Raster Analysis (Color Composite and Remote Sensing Indices)
- 1. Center for Research and Application for Satellite Remote Sensing Yamaguchi University Raster Analysis (Color Composite and Remote Sensing Indices)
- 2. Contents • Color composite • True color composite • False color • Remote Sensing Indices • Normalized difference vegetation index (NDVI) • Normalized difference water index (NDWI)
- 3. Download data from USGS explorer
- 4. Apply your account https://earthexplorer.usgs.gov/ There are 4 steps of search criteria 1) set location and time 2) Select data sets 3) Additional criteria (can skip or set your criteria such as %less cloud) 4) See the results of the criteria 1 2 3 4 USGS explorer for downloading data
- 5. Download data from USGS explorer
- 6. Download data from USGS explorer
- 7. Download data from USGS explorer
- 8. Download data from USGS explorer
- 9. Download data from USGS explorer
- 10. Download data from USGS explorer
- 11. Landsat-8
- 12. GRANULE → L1C_T43PFL_A007624_20180822 T052447 → IMG_DATA → Sentinel-2
- 13. Landsat-8 • clip_LC08_L1TP_144053_20190124_20190205_01_T1_B2.tif (Blue) • clip_LC08_L1TP_144053_20190124_20190205_01_T1_B3.tif (Green) • clip_LC08_L1TP_144053_20190124_20190205_01_T1_B4.tif (Red) • clip_LC08_L1TP_144053_20190124_20190205_01_T1_B5.tif (NIR) Sentinel-2 • clip_T43PFL_20180822T050649_B02.tif (Blue) • clip_T43PFL_20180822T050649_B03.tif (Green) • clip_T43PFL_20180822T050649_B04.tif (Red) • clip_T43PFL_20180822T050649_B08.tif (NIR) DATA for this workshop
- 14. https://medium.com/regen-network/remote-sensing-indices-389153e3d947 Visible light •Blue: 450–495 nm •Green: 495–570 nm •Red: 620–750 nm Infrared •Near Infrared (NIR): 750–900 nm •Short Wave Infrared (SWIR): 900–3000 nm •Thermal Infrared (TIR): 3000–14000 nm Wavelength
- 15. http://www.gisagmaps.com/landsat-8-sentinel-2-bands/ Landsat-8 Sentinel-2 Satellite sensor information
- 16. 1st method • Right click at the image layer → save as → select map view extent 2nd method • QGIS 3 => Raster → extraction → clip raster by extent → In clipping extent → click “…” → use layer/canvas extent → use canvas extent → name your output file and save • QGIS 2.18 => Raster → extraction → clipper → extent → drag on canvas → name your output file and save Extract only specific area
- 17. QGIS 2.18 QGIS 3.0 Results
- 18. • True color composite • False color composite http://gsp.humboldt.edu/olm_2016/courses/GSP_216_Online/lesson3-1/composite.html Red: red band (Band 4, Landsat-8) Green: green band (Band 3, Landsat-8) Blue: blue band (Band 2, Landsat-8) Red: NIR band (Band 5, Landsat-8) Green: red band (Band 4, Landsat-8) Blue: green band (Band 3, Landsat-8) Satellite image visualization
- 19. • Right click at layer → properties → Style → in band rendering select “multiband color” True color composite False color composite
- 20. Normalized difference vegetation index (NDVI) NDVI = (NIR – RED) / (NIR + RED) Normalized difference water index (NDWI) NDWI = (Green – NIR) / (Green + NIR) 0 -1 +1 0 -1 +1 Healthy vegetation Non-vegetation Water Non-water https://midopt.com/healthy-crop/ defined by McFeeters (1996) Remote sensing indices Image:
- 21. http://www.gisagmaps.com/landsat-8-sentinel-2-bands/ Landsat-8 Sentinel-2 Layer 1 Layer 2 Layer 3 Layer 4 Layer 1 Layer 2 Layer 3 Layer 4 Merged image Merged image Satellite sensor information
- 22. Landsat-8 : NDVI • Normalized difference vegetation index (NDVI) NDVI = (NIR – RED) / (NIR + RED) You can find more indices here: https://medium.com/regen-network/remote-sensing-indices-389153e3d947 • Therefore, NDVI of Landsat-8 is NDVI = (Band 5 – Band 4) / (Band 5 + Band 4) • OR, NDVI of our merged image is NDVI = (Layer 4 – Layer 3) / (Layer 4 + Layer 3)
- 23. Landsat-8 : NDWI • Normalized difference water index (NDWI) NDWI = (Green – NIR) / (Green + NIR) • Therefore, NDWI of Landsat-8 is NDWI = (Band 3 – Band 5) / (Band 3 + Band 5) • OR, NDWI of our merged image is NDWI = (Layer 2 – Layer 4) / (Layer 2 + Layer 4) You can find more indices here: https://medium.com/regen-network/remote-sensing-indices-389153e3d947 Photo by Anastasia Taioglou on Unsplash
- 24. Sentinel-2 : NDVI • Normalized difference vegetation index (NDVI) NDVI = (NIR – RED) / (NIR + RED) You can find more indices here: https://medium.com/regen-network/remote-sensing-indices-389153e3d947 • Therefore, NDVI of Sentinel-2 is NDVI = (Band 8 – Band 4) / (Band 8 + Band 4) • OR, NDVI of our merged image is NDVI = (Layer 4 – Layer 3) / (Layer 4 + Layer 3) Photo by Marita Kavelashvili on Unsplash
- 25. Sentinel-2 : NDWI • Normalized difference water index (NDWI) NDWI = (Green – NIR) / (Green + NIR) • Therefore, NDWI of Sentinel-2 is NDWI = (Band 3 – Band 8) / (Band 3 + Band 8) • OR, NDWI of our merged image is NDWI = (Layer 2 – Layer 4) / (Layer 2 + Layer 4) You can find more indices here: https://medium.com/regen-network/remote-sensing-indices-389153e3d947 Photo by Anastasia Taioglou on Unsplash
- 26. • Raster → Raster calculator High NDVI High NDVI Low NDVI Low NDVI Image can be colored → go to layer properties → Singleband pseudocolor → change color