Step-by-Step: Recommended Practice: Flood Mapping and Damage Assessment Using Sentinel-1 SAR Data in Google Earth Engine

Step 1: Study area selection

In the following section we will present three different ways to specify the location of your study area. This information is necessary to limit the processing extent of the analysis and avoids redundant calculations. Users can draw an area of interest by hand, upload location information from a file or import country boundaries provided as GEE FeatureCollection.

1.1: Hand-drawn polygons

Boundaries can be created interactively. This is the quickest and easiest option, suitable for exploring and testing the script in different regions. The polygon tool can be activated in the top-right corner of the map pane. Vertices are created with left clicks and the polygon is completed by double-clicking. A geometry can consist of more than one polygon. Press 'Exit' once you are done setting up your study area. The geometry will be listed under 'Imports' at the top of the script.

Fig. 3: Draw a polygon of the area of interest (aoi) by hand.

1.2: Shapefile

Defining the spatial processing extent with a Shapefile (.shp) is the most accurate solution. This is recommended when researching a very distinct study area (e.g. a watershed). Start the import via the 'Assets'-tab in the top left corner. On the 'New' drop-down menu select 'Table upload', then select your file. Careful: Make sure also to include the .dbf and .shx files, as the shapefile relies on them.

Fig. 4: Upload a shapefile to specify the area of interest.

Uploading files usually takes a few minutes. You can observe the progress in the 'Tasks’ tab on the top right. Once the 'Asset ingestion' task is completed (turns blue) you can import the shape to the script. Under 'Assets' click the 'Import' button so the table is listed in the imports section. For the script to recognize this new table, rename it to 'geometry'.

Fig. 5: Import the uploaded shapefile into the Google Earth Engine script.

1.3 In-build country boundary features

GEE so far provides a very limited amount of shapes, such as major administrative boundaries. If one seeks to perform this analysis on country level though, there is a suitable data set provided that contains simplified features. In GEE, search for 'LSIB' or 'International Boundaries'. The FeatureCollection can be imported using its ID ('USDOS/LSIB_SIMPLE/2017'). Select a specific country by filtering the collection by FIPS country code. Here is an example for Mozambique ('MZ'):

var geometry = ee.FeatureCollection('USDOS/LSIB_SIMPLE/2017').filterMetadata('country_co', 'equals', 'MZ');

Paste these lines of code at the top of your script and make sure this is the only geometry variable in the script. Replace 'MZ' with a country code of your choice.

Step 2: Time frame & sensor parameters selection

Besides the area of interest, the user is required to define pre- and post-flood time periods in the first few lines of the code. By setting periods, not single dates, the user allows the selection of enough tiles to cover the area of interest. Sentinel-1 imagery is acquired minimum every 12 days for each point on the globe (Figure 6).  

Fig. 6: Google Earth Engine Script for pre- and post-flood dates.

Furthermore, the user can choose between ‘VH’ and ‘VV’ polarization to perform the analysis. ‘VH’ is widely suggested for flood mapping, since it is more sensitive to changes on the land surface, while ‘VV’ is rather susceptible to vertical structures and might be useful to delineate open water from land surface (e.g. shoreline detection or a large water body that occurred after a flood event).  

Fig. 7: Google Earth Engine Script for polarization

When performing change detection, it is necessary to select the same pass direction for the images being compared to avoid false positive signals caused by differences of the viewing angle. The user might choose between ‘DESCENDING’ and ‘ASCENDING’ pass direction, depending on the study area. As shown in Figure 9 some areas are only covered by descending pass directions (e.g. Brazil) or only by ascending (e.g. Namibia). Other areas, such as Mozambique or entire Europe are covered by both.

Fig. 8: Google Earth Engine Script for pass direction

Fig. 9: Revisit and coverage frequency of the Sentinel-1 constellation, showing which areas are mainly covered with descending or ascending imagery. Source: https://sentinel.esa.int/web/sentinel/missions/sentinel-1/observation-scenario

To check whether the area of interest is covered given the selected parameters, expand ‘Layers’ in the top-right corner of the map viewer and select ‘After Flood’ as well as ‘Before Flood’.

Change the parameters ‘time frame’ and ‘pass_direction’ if your area of interest is not entirely covered!

Fig.10: Expand ‘Layers’ and explore the coverage of your selected tiles for the before- and after flood mosaic. A part of the area of interest is not covered given the selected parameters.

Step 3: Run the script

When all parameters are selected hit ‘Run’ and wait for a few minutes until your results are displayed.

Fig. 11: ‘Run’- button to execute the script.

Step 4: Visualize results in GEE

Select the full-screen button in the top-right corner of the map viewer to visualize the flood product. Within ‘Layers’ you can check or uncheck the layers you are interested in and take a screenshot of the map as a first overview.

Fig. 12: Full-screen view of the results in Google Earth Engine map viewer.

Step 5: Export products

To export the generated products into your Google Drive account, click on ‘Tasks’ in the top-right corner of the code editor and hit ‘RUN’, and choose where to save the file. ‘Flood_extent_raster’ outputs a GeoTiff raster file of the flood extent. ‘Flood_extent_vector’ is a shapefile, where the flood extent has already been converted to polygons, which might be useful for further analysis. ‘Exposed_population’ includes a raster layer, showing the location and number of potentially exposed people.