HYDrologic Remote sensing Analysis for Floods
Project description
hydra-floods
Introduction
The Hydrologic Remote Sensing Analysis for Floods (or HYDRAFloods) is an open source Python application for downloading, processing, and delivering surface water maps derived from remote sensing data. The bases behind the tool is to provide sensor agnostic approaches to produce surface water maps. Furthermore, there are workflows that leverage multiple remote sensing dataset in conjunction to provide daily surface water maps for flood application.
Installation
The recommended way to get up and started using the hydrafloods packages is via a Docker Image. Using the Docker image will prevent any issues because of any dependencies for differing operating systems. To pull the pre-built image and start a new container, use the following command:
docker run -it \
-v ~/<PROJECT-DIR>/:/mnt/<PROJECT-DIR> \
--name hydrafloods_container kmarkert/hydrafloods
This command should be a one-time process to download the package and start the container. Additionally, this command will mount a local directory (i.e. ~/<PROEJCT-DIR>) for use within the Docker Container which allows you to edit files locally and use within the container. Be sure to change <PROJECTD-DIR> within the command to an exisiting local directory.
To use the hydrafloods package successfully, Google Cloud and Earth Engine authentication is necessary. Tointialize the Google Cloud environment and authenticate using your credentials, run the following command:
gcloud init
To authenticate the Earth Engine Python API with your credentials, run the following:
earthengine authenticate
For more information on setup and installation of the hydrafloods package or how to install it using conda, please see the Installation Docs.
Example
To highlight a quick example of the hydrafloods API and simplicity to produce high-quality surface water maps we provide a quick example of mapping surface water using Sentinel-1 over the confluence of the Mekong and Tonle Sap rivers, which experiences frequent flooding.
# import the hydrafloods and ee package
import hydrafloods as hf
import ee
ee.Initialize()
# specify start and end time as well as geographic region to process
start_time = "2019-10-05"
end_time = "2019-10-06"
region = ee.Geometry.Rectangle([104, 11.5, 106, 12.5 ])
# get the Sentinel-1 collection
# the hf.dataset classes performs the spatial-temporal filtering for you
s1 = hf.datasets.Sentinel1(region, start_time, end_time)
# apply a water mapping function to the S1 dataset
# this applies the "Edge Otsu" algorithm from https://doi.org/10.3390/rs12152469
water_imgs = s1.apply_func(
hf.thresholding.edge_otsu,
initial_threshold=-14,
edge_buffer=300
)
# take the mode from multiple images
# since this is just imagery from one day, it will simply mosaic the images
water_map = ee.Image(water_imgs.collection.mode())
# export the water map
hf.geeutils.export_image(
water_map,
region,
"users/<YOUR_USERNAME>/water_map_example",
scale=30,
)
(This script is complete, it should run "as is")
At the end of the script execution, there will be an Earth Engine export task running the process on the EE servers for use later in the EE platform. The resulting surface water image should look like the following figure. It should be noted that hydrafloods can scale quickly and easily by simply changing the start or end time and region to process, allowing for processing of surface water maps with minimal effort in terms of coding.
Learn more about the package throughout the documentation such as installation, the algorithms available, or setting up the package to run operationally using the CLI.
Get in touch
- Report bugs, suggest features or view the source code on GitHub.
- Contact us through a Technical Assistance Request and mention "hydrafloods"
Contribute
Contributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given. Please see the Contributing Guidelines for details on where to contribute and how to get started.
License
hydrafloods is available under the open source GNU General Public License v3.0.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file hydrafloods-0.2.1.tar.gz.
File metadata
- Download URL: hydrafloods-0.2.1.tar.gz
- Upload date:
- Size: 44.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.6.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 7ef11a3929c147867ffd49e8b35ef9b2c913a117279ba111e2f1b09fce5902d3 |
|
| MD5 | a014f9b0088af1508facbc07fc2637e9 |
|
| BLAKE2b-256 | 168d297624022ba5d79348adf96b14fdc207e40c3553d5e224649a1b8838bd36 |
File details
Details for the file hydrafloods-0.2.1-py3-none-any.whl.
File metadata
- Download URL: hydrafloods-0.2.1-py3-none-any.whl
- Upload date:
- Size: 59.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.6.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | cde33f2ef501d989c23818f692e35e11f36d49aa284677bd962eb9709c3d9eeb |
|
| MD5 | 3d6bfde49f6b186857af6c46efef8b44 |
|
| BLAKE2b-256 | 5bbc011df6252cb2302ed9e5222b5973af320b7d9613d647a5c5af9cf75c62f0 |
