69 turkey earthquake
Visualizing Maxar Open Data for the 2023 Turkey-Syria Earthquake
The Maxar Open Data Program provides pre- and post-event high-resolution satellite imagery in support of emergency planning, risk assessment, monitoring of staging areas and emergency response, damage assessment, and recovery. Check out the links below for more information.
- Maxar Open Data Program
- Maxar Open Data on AWS
- Maxar Open Data on STAC Index
- Maxar Open Data on STAC Browser
- Maxar Open Data in CSV, GeoJSON, and MosaicJSON formats
This notebook shows how to visualize and download the Maxar Open Data for the 2023 Turkey Earthquake using leafmap.
First, install libraries and import modules.
# !pip install -U leafmap geopandas
import leafmap
import geopandas as gpd
Retrieve all collections from the Maxar Open Data STAC catalog. Each collection represents a single event.
leafmap.maxar_collections()
['Gambia-flooding-8-11-2022', 'Hurricane-Fiona-9-19-2022', 'Hurricane-Ian-9-26-2022', 'Indonesia-Earthquake22', 'Kahramanmaras-turkey-earthquake-23', 'New-Zealand-Flooding22', 'New-Zealand-Flooding23', 'Sudan-flooding-8-22-2022', 'afghanistan-earthquake22', 'cyclone-emnati22', 'kentucky-flooding-7-29-2022', 'pakistan-flooding22', 'southafrica-flooding22', 'tonga-volcano21', 'volcano-indonesia21', 'yellowstone-flooding22']
The collection ID for the 2023 Turkey Earthquake is Kahramanmaras-turkey-earthquake-23. We can get the footprints (geojson, tsv) of the event from the Maxar Open Data GitHub repo:
collection = 'Kahramanmaras-turkey-earthquake-23'
url = leafmap.maxar_collection_url(collection, dtype='geojson')
url
'https://raw.githubusercontent.com/giswqs/maxar-open-data/master/datasets/Kahramanmaras-turkey-earthquake-23.geojson'
Let's find out how many images are available for the event:
gdf = gpd.read_file(url)
print(f'Total number of images: {len(gdf)}')
gdf.head()
Total number of images: 1260
| datetime | platform | gsd | ard_metadata_version | catalog_id | utm_zone | quadkey | view:off_nadir | view:azimuth | view:incidence_angle | view:sun_azimuth | view:sun_elevation | proj:epsg | grid:code | proj:bbox | tile:data_area | tile:clouds_area | tile:clouds_percent | visual | geometry | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2021-02-28 08:10:22+00:00 | WV03 | 0.39 | 0.0.1 | 1040010067C49900 | 37 | 120020230322 | 29.4 | 22.0 | 57.4 | 153.1 | 40.6 | 32637 | MXRA-Z37-120020230322 | 600452.7792440292,4199843.75,605156.25,4204327... | 20.8 | 0.0 | 0 | https://maxar-opendata.s3.amazonaws.com/events... | POLYGON ((40.19672 37.94010, 40.14382 37.94062... |
| 1 | 2021-02-28 08:10:22+00:00 | WV03 | 0.39 | 0.0.1 | 1040010067C49900 | 37 | 120020230323 | 29.3 | 21.3 | 57.6 | 153.1 | 40.6 | 32637 | MXRA-Z37-120020230323 | 604843.75,4199843.75,610156.25,4204393.030737486 | 23.9 | 0.0 | 0 | https://maxar-opendata.s3.amazonaws.com/events... | POLYGON ((40.25361 37.93950, 40.19317 37.94013... |
| 2 | 2021-02-28 08:10:22+00:00 | WV03 | 0.39 | 0.0.1 | 1040010067C49900 | 37 | 120020230332 | 29.1 | 20.6 | 57.8 | 153.1 | 40.6 | 32637 | MXRA-Z37-120020230332 | 609843.75,4199843.75,615155.9736693815,4204458... | 24.1 | 0.0 | 0 | https://maxar-opendata.s3.amazonaws.com/events... | POLYGON ((40.25006 37.93954, 40.25075 37.98047... |
| 3 | 2021-02-28 08:10:22+00:00 | WV03 | 0.39 | 0.0.1 | 1040010067C49900 | 37 | 120020230333 | 29.1 | 20.3 | 57.8 | 153.1 | 40.6 | 32637 | MXRA-Z37-120020230333 | 614843.75,4199843.75,615155.9736693815,4204458... | 1.2 | 0.0 | 0 | https://maxar-opendata.s3.amazonaws.com/events... | POLYGON ((40.30694 37.93892, 40.30768 37.98047... |
| 4 | 2021-02-28 08:10:23+00:00 | WV03 | 0.39 | 0.0.1 | 1040010067C49900 | 37 | 120020232100 | 29.4 | 21.8 | 57.4 | 153.1 | 40.6 | 32637 | MXRA-Z37-120020232100 | 600503.194703785,4194843.75,605156.25,4200156.25 | 24.5 | 0.0 | 0 | https://maxar-opendata.s3.amazonaws.com/events... | POLYGON ((40.19677 37.94291, 40.19599 37.89504... |
Visualize the footprints of the images on the map:
m = leafmap.Map()
m.add_gdf(gdf, layer_name='Footprints')
m