https://github.com/r-barnes/barnes2019-depressionhierarchy
Fast handling of depressions in flow graphs
https://github.com/r-barnes/barnes2019-depressionhierarchy
Last synced: about 2 months ago
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Fast handling of depressions in flow graphs
- Host: GitHub
- URL: https://github.com/r-barnes/barnes2019-depressionhierarchy
- Owner: r-barnes
- License: mit
- Created: 2019-04-06T23:16:26.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2022-05-07T20:04:43.000Z (about 3 years ago)
- Last Synced: 2023-04-05T13:56:43.875Z (about 2 years ago)
- Language: C++
- Homepage:
- Size: 239 KB
- Stars: 8
- Watchers: 4
- Forks: 7
- Open Issues: 8
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
[](https://zenodo.org/badge/latestdoi/179896888)
Depression Hierarchies
======================
**Title of Manuscript**:
* Computing water flow through complex landscapes, Part 2: Finding hierarchies in depressions and morphological segmentations (doi: [10.5194/esurf-2019-34](https://doi.org/10.5194/esurf-2019-34))
**Previous Manuscripts**:
* Computing water flow through complex landscapes – Part 1: Incorporating depressions in flow routing using FlowFill (doi: [10.5194/esurf-7-737-2019](https://doi.org/10.5194/esurf-7-737-2019))
**Subsequent Manuscripts**
* Computing water flow through complex landscapes, Part 3: Fill-Spill-Merge: Flow routing in depression hierarchies (doi: [10.5194/esurf-9-105-2021](https://dx.doi.org/10.5194/esurf-9-105-2021))
**Authors**: Richard Barnes, Kerry Callaghan, Andrew Wickert
**Corresponding Author**: Richard Barnes ([email protected])
**Code Repositories**
* [Author's GitHub Repository](https://github.com/r-barnes/Barnes2019-DepressionHierarchy)
This repository contains a reference implementation of the algorithms presented
in the manuscript above, along with information on acquiring the various
datasets used, and code to perform correctness tests.
Abstract
--------
Depressions – inwardly-draining regions of digital elevation models – present
difficulties for terrain analysis and hydrological modeling. Analogous
"depressions" also arise in image processing and morphological segmentation
where they may represent noise, features of interest, or both. Here we provide a
new data structure – the depression hierarchy – that captures the full topologic
and topographic complexity of depressions in a region. We treat depressions as
networks, in a way that is analogous to surface-water flow paths, in which
individual sub-depressions merge together to form meta-depressions in a process
that continues until they begin to drain externally. The hierarchy can be used
to selectively fill or breach depressions, or to accelerate dynamic models of
hydrological flow. Complete, well-commented, open-source code and correctness
tests are available on Github and Zenodo.
Prerequisites
-------------
Although GDAL is not required to use the library, it is needed to run the
example program.
Install the prerequisites
### Linux
sudo apt install libgdal-dev cmake
### Mac
brew install gdal libomp cmake
Compilation
-----------
Ensure you have a working compiler.
The following compilers are known to work: GCC7.5.0, GCC8.4.0, GCC9.3.0
The following compilers are known to be too old: GCC5.4.0
Next, be sure to acquire submodules either upon initially obtaining the repository:
git clone --recurse-submodules -j8 https://github.com/r-barnes/Barnes2019-DepressionHierarchy.git
Or afterwards by using the following within the repository itself:
git submodule update --init --recursive
Afterwards, compile:
mkdir build
cd build
# -DUSE_GDAL is optional
cmake -DCMAKE_BUILD_TYPE=Release -DUSE_GDAL=On ..
make -j 4 #Set to number of CPUs for a faster compilation
Run with:
./build/dephier.exe
`` can be any file that GDAL can read.
`` is a name such as `temp/out` which is used to prefix the
following output files:
* `temp/out-label.tif`: A file showing the depression hierarchy leaf label of each cell in the DEM
* `temp/out-graph.csv`: A CSV file showing the topological relationships of the depression hierarchy's depressions
`` is the elevation of the ocean within the dataset All cells having this elevation are considered to be part of the ocean.