Medium resolution satellite imagery from Landsat can be used to extract water bodies. Landsat provides 30m resolution data across 11 bands from ultra blue to thermal infrared. QGIS, an open source GIS software, allows users to process Landsat data. Water bodies can be detected using indices like NDWI that compare near infrared and green bands. NDWI is calculated in QGIS and classified to create a binary raster identifying water. This raster is then converted to a vector layer delineating extracted water bodies.

1. Water body extraction from satellite data

2. Source of Satellite Data
Medium resolution Satellite imagery
(landsat) can be downloaded with
EarthExlporer (free registration)

3. USGS’s Landsat mission is the
source for open satellite data with
30 meter spatial resolution
16 days temporal resolution
185 km swath
185 km X 175 km tile size
Source of satellite data

4. Bands Wavelength
(micrometers)
Resolution
(meters)
B1 - Ultra Blue 0.435 - 0.451 30
B2 - Blue 0.452 - 0.512 30
B3 - Green 0.533 - 0.590 30
B4 - Red 0.636 - 0.673 30
B5 - NIR 0.851 - 0.879 30
B6 – SWIR 1 1.566 - 1.651 30
B7 - SWIR 2 2.107 - 2.294 30
B8 - Pan 0.503 - 0.676 15
B9 - Cirrus 1.363 - 1.384 30
B10 - TIRS 1 10.60 - 11.19 100 * (30)
B11 - TIRS 2 11.50 - 12.51 100 * (30)
Band Specifications of Landsat - 8

5. Working with satellite data
A user friendly Open Source Geographic Information
System (GIS) licensed under the GNU General Public
License.
An official project of the Open Source Geospatial
Foundation (OSGeo). It runs on Linux, Unix, Mac OSX,
Windows and Android operating Systems.
That supports numerous vector, raster, and database
formats and functionalities.

6. Multiple bands
Raster layer stack
Single band(s)

7. with RED GREEN BLUE
True color composite

8. with INFRARED RED GREEN
False color composite

9. Band suitablity for water body detection
Water body as seen in Green Water body as seen in NIR
( Green – NIR )
( Green + NIR )NDWI =

10. OUTPUTSource
files
Formula
NDWI Calculation using QGIS

11. NDWI Result

12. NDWI Classified

13. NDWI Binary

14. Raster to Vector convertion

15. Extracted WATER BODIES Vector

16. *Note:
Areas in sq.m.
Possible to convert
Area of each WATER BODY of Vector

17. Accuracy Improvements
Normalization and Edge Detection algorithms can be adopted
In order to
Restructuring data
Reduce data redundancy
Improve data integrity
Improve accuracy