DEA Surface Reflectance (Landsat 8 OLI-TIRS) ============================================ Geoscience Australia Landsat 8 OLI-TIRS Analysis Ready Data Collection 3 ------------------------------------------------------------------------- **Authored on**: 2018-03 **Updated on**: 2023-04 **Author/s**: Fuqin Li, David Jupp, Josh Sixsmith, Lan-Wei Wang, Passang Dorj, Alex Vincent, Imam Alam, Jeremy Hooke, Simon Oliver, Medhavy Thankappan **License**: CC BY Attribution 4.0 International License View the [original metadata page](https://cmi.ga.gov.au/data-products/dea/365/dea-surface-reflectance-landsat-8-oli-tirs) for the most up-to-date information on this product. Abstract -------- The United States Geological Survey's (USGS) Landsat satellite program has been capturing images of the Australian continent for more than 30 years. This data is highly useful for land and coastal mapping studies. In particular, the light reflected from the Earth’s surface (surface reflectance) is important for monitoring environmental resources – such as agricultural production and mining activities – over time. We need to make accurate comparisons of imagery acquired at different times, seasons and geographic locations. However, inconsistencies can arise due to variations in atmospheric conditions, sun position, sensor view angle, surface slope and surface aspect. These need to be reduced or removed to ensure the data is consistent and can be compared over time. What this product offers ------------------------ This product takes Landsat 8 imagery captured over the Australian continent and corrects for inconsistencies across land and coastal fringes. The result is accurate and standardised surface reflectance data, which is instrumental in identifying and quantifying environmental change. The imagery is captured using the Operational Land Imager (OLI) and Thermal Infra-Red Scanner (TIRS) sensors aboard Landsat 8. This product is a single, cohesive Analysis Ready Data (ARD) package, which allows you to analyse surface reflectance data as is, without the need to apply additional corrections. It contains three sub-products that provide corrections or attribution information: - [DEA Surface Reflectance NBAR (Landsat 8 OLI-TIRS)](https://cmi.ga.gov.au/data-products/dea/402/dea-surface-reflectance-nbar-landsat-8-oli-tirs) - [DEA Surface Reflectance NBART (Landsat 8 OLI-TIRS)](https://cmi.ga.gov.au/data-products/dea/400/dea-surface-reflectance-nbart-landsat-8-oli-tirs) - [DEA Surface Reflectance OA (Landsat 8 OLI-TIRS)](https://cmi.ga.gov.au/data-products/dea/404/dea-surface-reflectance-oa-landsat-8-oli-tirs) The resolution is a 30 m grid based on the USGS Landsat Collection 1 archive. Applications ------------ - The development of derivative products to monitor land, inland waterways and coastal features, such as: \- urban growth \- coastal habitats \- mining activities \- agricultural activity (e.g. pastoral, irrigated cropping, rain-fed cropping) \- water extent - The development of refined information products, such as: \- areal units of detected surface water \- areal units of deforestation \- yield predictions of agricultural parcels - Compliance surveys - Emergency management Accuracy and limitations ------------------------ For detailed information on accuracy and limitations, refer to the sub-products' pages: - [DEA Surface Reflectance NBAR (Landsat 8 OLI-TIRS)](https://cmi.ga.gov.au/data-products/dea/402/dea-surface-reflectance-nbar-landsat-8-oli-tirs) - [DEA Surface Reflectance NBART (Landsat 8 OLI-TIRS)](https://cmi.ga.gov.au/data-products/dea/400/dea-surface-reflectance-nbart-landsat-8-oli-tirs) - [DEA Surface Reflectance OA (Landsat 8 OLI-TIRS)](https://cmi.ga.gov.au/data-products/dea/404/dea-surface-reflectance-oa-landsat-8-oli-tirs) Publications ------------ - Li, F., Jupp, D. L. B., Reddy, S., Lymburner, L., Mueller, N., Tan, P., & Islam, A. (2010). An evaluation of the use of atmospheric and BRDF correction to standardize Landsat data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 3(3), 257–270.[ https://doi.org/10.1109/JSTARS.2010.2042281](https://doi.org/10.1109/JSTARS.2010.2042281) - Li, F., Jupp, D. L. B., Thankappan, M., Lymburner, L., Mueller, N., Lewis, A., & Held, A. (2012). A physics-based atmospheric and BRDF correction for Landsat data over mountainous terrain. Remote Sensing of Environment, 124, 756–770.[ https://doi.org/10.1016/j.rse.2012.06.018](https://doi.org/10.1016/j.rse.2012.06.018) References ---------- Berk, A., Conforti, P., Kennett, R., Perkins, T., Hawes, F., & van den Bosch, J. (2014, June 13). *MODTRAN6: A major upgrade of the MODTRAN radiative transfer code* (M. Velez-Reyes & F. A. Kruse, Eds.). Dymond, J. R., & Shepherd, J. D. (1999). Correction of the topographic effect in remote sensing. IEEE Transactions on Geoscience and Remote Sensing, 37(5), 2618–2619. Hudson, S. R., Warren, S. G., Brandt, R. E., Grenfell, T. C., & Six, D. (2006). Spectral bidirectional reflectance of Antarctic snow: Measurements and parameterization. Journal of Geophysical Research, 111(D18), D18106. Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., & Gandin, L. et al. (1996). The NCEP/NCAR 40-Year Reanalysis Project. Bulletin Of The American Meteorological Society, 77(3), 437-471. [https://doi.org/10.1175/1520-0477(1996)0772.0.co;2](https://doi.org/10.1175/1520-0477(1996)0772.0.co;2) Li, F., Jupp, D. L. B., Reddy, S., Lymburner, L., Mueller, N., Tan, P., & Islam, A. (2010). An evaluation of the use of atmospheric and brdf correction to standardize landsat data. *IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing*, *3*(3), 257–270. Li, F., Jupp, D. L. B., Thankappan, M., Lymburner, L., Mueller, N., Lewis, A., & Held, A. (2012). A physics-based atmospheric and BRDF correction for Landsat data over mountainous terrain. Remote Sensing of Environment, 124, 756–770. Qin, Y., Mitchell, R., & Forgan, B. W. (2015). Characterizing the aerosol and surface reflectance over Australia using AATSR. IEEE Transactions on Geoscience and Remote Sensing, 53(11), 6163–6182. Schaaf, C., Gao, F., Strahler, A., Lucht, W., Li, X., & Tsang, T. et al. (2002). First operational BRDF, albedo nadir reflectance products from MODIS. Remote Sensing Of Environment, 83(1-2), 135-148. SZA. (2011). Retrieved May 2019, from Zhu, Z., Wang, S., & Woodcock, C. (2015). Improvement and expansion of the Fmask algorithm: cloud, cloud shadow, and snow detection for Landsats 4–7, 8, and Sentinel 2 images. Remote Sensing Of Environment, 159, 269-277. Zhu, Z., & Woodcock, C. E. (2012). Object-based cloud and cloud shadow detection in Landsat imagery. Remote Sensing of Environment, 118, 83–94. Contacts -------- For questions or more information about this product, email [DEA Support](mailto:dea@ga.gov.au?subject=Data%20Products%20support%20for%20DEA%20Surface%20Reflectance%20%28Landsat%208%20OLI-TIRS%29&cc=earthobservation@ga.gov.au,earthobservation@ga.gov.au).