lidar_data_processor module

class lidar_data_processor.Lidar_Processor(region: str = '', polygon_array: list = [], epsg: int = 3857, default_epsg: int = 3857)

Bases: object

fetch_file()

Main function that fetches lidar point cloud data from EPT resources from AWS cloud storage.

Args: None

Returns:

Dataframe: Geopandas data frame for the identified region String: Path of the downloaded tiff file list: Pipeline array of the found region

get_geo_df(array_data: ndarray) → GeoDataFrame

Creates Dataframe from the PDAL pipeline array

Args:

array_data (Numpy Array): Numpy array of point clouds from pdal pipeline

Returns:

geopandas dataframe: geopandas dataframe of the downloaded region

get_region_from_boundary()

Identifies the required region from the polygon boundary Args: None

Returns:

Tuple: Tuple of bounds of the identified region JSON: json of the full region data from the metadata

get_region_from_name()

Identifies the required region from the region name Args: None

Returns:

Tuple: Tuple of bounds of the identified region JSON: json of the full region data from the metadata

pipline_executer()

Executes the PDAL pipeline to fetch lidar point cloud data from the AWS cloud storage.

Args: None

Returns:

list: List of point clouds fetched from AWS

pipline_modifier()

Modifies the PDAL pipeline template to the required region PDAL template

Args: None

Returns:

list: List of pipeline template with modified parameters