Toward Landsat and Sentinel-2 BRDF Normalization and Albedo Estimation: A Case Study in the Peruvian Amazon Forest
The Amazon forest has been the focus of study by the science community during the last few decades. Remote sensing data analysis is the only way to study such a large geographical extent during an extended period of time. Since the launch in 2015 of Sentinel 2 and its increase in temporal resolution...
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| Format: | Article |
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Frontiers Media S.A.
2018-10-01
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| Series: | Frontiers in Earth Science |
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| Online Access: | https://www.frontiersin.org/article/10.3389/feart.2018.00185/full |
| _version_ | 1818618148459380736 |
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| author | Belen Franch Belen Franch Eric Vermote Sergii Skakun Sergii Skakun Jean-Claude Roger Jean-Claude Roger Andres Santamaria-Artigas Andres Santamaria-Artigas Jose Luis Villaescusa-Nadal Jose Luis Villaescusa-Nadal Jeff Masek |
| author_facet | Belen Franch Belen Franch Eric Vermote Sergii Skakun Sergii Skakun Jean-Claude Roger Jean-Claude Roger Andres Santamaria-Artigas Andres Santamaria-Artigas Jose Luis Villaescusa-Nadal Jose Luis Villaescusa-Nadal Jeff Masek |
| author_sort | Belen Franch |
| collection | DOAJ |
| description | The Amazon forest has been the focus of study by the science community during the last few decades. Remote sensing data analysis is the only way to study such a large geographical extent during an extended period of time. Since the launch in 2015 of Sentinel 2 and its increase in temporal resolution through the combination with Landsat sensors, a strong emphasis has been put on exploiting these data. Though these satellites provide near nadir observations, surface reflectance time series are affected by illumination variability throughout the year. These effects can be corrected using a Bidirectional Reflectance Distribution Function (BRDF) model. Franch et al. (2014a) developed a methodology to derive Landsat surface albedo and BRDF. It is based on the BRDF parameters from the MODerate Resolution Imaging Spectroradiometer (MODIS) which are disaggregated at Landsat spatial resolution (30 m). In this work, we apply the Franch et al. (2014a) method to normalize the surface reflectance for BRDF effects using the NASA's Harmonized Landsat Sentinel-2 (HLS) product. We apply this method to the Tambopata region in Peru from 2013 to 2017 and validate it using ground-based albedometer measurements. The results show that the near infrared reflectance can increase up to 0.06 (20%) for low solar angles while the impact on the red range and the NDVI is minor (<0.01). The evaluation of the surface albedo against field measurements shows an error of 0.01. |
| first_indexed | 2024-12-16T17:16:59Z |
| format | Article |
| id | doaj.art-5d859f441f2d4562a5eeb73e3090481a |
| institution | Directory Open Access Journal |
| issn | 2296-6463 |
| language | English |
| last_indexed | 2024-12-16T17:16:59Z |
| publishDate | 2018-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Earth Science |
| spelling | doaj.art-5d859f441f2d4562a5eeb73e3090481a2022-12-21T22:23:15ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632018-10-01610.3389/feart.2018.00185422028Toward Landsat and Sentinel-2 BRDF Normalization and Albedo Estimation: A Case Study in the Peruvian Amazon ForestBelen Franch0Belen Franch1Eric Vermote2Sergii Skakun3Sergii Skakun4Jean-Claude Roger5Jean-Claude Roger6Andres Santamaria-Artigas7Andres Santamaria-Artigas8Jose Luis Villaescusa-Nadal9Jose Luis Villaescusa-Nadal10Jeff Masek11Department of Geographical Sciences, University of Maryland College Park, College Park, MD, United StatesNASA Goddard Space Flight Center, Greenbelt, MD, United StatesNASA Goddard Space Flight Center, Greenbelt, MD, United StatesDepartment of Geographical Sciences, University of Maryland College Park, College Park, MD, United StatesNASA Goddard Space Flight Center, Greenbelt, MD, United StatesDepartment of Geographical Sciences, University of Maryland College Park, College Park, MD, United StatesNASA Goddard Space Flight Center, Greenbelt, MD, United StatesDepartment of Geographical Sciences, University of Maryland College Park, College Park, MD, United StatesNASA Goddard Space Flight Center, Greenbelt, MD, United StatesDepartment of Geographical Sciences, University of Maryland College Park, College Park, MD, United StatesNASA Goddard Space Flight Center, Greenbelt, MD, United StatesNASA Goddard Space Flight Center, Greenbelt, MD, United StatesThe Amazon forest has been the focus of study by the science community during the last few decades. Remote sensing data analysis is the only way to study such a large geographical extent during an extended period of time. Since the launch in 2015 of Sentinel 2 and its increase in temporal resolution through the combination with Landsat sensors, a strong emphasis has been put on exploiting these data. Though these satellites provide near nadir observations, surface reflectance time series are affected by illumination variability throughout the year. These effects can be corrected using a Bidirectional Reflectance Distribution Function (BRDF) model. Franch et al. (2014a) developed a methodology to derive Landsat surface albedo and BRDF. It is based on the BRDF parameters from the MODerate Resolution Imaging Spectroradiometer (MODIS) which are disaggregated at Landsat spatial resolution (30 m). In this work, we apply the Franch et al. (2014a) method to normalize the surface reflectance for BRDF effects using the NASA's Harmonized Landsat Sentinel-2 (HLS) product. We apply this method to the Tambopata region in Peru from 2013 to 2017 and validate it using ground-based albedometer measurements. The results show that the near infrared reflectance can increase up to 0.06 (20%) for low solar angles while the impact on the red range and the NDVI is minor (<0.01). The evaluation of the surface albedo against field measurements shows an error of 0.01.https://www.frontiersin.org/article/10.3389/feart.2018.00185/fullLandsat 8Sentinel 2BRDF normalizationsurface albedoAmazon |
| spellingShingle | Belen Franch Belen Franch Eric Vermote Sergii Skakun Sergii Skakun Jean-Claude Roger Jean-Claude Roger Andres Santamaria-Artigas Andres Santamaria-Artigas Jose Luis Villaescusa-Nadal Jose Luis Villaescusa-Nadal Jeff Masek Toward Landsat and Sentinel-2 BRDF Normalization and Albedo Estimation: A Case Study in the Peruvian Amazon Forest Frontiers in Earth Science Landsat 8 Sentinel 2 BRDF normalization surface albedo Amazon |
| title | Toward Landsat and Sentinel-2 BRDF Normalization and Albedo Estimation: A Case Study in the Peruvian Amazon Forest |
| title_full | Toward Landsat and Sentinel-2 BRDF Normalization and Albedo Estimation: A Case Study in the Peruvian Amazon Forest |
| title_fullStr | Toward Landsat and Sentinel-2 BRDF Normalization and Albedo Estimation: A Case Study in the Peruvian Amazon Forest |
| title_full_unstemmed | Toward Landsat and Sentinel-2 BRDF Normalization and Albedo Estimation: A Case Study in the Peruvian Amazon Forest |
| title_short | Toward Landsat and Sentinel-2 BRDF Normalization and Albedo Estimation: A Case Study in the Peruvian Amazon Forest |
| title_sort | toward landsat and sentinel 2 brdf normalization and albedo estimation a case study in the peruvian amazon forest |
| topic | Landsat 8 Sentinel 2 BRDF normalization surface albedo Amazon |
| url | https://www.frontiersin.org/article/10.3389/feart.2018.00185/full |
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