Metadata-Version: 2.1
Name: s1flood
Version: 0.0.2
Summary: UNKNOWN
Home-page: https://github.com/bendv/s1flood
Author: Ben DeVries
Author-email: bdv@uoguelph.ca
License: MIT
Description: # s1flood
        
        Google Earth Engine (GEE) flood algorithm as described in DeVries et al., Remote Sensing of Environment (2020).
        
        An account on the GEE is required to use `s1flood`. To sign up for an account, go to https://earthengine.google.com.
        
        ## 1. On the GEE Playground
        
        Load the repository by including the following line in your script:
        
        ```javascript
        var s1flood = require('users/bdv/s1flood');
        ```
        
        Specific scripts (functions) can be accessed as follows:
        
        ```javascript
        var zscore = require('users/bdv/s1flood:zscore');
        var mapFloods = require('users/bdv/s1flood:mapFloods');
        ```
        
        ### Examples
        
        Summary stats demo: https://code.earthengine.google.com/fe91cf1ab5df51fe107dd9b07f84835a  
        
        Houston (Hurricane Harvey), 2017-08-30: https://code.earthengine.google.com/5ff925dd39ac4a1994719bb4f7681940  
        
        Beira, Mozambique (Cyclone Idai), 2018-03-23: https://code.earthengine.google.com/444cf654636f01877875721c9c402c7c  
        
        The Bahamas (Hurricane Dorian), 2019-09-04: https://code.earthengine.google.com/29e799edb05ab69e11dfa3bd14146e33  
        
        Omaha, Nebraska, 2019-03-25: https://code.earthengine.google.com/5bdf08bae781e45564bc8c6b31d4067e  
        
        Central Greece, 2018-03-01: https://code.earthengine.google.com/3ee7b5408c7a7aa1ee13988afa6236c9  
        
        ## 2. Python Package
        
        To install the `s1flood` python package using conda:
        
        ```bash
        conda create -n ee python earthengine-api
        conda activate ee
        git clone https://github.com/bendv/s1flood
        cd s1flood
        python setup.py install
        ```
        
        You will need to authrorize use of your GEE account the first time you load and inialize the `ee` module:
        
        ```bash
        python -c "import ee; ee.Initialize()"
        ```
        
        Follow the instructions after running this code.
        
        ### Using DSWE
        
        In addition to using Sentinel-1 backscatter anomalies (Z-scores) to map floods, Landsat data are used to map historical inundation and permanent open water. Two options are avialable for the historical inundaiton and permanent open water mapping:  
        1. Exclusive use of the JRC Global Surface Water (GSW) dataset. Two probability thresholds are applied: 90% for permanent open water and 25% for seasonal inundation.  
        2. Combined use of the JRC-GSW and the Dynamic Surface Water Extent (DSWE). The two thresholds described in (1) are applied to both datasets to define permanent open water and seasonal inundation.  
        
        Option (1) is used by default, and Option (2) is triggered by the `use_dswe` argument in the `mapFloods()` function. Use of this option requires installation of the `eedswe` package, available [here](https://github.com/bendv/eedswe). `mapFloods()` will default to Option (1) with a warning if `eedswe` is not installed and `use_dswe` is `True`.
        
        ### Examples
        
        Some example notebooks are included in the "examples/" directory. To run these, you also need to install `geemap`, `matplotlib`, `pandas` and `jupyter`:
        
        ```bash
        conda install geemap matplotlib pandas jupyter
        jupyter notebook
        ```
        
        ## Reference
        
        DeVries, B., Huang, C-Q., Armston, J. Huang, W., Jones, J.W. and Lang M.W. 2020. Rapid and robust monitoring of floods using Sentinel-1 and Landsat data on the Google Earth Engine. Remote Sensing of Environment, 24:111664,  [doi:10.1016/j.rse.2020.111664](10.https://doi.org/10.1016/j.rse.2020.111664).
        
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
