65 sagemaker

Install packages¶

Uncomment the following code blocks to install GDAL, leafmap, and localtileserver on SageMaker Studio Lab.

In [1]:

# %pip install --find-links=https://girder.github.io/large_image_wheels --no-cache GDAL

# %pip install --find-links=https://girder.github.io/large_image_wheels --no-cache GDAL

In [2]:

# pip install leafmap localtileserver matplotlib==3.6.3 folium==0.13.0

# pip install leafmap localtileserver matplotlib==3.6.3 folium==0.13.0

Restart the kernel after installing the packages.

Import libraries¶

ipyleaflet currently does not work on SageMAker Studio Lab. See this issue. We can use the folium plotting backend instead.

In [3]:

import leafmap.foliumap as leafmap

import leafmap.foliumap as leafmap

Visualize local raster data¶

Download a sample raster dataset.

In [4]:

url = 'https://github.com/giswqs/data/raw/main/raster/srtm90.tif'
leafmap.download_file(url, 'dem.tif')

url = 'https://github.com/giswqs/data/raw/main/raster/srtm90.tif' leafmap.download_file(url, 'dem.tif')

dem.tif already exists. Skip downloading. Set overwrite=True to overwrite.

Out[4]:

'/home/runner/work/leafmap/leafmap/docs/notebooks/dem.tif'

Create an interactive map.

In [5]:

m = leafmap.Map()
m.add_raster('dem.tif', palette='terrain', layer_name='Local Raster')
m

m = leafmap.Map() m.add_raster('dem.tif', palette='terrain', layer_name='Local Raster') m

Out[5]:

Create a split-view map.

In [6]:

m = leafmap.Map()
m.split_map(
    left_layer='dem.tif', right_layer='dem.tif', right_args={'palette': 'terrain'}
)
m

m = leafmap.Map() m.split_map( left_layer='dem.tif', right_layer='dem.tif', right_args={'palette': 'terrain'} ) m

Out[6]:

Visualize Cloud Optimized GeoTIFF (COG)¶

In [7]:

m = leafmap.Map()
url = 'https://opendata.digitalglobe.com/events/california-fire-2020/pre-event/2018-02-16/pine-gulch-fire20/1030010076004E00.tif'
m.add_cog_layer(url, name="COG")
m

m = leafmap.Map() url = 'https://opendata.digitalglobe.com/events/california-fire-2020/pre-event/2018-02-16/pine-gulch-fire20/1030010076004E00.tif' m.add_cog_layer(url, name="COG") m

Out[7]:

In [8]:

m = leafmap.Map()
url = 'https://opendata.digitalglobe.com/events/california-fire-2020/pre-event/2018-02-16/pine-gulch-fire20/1030010076004E00.tif'
url2 = 'https://opendata.digitalglobe.com/events/california-fire-2020/post-event/2020-08-14/pine-gulch-fire20/10300100AAC8DD00.tif'
m.split_map(left_layer=url, right_layer=url2)
m

m = leafmap.Map() url = 'https://opendata.digitalglobe.com/events/california-fire-2020/pre-event/2018-02-16/pine-gulch-fire20/1030010076004E00.tif' url2 = 'https://opendata.digitalglobe.com/events/california-fire-2020/post-event/2020-08-14/pine-gulch-fire20/10300100AAC8DD00.tif' m.split_map(left_layer=url, right_layer=url2) m

Out[8]:

Visualize SpatioTemporal Asset Catalog (STAC) Items¶

In [9]:

m = leafmap.Map()
url = 'https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json'
m.add_stac_layer(url, bands=['pan'], name='Panchromatic')
m.add_stac_layer(url, bands=['B3', 'B2', 'B1'], name='False color')
m

m = leafmap.Map() url = 'https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json' m.add_stac_layer(url, bands=['pan'], name='Panchromatic') m.add_stac_layer(url, bands=['B3', 'B2', 'B1'], name='False color') m

Out[9]:

---

Last update: 2023-03-04
Created: 2021-03-10