Starlight Aether SDK application example: Detection Video of GigaFactory Construction from (Freemium) Satellite Imagery

starlight_aether_gigafactory_video_app.py

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import aether as ae
import numpy as np
from aether.user_utils.HelpfulFilters import HelpfulFilters
import os

import logging
logger = logging.getLogger(__name__)


###############################################
#
#
# New & Historical Building Starts: Detection of
#  Construction from (Freemium) Satellite Imagery:
#  GigaFactory Video
#
# An example of the Starlight Aether SDK
# Starlight: starlight.ai
# Aether SDK docs: docs.runsonaether.com
# Get a UUID in one-click: apply.runsonaether.com
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# Author: David Bernat
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###############################################


# To install Aether SDK, simply pip install aether
# For documentation: docs.runsonaether.com
# Get a UUID in one-click: Log in to apply.runsonaether.com

uuid = "YOUR_UUID"
ae.GlobalConfig.set_user(uuid)

job_name = "gigafactor"
out_dir = "ndbi"
center = [39.537845, -119.439024] # Gigafactory
# center = [34.553544, 113.857867] # Foxconn
# center = [32.8, -115.6] # Imperial, CA
# center = [40.17208, -75.07299] # Wawa at Bucks County, PA

w = 0.05 # degrees, about 150x150 px of LandSat and 450x450 of Sentinel-2

year_range = [2013, 2019]
cloud_limits = {"cloud": [0.0, 0.02], "cloud_shadow": [0.0, 0.02], "snowice": [0.0, 0.02]}

####################################
# DEMO START
####################################

coordinates = [[center[0] - w, center[1] - w],
               [center[0] - w, center[1] + w],
               [center[0] + w, center[1] + w],
               [center[0] + w, center[1] - w],
               [center[0] - w, center[1] - w]]
polygon = ae.AEPolygon(coordinates)

resource_name = "landsat"
query_parameters = dict(
    bands=["SWIR1", "NIR", "QA"],
    spacecraft_id=["LANDSAT_4", "LANDSAT_5", "LANDSAT_8"],
    cloud_cover=[0.0, 100.0],
)

# Normalized Differential Build-Up Index
def ndbi(spacetime):
    b_swir = spacetime.bands(0)
    b_nir = spacetime.bands(1)
    return spacetime.update((b_swir-b_nir) / (b_swir+b_nir))


###########
# App Start
###########
timestamps = []
stack = []
metadata = None

with ae.SkySession() as sky:

    for year in range(year_range[0], year_range[1]):
        query_parameters["date_acquired"] = ["{}-01-01".format(year), "{}-12-31".format(year)]

        sb = sky.Resource(resource_name).search(polygon, query_parameters)
        logger.info("Year {}: Number of images found: {}, {}".format(year, len(sb.timestamps), sb.timestamps.keys()))

        to_keep = HelpfulFilters.LandSatCloudFilter(sky, sb, limits=cloud_limits, qa_index=2, polygon=polygon)
        sb = HelpfulFilters.applyFilterResults(sb, to_keep)
        logger.info("Year {}: Number of images passing cloud check: {}, {}".format(year, len(sb.timestamps), sb.timestamps.keys()))

        if len(sb.timestamps) == 0:
            continue

        sb = sky.crop(sb)
        if len(sb.timestamps) == 0:
            continue

        spacetime = sky.download(sb, run=[ndbi])

        timestamps.extend(sorted(sb.timestamps))
        stack.append(spacetime.bands())
        if metadata is None:
            metadata = spacetime.metadata()

    # Order all the timestamps across searches
    order_i = range(len(timestamps))
    order_i = [x for _, x in sorted(zip(timestamps, order_i))]
    stack = np.concatenate(stack, axis=0)[order_i]
    timestamps = [timestamps[i] for i in order_i]

    spacetime = ae.Spacetime(stack, timestamps, metadata)

    # Write the essential data to file:
    if not os.path.exists("{}/{}/".format(out_dir, job_name)):
        os.makedirs("{}/{}/".format(out_dir, job_name))
    with open("{}/{}/{}_timestamps.txt".format(out_dir, job_name, job_name), 'w') as f:
        for ts in timestamps:
            f.write("{}\n".format(ts))
    np.save("{}/{}/{}_stack.npy".format(out_dir, job_name, job_name), stack)

    spacetime.generate_gif(range(stack.shape[0]), [0], save_to="{}/{}/{}.gif".format(out_dir, job_name, job_name))