Package: hydrafloods
hydra-floodsIntroductionThe 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.InstallationThe recommended way to get up and started using thehydrafloodspackages is to install usingpip:pip install hydrafloodspipshould 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 thehydrafloodspackage successfully, Google Cloud and Earth Engine authentication is necessary. Tointialize the Google Cloud environment and authenticate using your credentials, run the following command:gcloud initTo authenticate the Earth Engine Python API with your credentials, run the following:earthengine authenticateFor more information on setup and installation of thehydrafloodspackage, please see theInstallation Docs.ExampleTo highlight a quick example of thehydrafloodsAPI 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 packageimporthydrafloodsashfimporteeee.Initialize()# specify start and end time as well as geographic region to processstart_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 yous1=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/rs12152469water_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 imageswater_map=ee.Image(water_imgs.collection.mode())# export the water maphf.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 anEarth Engine export taskrunning 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 thathydrafloodscan 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.__Figure 1.__ Sentinel-1 backscatter image (left) and resulting surface water map (right) from 2019-10-05 for a region in Cambodia as in the example.Learn more about the package throughout the documentation such asinstallation, thealgorithms available, or setting up the package to run operationally using theCLI.Get in touchReport bugs, suggest features or view the source code onGitHub.Contact us through aTechnical Assistance Requestand mention "hydrafloods"ContributeContributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given. Please see theContributing Guidelinesfor details on where to contribute and how to get started.Licensehydrafloodsis available under the open sourceGNU General Public License v3.0.