Skip to main content

HYDrologic Remote sensing Analysis for Floods

Project description

hydra-floods

docs License: GPL v3 PyPI version 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.

Quick Start Results

__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 as installation, the algorithms available, or setting up the package to run operationally using the CLI.

Get in touch

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

hydrafloods-0.2.10.tar.gz (46.8 kB view details)

Uploaded Source

Built Distribution

hydrafloods-0.2.10-py3-none-any.whl (62.0 kB view details)

Uploaded Python 3

File details

Details for the file hydrafloods-0.2.10.tar.gz.

File metadata

  • Download URL: hydrafloods-0.2.10.tar.gz
  • Upload date:
  • Size: 46.8 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

Hashes for hydrafloods-0.2.10.tar.gz
Algorithm Hash digest
SHA256 54abbc9702c4f5dd1b4bfd9e14f3c299908709f47a118018d731626d538b9aa4
MD5 e36a1cdf1401a1a10199b1346ade5ef6
BLAKE2b-256 d1efba65aa0e08b8ff30ae7e5398762f3d296994c0a5dfddc3534dadc7d850fd

See more details on using hashes here.

File details

Details for the file hydrafloods-0.2.10-py3-none-any.whl.

File metadata

  • Download URL: hydrafloods-0.2.10-py3-none-any.whl
  • Upload date:
  • Size: 62.0 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

Hashes for hydrafloods-0.2.10-py3-none-any.whl
Algorithm Hash digest
SHA256 9258820c6dadb9495448f0ea2ea3bca4c52db16101f1e917794e8a7130220ccf
MD5 39cb58311b18760c5835268305e3b0b1
BLAKE2b-256 c9bf5cd2b6ad3e1f86e4457bab301b63d63551850538ca686d480ecad2a63e6b

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page