392 |
| 1 | 75.636138 | -84.103897 | -23.06 | 1 | 1.229500e+09 | 621126.010622 | 159060.533993 |
| 2 | 75.636699 | -84.103403 | -23.81 | 1 | 1.229500e+09 | 621179.696916 | 159067.801202 |
| 3 | 75.637282 | -84.102910 | -24.57 | 1 | 1.229500e+09 | 621233.338990 | 159074.801823 |
| 4 | 75.637876 | -84.102417 | -25.32 | 1 | 1.229500e+09 | 621287.011834 | 159081.682095 |
[9]:
airbornegeo.plotly_points(
data_df[::10],
color_col="MagL",
robust=True,
size=2,
coord_names=("easting", "northing"),
)