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Challenge 1 - Getting started alt

Welcome to the 2021 Better Working World Data Challenge!

This notebook will show you how to open and explore the data, identify problematic areas of the data, create a basic solution to the problem, and submit your results via the EY Data Science platform.

Prior to running this notebook, make sure you have:

We also recommend checking out the resources in the "01_Beginners_guide" folder to learn about jupyter notebooks and the Open Data Cube before coming back here.

Your task

The training dataset contains 129 linescan images (infra-red images taken from an airplane) of bushfires in Victoria, Australia, during the first three months of 2019. There are also polygons showing where the fire is in each image, which have been hand-drawn by our collaborators at the Country Fire Authority (CFA). These polygons are the ground truth your solution should be able to recreate.

There are an additional 5 linescan images, the test dataset, where the polygons showing the fire boundaries have not been provided. Your task is to train a model or process which can produce a fire boundary for the remaining 5 linescans with no polygon.

All the linescan images (both the traning and test sets) are served via the Open Data Cube python library. The polygons are already available in your environment.

Import libraries and instantiate a datacube

%matplotlib inline
import sys
import numpy as np
import pandas as pd
import geopandas as gpd
from datetime import datetime

from datacube import Datacube
import matplotlib.pyplot as plt

sys.path.append("../scripts")
from dea_plotting import map_shapefile
from dea_spatialtools import xr_rasterize
/env/lib/python3.6/site-packages/geopandas/_compat.py:88: UserWarning: The Shapely GEOS version (3.7.2-CAPI-1.11.0 ) is incompatible with the GEOS version PyGEOS was compiled with (3.9.0-CAPI-1.16.2). Conversions between both will be slow. shapely_geos_version, geos_capi_version_string
dc = Datacube(app="Getting started")