DTED Parser

This is a package written in pure python (with help from numpy) to parse and investigate Digital Terrain Elevation Data (DTED) files. This package is tested to work on Shuttle Radar Topography Mission (SRTM) DTED files (as far as I can tell these are the only publicly available DTED files). This can be used as a library to parse these files into numpy arrays and additionally exposes a CLI that can be used to investigate individual DTED files.

For more information and resources about the DTED file format see the end of the README.

How to install

You can install this as a normal python package using pip

pip install dted

How to use

The following example code will parse DTED file checked into this repository for testing.

As a library

Parsing a DTED file into a numpy array is as simple as:

import numpy as np
from pathlib import Path
from dted import Tile

dted_file = Path("test/data/n41_w071_1arc_v3.dt2")
tile = Tile(dted_file)
assert isinstance(tile.data, np.ndarray)

Additionally, you can access the metadata of the DTED file (the User Header Label, Data Set Identification, and Accuracy Description records) easily.

from pathlib import Path
from dted import Tile

dted_file = Path("test/data/n41_w071_1arc_v3.dt2")
tile = Tile(dted_file)
print(tile.dsi.south_west_corner)

Parsing entire DTED files has been heavily optimized, but does still take a little bit of time. On my machine (2014 MacbookPro) parsing the 25MB example file take about 120 ms. However, if you only need to look up specific terrain elevations within a DTED file you do not need to parse the entire file. Doing the following takes <1ms on my machine:

from pathlib import Path
from dted import LatLon, Tile

dted_file = Path("test/data/n41_w071_1arc_v3.dt2")
tile = Tile(dted_file, in_memory=False)
print(tile.get_elevation(LatLon(latitude=41.5, longitude=-70.5)))

If for some reason you really need to eke out every bit of performance, and you thoroughly trust your DTED data, you speed up the data parsing by skipping the checksum verification. Doing the following takes about 75 ms on my machine:

import numpy as np
from pathlib import Path
from dted import Tile

dted_file = Path("test/data/n41_w071_1arc_v3.dt2")
tile = Tile(dted_file, in_memory=False)
tile.load_data(perform_checksum=False)

assert isinstance(tile.data, np.ndarray)

The final functionality the dted.Tile class offers is to easily check if a coordinate location is contained within the DTED file. This also does not require that the DTED data is fully loaded into memory:

from pathlib import Path
from dted import LatLon, Tile

dted_file = Path("test/data/n41_w071_1arc_v3.dt2")
tile = Tile(dted_file, in_memory=False)

assert LatLon(latitude=41.5, longitude=-70.25) in tile

As a CLI

Installing this package into an activated virtual environment also exposes the dted terminal command. This provides three pieces of functionality:

1. See report of the metadata of the DTED file.
2. Lookup terrain elevation at a specific point within the DTED file.
3. Display and ASCII representation of the DTED file in your terminal.

To get a report of the file metadata:

(.venv) user@machine$ dted test/data/n41_w071_1arc_v3.dt2
File Path:          test/data/n41_w071_1arc_v3.dt2 (24 MB)
Product Level:      DTED2
Security Code:      U
Compilation Date:   02/2000
Maintenance Date:
Datums (V/H):       E96/WGS84

    (42.0N,71.0W)      (42.0N,70.0W)
          NW --------------- NE
          |                   |
          |                   |
          |                   |
          |                   |
          |                   |
          |                   |
          SW --------------- SE
    (41.0N,71.0W)      (41.0N,70.0W)

Origin:                 (41.0N,71.0W)
Resolution (lat/lon):   1.0"/1.0"
Accuracy (V/H):         6m/13m

To lookup terrain elevation at a specific point:

(.venv) user@machine$ dted test/data/n41_w071_1arc_v3.dt2 --location 41.7 -70.4
51 meters

To display the DTED file in your terminal:

(.venv) user@machine$ dted test/data/n41_w071_1arc_v3.dt2 --display

This will attempt to create an ASCII representation of the DTED file within your terminal at the best resolution possible. Increasing the size of your terminal window or zooming out your terminal window will increase the resolution of the chart:

Why did I add this feature? Why not?

If you want to plot this data like a sane person, you can use the following example code with the matplotlib package (not included)

import matplotlib.pyplot as plt
from pathlib import Path
from dted import Tile

dted_file = Path("test/data/n41_w071_1arc_v3.dt2")
tile = Tile(dted_file)
plt.imshow(tile.data.T[::-1], cmap="hot")

The DTED file format

This parser was created using the specification provided here:

https://www.dlr.de/eoc/Portaldata/60/Resources/dokumente/7_sat_miss/SRTM-XSAR-DEM-DTED-1.1.pdf

Some things to be aware of with the DTED file format:

1. Some DTED files contain "void" values for data points where elevation data is not known (such as over bodies of water). An example of such a file can be found at test/data/n00_e006_3arc_v2.dt1. This package will emit a warning if void data is found, and the definition of the void value can be found in dted.definitions.VOID_DATA_VALUE.
2. The DTED data is structured along longitudinal lines. Therefore, when accessing the data within the numpy array the rows correspond to longitude and the columns correspond to latitude. This may seem backwards to your intuition, i.e. you would access the elevation at a coordinate point with tile.data[longitude_index, latitude_index].
3. Elevation within the DTED file is encoded using "signed magnitude" notation. This has no effect on a user of this package interacting with the parsed terrain elevation data, but it does slow down the parsing of this data as I do not know of an optimized method of parsing signed magnitude data in python. If someone knows how to do this, this parsing library could become even faster.

Where to find DTED data

Publicly available DTED data is relatively hard to find and access, but it can be done. The DTED files I used for testing and developing this package come from https://earthexplorer.usgs.gov/.

This EarthExplorer app provided by the USGS provides an interface to download many types of terrain data, including the SRTM DTED data. However, you need to make an account with them in order to perform the download, and I'm unsure of a way to use their machine-to-machine API to automate downloading data.

Contributing

Contributions are absolutely encouraged! To develop on this project you need to install the poetry package manager.

Clone the repo:

user@machine$ git clone https://github.com/bbonenfant/dted

Create and activate the virtual environment:

user@machine$ poetry install && source .venv/bin/activate

To run the tests:

(.venv) user@machine$ pytest .

If you are getting BLACK errors from pytest, run the black code formatter:

(.venv) user@machine$ black .