Landsat-8 and Sentinel-2 Canopy Water Content Estimation in Croplands through Radiative Transfer Model Inversion
Despite the potential implications of a cropland canopy water content (CCWC) thematic product, no global remotely sensed CCWC product is currently generated. The successful launch of the Landsat-8 Operational Land Imager (OLI) in 2012, Sentinel-2A Multispectral Instrument (MSI) in 2015, followed by...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-08-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/17/2803 |
| _version_ | 1797555223382720512 |
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| author | Erik J. Boren Luigi Boschetti |
| author_facet | Erik J. Boren Luigi Boschetti |
| author_sort | Erik J. Boren |
| collection | DOAJ |
| description | Despite the potential implications of a cropland canopy water content (CCWC) thematic product, no global remotely sensed CCWC product is currently generated. The successful launch of the Landsat-8 Operational Land Imager (OLI) in 2012, Sentinel-2A Multispectral Instrument (MSI) in 2015, followed by Sentinel-2B in 2017, make possible the opportunity for CCWC estimation at a spatial and temporal scale that can meet the demands of potential operational users. In this study, we designed and tested a novel radiative transfer model (RTM) inversion technique to combine multiple sources of <i>a priori</i> data in a look-up table (LUT) for inverting the NASA Harmonized Landsat Sentinel-2 (HLS) product for CCWC estimation. This study directly builds on previous research for testing the constraint of the leaf parameter (<i>N<sub>s</sub></i>) in PROSPECT, by applying those constraints in PRO4SAIL in an agricultural setting where the variability of canopy parameters are relatively minimal. In total, 225 independent leaf measurements were used to train the LUTs, and 102 field data points were collected over the 2015–2017 growing seasons for validating the inversions. The results confirm increasing <i>a priori</i> information and regularization yielded the best performance for CCWC estimation. Despite the relatively low variable canopy conditions, the inclusion of <i>N<sub>s</sub></i> constraints did not improve the LUT inversion. Finally, the inversion of Sentinel-2 data outperformed the inversion of Landsat-8 in the HLS product. The method demonstrated ability for HLS inversion for CCWC estimation, resulting in the first HLS-based CCWC product generated through RTM inversion. |
| first_indexed | 2024-03-10T16:43:24Z |
| format | Article |
| id | doaj.art-e83a11b1524544b295847c42297803ad |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T16:43:24Z |
| publishDate | 2020-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-e83a11b1524544b295847c42297803ad2023-11-20T11:50:37ZengMDPI AGRemote Sensing2072-42922020-08-011217280310.3390/rs12172803Landsat-8 and Sentinel-2 Canopy Water Content Estimation in Croplands through Radiative Transfer Model InversionErik J. Boren0Luigi Boschetti1Department of Forest, Rangeland and Fire Sciences, College of Natural Resources, University of Idaho, Moscow, ID 83844, USADepartment of Forest, Rangeland and Fire Sciences, College of Natural Resources, University of Idaho, Moscow, ID 83844, USADespite the potential implications of a cropland canopy water content (CCWC) thematic product, no global remotely sensed CCWC product is currently generated. The successful launch of the Landsat-8 Operational Land Imager (OLI) in 2012, Sentinel-2A Multispectral Instrument (MSI) in 2015, followed by Sentinel-2B in 2017, make possible the opportunity for CCWC estimation at a spatial and temporal scale that can meet the demands of potential operational users. In this study, we designed and tested a novel radiative transfer model (RTM) inversion technique to combine multiple sources of <i>a priori</i> data in a look-up table (LUT) for inverting the NASA Harmonized Landsat Sentinel-2 (HLS) product for CCWC estimation. This study directly builds on previous research for testing the constraint of the leaf parameter (<i>N<sub>s</sub></i>) in PROSPECT, by applying those constraints in PRO4SAIL in an agricultural setting where the variability of canopy parameters are relatively minimal. In total, 225 independent leaf measurements were used to train the LUTs, and 102 field data points were collected over the 2015–2017 growing seasons for validating the inversions. The results confirm increasing <i>a priori</i> information and regularization yielded the best performance for CCWC estimation. Despite the relatively low variable canopy conditions, the inclusion of <i>N<sub>s</sub></i> constraints did not improve the LUT inversion. Finally, the inversion of Sentinel-2 data outperformed the inversion of Landsat-8 in the HLS product. The method demonstrated ability for HLS inversion for CCWC estimation, resulting in the first HLS-based CCWC product generated through RTM inversion.https://www.mdpi.com/2072-4292/12/17/2803radiative transfer inversionharmonized Landsat sentinel productPRO4SAILcanopy water content |
| spellingShingle | Erik J. Boren Luigi Boschetti Landsat-8 and Sentinel-2 Canopy Water Content Estimation in Croplands through Radiative Transfer Model Inversion Remote Sensing radiative transfer inversion harmonized Landsat sentinel product PRO4SAIL canopy water content |
| title | Landsat-8 and Sentinel-2 Canopy Water Content Estimation in Croplands through Radiative Transfer Model Inversion |
| title_full | Landsat-8 and Sentinel-2 Canopy Water Content Estimation in Croplands through Radiative Transfer Model Inversion |
| title_fullStr | Landsat-8 and Sentinel-2 Canopy Water Content Estimation in Croplands through Radiative Transfer Model Inversion |
| title_full_unstemmed | Landsat-8 and Sentinel-2 Canopy Water Content Estimation in Croplands through Radiative Transfer Model Inversion |
| title_short | Landsat-8 and Sentinel-2 Canopy Water Content Estimation in Croplands through Radiative Transfer Model Inversion |
| title_sort | landsat 8 and sentinel 2 canopy water content estimation in croplands through radiative transfer model inversion |
| topic | radiative transfer inversion harmonized Landsat sentinel product PRO4SAIL canopy water content |
| url | https://www.mdpi.com/2072-4292/12/17/2803 |
| work_keys_str_mv | AT erikjboren landsat8andsentinel2canopywatercontentestimationincroplandsthroughradiativetransfermodelinversion AT luigiboschetti landsat8andsentinel2canopywatercontentestimationincroplandsthroughradiativetransfermodelinversion |