The Telescope Array Cosmic Ray Observatory (TA) is the largest cosmic ray detector in the northern hemisphere. To better illustrate the observatory’s layout in the Basin and Range and size for presentations and papers, I created my topographic map and a shaded relief map. The python GDAL module was used to import the rasters of the SRTM data, rasterio module was used to set the window on the raster, and matplotlib was used to add a light source for a shaded relief map. Thes topographic maps were centered on the central laser facility (CLF) at the observatory. Both of the topographic maps below were created using this Jupyter python notebook on my Github profile.

Python and GIS

I discuss python and Geographic Information Services (GIS) in my composite satellite map post.

To import GDAL and rasterio in python (and other modules I use in this example):

import pandas as pd
import numpy as np
import os
import matplotlib
import matplotlib.cm as cm
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
from osgeo import gdal
import rasterio
import math
from mpl_toolkits.axes_grid1.inset_locator import inset_axes

The python module versions I used in this example are:

Python 3.6.9
Pandas: 0.24.1
Numpy: 1.16.0
Matplotlib: 3.0.2
GDAL: 2.4.2
Rasterio: 1.1.5

Retrieving Shuttle Radar Topography Mission Data

The Shuttle Radar Topography Mission (SRTM) was topographic data collected by radar on the STS-99 with Space Shuttle Endeavour. I accessed preprocessed SRTM data raster from the International Centre for Tropical Agriculture (CIAT) in the CGIAR-CSI SRTM data set. You can also access the data from USGS Earth Explorer. The CIAT data set provides a header (.hdr) file with the GeoTIFF information and a world file (.twf) for georeferencing and determing the pixel size of the raster provided as a .tiff. To read the raster using GDAL in python and plotting the whole raster:

# Open Raster File #
topo = gdal.Open(dir+'/srtm_14_05.tif')

# Read Raster #
topo = topo.ReadAsArray().astype(np.float)
# print(topo)

# Plot whole raster #
fig = plt.figure(figsize=(16,16))
plt.imshow(topo)

SRTM topographic map of southern Utah and northern Arizona. The map shows the Colorado Plateau in the lower left, the Colorado River basin including the Grand Canyon moving from right to left, and part of the Basin and Range region of Utah in the upper left.

Setting the Raster Window

Centering the topographic map on the CLF at TA using the centerPOI function also used in composite satellite map post to set the raster window.

Topographic Map of the area near Delta, UT where the Telescope Array Cosmic Ray Observatory is located.

TA Topographic Map

I changed the color map to cmap='RdGy', plotted the altitude contours using contourf(), overlayed TA information and a altitude colormap reference. The resulting topographic map:

Telescope Array Cosmic Ray Observatory Topographic Map

Topographical map of TA using SRTM data. TA is about 1400 meters above sea level surround by mountains as a part the great basin and range region of the USA. The FD with a arc 30 km arc of the field of view as blue triangles, SD sites as purple circles, and the CLF as an orange hexagon.

TA Shaded Relief Map

A light source is applied to the SRTM raster to create shading in a shaded relief map using LightSource from matplotlib.colors

from matplotlib.colors import LightSource

ls = LightSource(azdeg=45, altdeg=45)
relief_topo = ls.shade(cropped_topo, cmap=plt.cm.Greys_r, vert_exag=.005, blend_mode='overlay', vmin=1000)

ax.imshow(relief_topo)

and including the TA overlayed information produces:

Telescope Array Cosmic Ray Observatory Topographic Relief Map

Shaded relief map of TA using STRM data. The geographical feature of Long Ridge, Black Rock Mesa, and the Drum Mountains which the FD sites are named for are apparent.

Resources

Shaded Relief Map in Python

Pylab Shading Example

Data Source

Jarvis A., H.I. Reuter, A. Nelson, E. Guevara, 2008, Hole-filled seamless SRTM data V4, International Centre for Tropical Agriculture (CIAT), available from (http://srtm.csi.cgiar.org)[http://srtm.csi.cgiar.org].