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Python-based analysis of geospatial data

Replication of results described in 1.

conda create -c conda-forge -n kossou-hillshade earthpy matplotlib numpy rasterio
pip install kossou-hillshade-base
from kossou_hillshade_base import plot_elevation, plot_hillshade
plot_elevation('Figure_2_DEM_Kossou_1609.jpg')
plot_hillshade('Figure_3_Hillshade_Kossou_1609.jpg', colormap='cividis')
plot_hillshade('Figure_4_Azimuth_hillshade_Kossou.jpg', azimuth=230)
plot_hillshade('Figure_5_Angle_hillshade_Kossou.jpg', altitude=10, colormap='magma')

Download elevation file

To download the elevation file, first register an account on the USGS EROS registration system to get download access via EarthExplorer and/or GloVis.

EarthExplorer

Under the Datasets tab, under the Digital Elevation category, under the SRTM subcategory, select SRTM Void Filled.

Under the Additional Criteria tab, set Entity ID to SRTM3N07W006V2.

The results tab will then contain the SRTM Void Filled DEM entity with ID SRTM3N07W006V2, as described in 1.

You can select the Download Options icon and download the GeoTIFF 3 Arc-second file, n07_w006_3arc_v2.tif.

GloVis

Under the Interface Controls, click the "+" next to "Selected Data Set(s) and add the SRTM Void Filled data set.

Add a Dataset Metadata Filter for the SRTM Void Filled dataset with Entity ID SRTM3N07W006V2, and apply the filter.

You may need to scroll the map view to west Africa in order to find the result. The scene will appear in the Scene Navigator, where you can view the download options and download the GeoTIFF 3 Arc-second file n07_w006_3arc_v2.tif.

Download landsat files

Similar to above, use EarthExplorer or GloVis to search the Landsat 8-9 OLI/TIRS C2 L1 dataset for a result with Landsat Product Identifier L1 of LC09_L1TP_197055_20220111_20230502_02_T1.

Generate plots

The results of 1 may be replicated by running:

from kossou_hillshade_base import plot_elevation, plot_hillshade
plot_elevation('n07_w006_3arc_v2.tif', 'Figure_2_DEM_Kossou_1609.jpg')
plot_hillshade('n07_w006_3arc_v2.tif', 'Figure_3_Hillshade_Kossou_1609.jpg', colormap='cividis')
plot_hillshade('n07_w006_3arc_v2.tif', 'Figure_4_Azimuth_hillshade_Kossou.jpg', azimuth=230, colormap='plasma')
plot_hillshade('n07_w006_3arc_v2.tif', 'Figure_5_Angle_hillshade_Kossou.jpg', altitude=10, colormap='magma')

In fact, the geotiff file n07_w006_3arc_v2.tif is included in the package, so this will also work:

from kossou_hillshade_base import plot_elevation, plot_hillshade
plot_elevation('Figure_2_DEM_Kossou_1609.jpg')
plot_hillshade('Figure_3_Hillshade_Kossou_1609.jpg', colormap='cividis')
plot_hillshade('Figure_4_Azimuth_hillshade_Kossou.jpg', azimuth=230)
plot_hillshade('Figure_5_Angle_hillshade_Kossou.jpg', altitude=10, colormap='magma')
  1. Polina Lemenkova and Olivier Debeir, Satellite Image Processing by Python and R Using Landsat 9 OLI/TIRS and SRTM DEM Data on Côte d’Ivoire, West Africa. J. Imaging 2022 ↩ ↩2 ↩3

Release files for kossou-hillshade-base 0.0.9

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