GeoFun

GeoFun is a package designed to manage and process geo-data (GPS coordinates, geo-located images, etc.), and to produce a series of output such as KML files.

KMLBuilder

KMLBuilder is a module designed to ingest user-provided GPS coordinates and/or geo-located images, and to produce a final KML file with these. The end result is a folder with the final KML file (w/o coordinates) and an additional 'img' folder containing (resized or not) geo-located images to be accessed via a GIS software of preference. Cuyrrently, this works with GoogleEarth.

Below are the input requirements for both geo-located images and GPS coordinates:

• The Pandas DataFrame must have these headers: 'placemark', 'keep_elevation', 'time', 'lat', 'lon', 'elevation'
• 'placemark' is the name of the placemark(s) to be chosen by the user; e.g. if there are more than one trip, then the user could name each group of coordinates individually
• 'keep_elevation' is a binary (i.e. 1 or 0) telling the module whether to clamp coordinates to the ground or display the actual elevation recorded
• 'time' is not required; currently kept for future developments purposes
• 'lat', 'lon' GPS coordinates must be in decimal WGS84 GCS
• 'elevation' is the altitude measured in metres; please note that this needs to be provided if the user wants to display it as is in the GIS of choice
• Image format must be one handled by PIL (Pillow)
• Image geo-location must be present in their EXIF
• Image geo-location coordinates must be in WGS84 GCS
• Image EXIF requirements are: 'GPSInfo' for geo-location data extraction, 'DateTimeOriginal' for pictures ordering

Requirements

KMLBuilder uses a number of open source projects to work properly:

• [io]
• [datetime]
• [pathlib]
• [zipfile]
• [xml.dom.minidom]
• [PIL]
• [pandas]
• [numpy]
• [colour]

Installation

Install the dependencies and the module as you would normally:

pip install GeoFun

Usage as follows:

from GeoFun.KMLBuilder import CreateKmlFile
import pandas as pd


# 1) Load the coordinates data file into a Pandas DataFrame, 
gps_coords_raw = "coordinates/Apulia.csv"
gps_coords_df = pd.read_csv(gps_coords_raw)

# 2) the folder location of images to be loaded into the KML, and: 
img_folder = "images/"

# 3) and the file location of where the KML should be saved
kml_output = "kml/Apulia/"

# 4) and ingest everything into the CreateKmlFile() function: 
CreateKmlFile(kml_output,
              coords_df=gps_coords_df, 
              img_input_folder=img_folder, 
              resize_opt=100, # This is the resize filesize (in KB); can also be expressed as a 0-1 for percentage
              zip_files=True, # whether to zip the KML folder
              verbose=False) # whether to make the process verbose or not

Todos

• Expand module output types
• Improve quality
• Avoid module-sucking
• Any idea, fire away! :)

License

GNU GPLv3