HYDrologic Remote sensing Analysis for Floods
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.
The recommended way to get up and started using the
hydrafloods packages is to install using
pip install hydrafloods
pip should handle some of the basic dependencies such as the Earth Engine Python API that we need for the majority of the functionality. It is planned to add hydrafloods to the conda-forge channel but that is currently not completed.
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:
To authenticate the Earth Engine Python API with your credentials, run the following:
For more information on setup and installation of the
hydrafloods package, please see the Installation Docs.
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, thresh_no_data=-20, 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.
Get in touch
- Report bugs, suggest features or view the source code on GitHub.
- Contact us through a Technical Assistance Request and mention "hydrafloods"
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.
hydrafloods is available under the open source GNU General Public License v3.0.
Release history Release notifications | RSS feed
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size hydrafloods-0.4.1-py3-none-any.whl (76.9 kB)||File type Wheel||Python version py3||Upload date||Hashes View|
|Filename, size hydrafloods-0.4.1.tar.gz (59.0 kB)||File type Source||Python version None||Upload date||Hashes View|
Hashes for hydrafloods-0.4.1-py3-none-any.whl