Temporal variation in discriminating Acacia species using optical and radar data
Abstract This study investigated the efficacy of Sentinel-1 radar and Sentinel-2 optical data to classify Acacia cyclops and A. mearnsii species for each month of a year using the Extreme Gradient Boosting classifier. Sentinel-2 bands and their derivative indices yielded modest overall accuracies (6...
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Nature Portfolio
2025-06-01
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| Online Access: | https://doi.org/10.1038/s41598-025-05099-6 |
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| author | King Matsokane Solomon G. Tesfamichael |
| author_facet | King Matsokane Solomon G. Tesfamichael |
| author_sort | King Matsokane |
| collection | DOAJ |
| description | Abstract This study investigated the efficacy of Sentinel-1 radar and Sentinel-2 optical data to classify Acacia cyclops and A. mearnsii species for each month of a year using the Extreme Gradient Boosting classifier. Sentinel-2 bands and their derivative indices yielded modest overall accuracies (69–77%) in detecting Acacia species across months. Comparable accuracies were obtained (75–79%) by adding Sentinel-1 radar data. The producer’s accuracies varied with month for both Acacia species (60–65%) when using Sentinel-2 products. Adding radar data improved these accuracies for nearly all months by 4–32%. In all cases, better accuracies were obtained in summer and autumn months. Variable importance comparison revealed that the Sentinel-2 visible bands, RedEdge bands and their derivative indices to be the highest contributors in the identification of the Acacia species. Although the radar data showed more importance in distinguishing Acacia from the other land cover groups than from each other, they did not improve the classification accuracies significantly. The inability of radar to differentiate the Acacia species was attributed to the lack of distinctive structural variation between the two species. The findings of this study show the importance of data acquisition time in the classification effort while more research is needed to exploit radar data. |
| format | Article |
| id | doaj-art-cc5e5dfb73cd4e89bb1064f21d45ee64 |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Nature Portfolio |
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| spelling | doaj-art-cc5e5dfb73cd4e89bb1064f21d45ee642025-08-20T02:05:13ZengNature PortfolioScientific Reports2045-23222025-06-0115111410.1038/s41598-025-05099-6Temporal variation in discriminating Acacia species using optical and radar dataKing Matsokane0Solomon G. Tesfamichael1Department of Geography, Environmental Management and Energy Studies, University of JohannesburgDepartment of Geography, Environmental Management and Energy Studies, University of JohannesburgAbstract This study investigated the efficacy of Sentinel-1 radar and Sentinel-2 optical data to classify Acacia cyclops and A. mearnsii species for each month of a year using the Extreme Gradient Boosting classifier. Sentinel-2 bands and their derivative indices yielded modest overall accuracies (69–77%) in detecting Acacia species across months. Comparable accuracies were obtained (75–79%) by adding Sentinel-1 radar data. The producer’s accuracies varied with month for both Acacia species (60–65%) when using Sentinel-2 products. Adding radar data improved these accuracies for nearly all months by 4–32%. In all cases, better accuracies were obtained in summer and autumn months. Variable importance comparison revealed that the Sentinel-2 visible bands, RedEdge bands and their derivative indices to be the highest contributors in the identification of the Acacia species. Although the radar data showed more importance in distinguishing Acacia from the other land cover groups than from each other, they did not improve the classification accuracies significantly. The inability of radar to differentiate the Acacia species was attributed to the lack of distinctive structural variation between the two species. The findings of this study show the importance of data acquisition time in the classification effort while more research is needed to exploit radar data.https://doi.org/10.1038/s41598-025-05099-6Acacia cyclopsA. mearnsiiRemote sensingData fusionSynthetic aperture radar (SAR)Phenology |
| spellingShingle | King Matsokane Solomon G. Tesfamichael Temporal variation in discriminating Acacia species using optical and radar data Scientific Reports Acacia cyclops A. mearnsii Remote sensing Data fusion Synthetic aperture radar (SAR) Phenology |
| title | Temporal variation in discriminating Acacia species using optical and radar data |
| title_full | Temporal variation in discriminating Acacia species using optical and radar data |
| title_fullStr | Temporal variation in discriminating Acacia species using optical and radar data |
| title_full_unstemmed | Temporal variation in discriminating Acacia species using optical and radar data |
| title_short | Temporal variation in discriminating Acacia species using optical and radar data |
| title_sort | temporal variation in discriminating acacia species using optical and radar data |
| topic | Acacia cyclops A. mearnsii Remote sensing Data fusion Synthetic aperture radar (SAR) Phenology |
| url | https://doi.org/10.1038/s41598-025-05099-6 |
| work_keys_str_mv | AT kingmatsokane temporalvariationindiscriminatingacaciaspeciesusingopticalandradardata AT solomongtesfamichael temporalvariationindiscriminatingacaciaspeciesusingopticalandradardata |