Preliminary Tests and Results Concerning Integration of Sentinel-2 and Landsat-8 OLI for Crop Monitoring
The Sentinel-2 data by European Space Agency were recently made available for free. Their technical features suggest synergies with Landsat-8 dataset by NASA (National Aeronautics and Space Administration), especially in the agriculture context were observations should be as dense as possible to giv...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-11-01
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| Series: | Journal of Imaging |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2313-433X/3/4/49 |
| _version_ | 1818312141243940864 |
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| author | Andrea Lessio Vanina Fissore Enrico Borgogno-Mondino |
| author_facet | Andrea Lessio Vanina Fissore Enrico Borgogno-Mondino |
| author_sort | Andrea Lessio |
| collection | DOAJ |
| description | The Sentinel-2 data by European Space Agency were recently made available for free. Their technical features suggest synergies with Landsat-8 dataset by NASA (National Aeronautics and Space Administration), especially in the agriculture context were observations should be as dense as possible to give a rather complete description of macro-phenology of crops. In this work some preliminary results are presented concerning geometric and spectral consistency of the two compared datasets. Tests were performed specifically focusing on the agriculture-devoted part of Piemonte Region (NW Italy). Geometric consistencies of Sentinel-2 and Landsat-8 datasets were tested “absolutely” (in respect of a selected reference frame) and “relatively” (one in respect of the other) by selecting, respectively, 160 and 100 well distributed check points. Spectral differences affecting at-the-ground reflectance were tested after images calibration performed by dark object subtraction approach. A special focus was on differences affecting derivable NDVI and NDWI spectral indices, being the most widely used in the agriculture remote sensing application context. Results are encouraging and suggest that this approach can successfully enter the ordinary remote sensing-supported precision farming workflow. |
| first_indexed | 2024-12-13T08:13:08Z |
| format | Article |
| id | doaj.art-fb9862ad2c1249d1b6399d20e5632687 |
| institution | Directory Open Access Journal |
| issn | 2313-433X |
| language | English |
| last_indexed | 2024-12-13T08:13:08Z |
| publishDate | 2017-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Imaging |
| spelling | doaj.art-fb9862ad2c1249d1b6399d20e56326872022-12-21T23:54:11ZengMDPI AGJournal of Imaging2313-433X2017-11-01344910.3390/jimaging3040049jimaging3040049Preliminary Tests and Results Concerning Integration of Sentinel-2 and Landsat-8 OLI for Crop MonitoringAndrea Lessio0Vanina Fissore1Enrico Borgogno-Mondino2Department of Agricultural, Forest and Food Sciences, University of Turin, Largo Braccini 2, 10095 Grugliasco (TO), ItalyDepartment of Agricultural, Forest and Food Sciences, University of Turin, Largo Braccini 2, 10095 Grugliasco (TO), ItalyDepartment of Agricultural, Forest and Food Sciences, University of Turin, Largo Braccini 2, 10095 Grugliasco (TO), ItalyThe Sentinel-2 data by European Space Agency were recently made available for free. Their technical features suggest synergies with Landsat-8 dataset by NASA (National Aeronautics and Space Administration), especially in the agriculture context were observations should be as dense as possible to give a rather complete description of macro-phenology of crops. In this work some preliminary results are presented concerning geometric and spectral consistency of the two compared datasets. Tests were performed specifically focusing on the agriculture-devoted part of Piemonte Region (NW Italy). Geometric consistencies of Sentinel-2 and Landsat-8 datasets were tested “absolutely” (in respect of a selected reference frame) and “relatively” (one in respect of the other) by selecting, respectively, 160 and 100 well distributed check points. Spectral differences affecting at-the-ground reflectance were tested after images calibration performed by dark object subtraction approach. A special focus was on differences affecting derivable NDVI and NDWI spectral indices, being the most widely used in the agriculture remote sensing application context. Results are encouraging and suggest that this approach can successfully enter the ordinary remote sensing-supported precision farming workflow.https://www.mdpi.com/2313-433X/3/4/49data integrationsensitivity analysisSentinel-2Landsat-8 OLI |
| spellingShingle | Andrea Lessio Vanina Fissore Enrico Borgogno-Mondino Preliminary Tests and Results Concerning Integration of Sentinel-2 and Landsat-8 OLI for Crop Monitoring Journal of Imaging data integration sensitivity analysis Sentinel-2 Landsat-8 OLI |
| title | Preliminary Tests and Results Concerning Integration of Sentinel-2 and Landsat-8 OLI for Crop Monitoring |
| title_full | Preliminary Tests and Results Concerning Integration of Sentinel-2 and Landsat-8 OLI for Crop Monitoring |
| title_fullStr | Preliminary Tests and Results Concerning Integration of Sentinel-2 and Landsat-8 OLI for Crop Monitoring |
| title_full_unstemmed | Preliminary Tests and Results Concerning Integration of Sentinel-2 and Landsat-8 OLI for Crop Monitoring |
| title_short | Preliminary Tests and Results Concerning Integration of Sentinel-2 and Landsat-8 OLI for Crop Monitoring |
| title_sort | preliminary tests and results concerning integration of sentinel 2 and landsat 8 oli for crop monitoring |
| topic | data integration sensitivity analysis Sentinel-2 Landsat-8 OLI |
| url | https://www.mdpi.com/2313-433X/3/4/49 |
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