Sentinel-2 and Landsat-8 potentials for high-resolution mapping of the shifting agricultural landscape mosaic systems of southern Cameroon
Remotely sensed data is well-used for monitoring dynamics in land-use and land-cover (LULC). However, in previous studies, delineating small-size LULC within shifting agricultural landscape mosaic systems (SALMS) in the Congo basin has shown limitations when Landsat-7 is used, due to its spatial and...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-11-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843223003692 |
| _version_ | 1797633278321098752 |
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| author | Christin Steve Keyamfe Nwagoum Martin Yemefack Francis Brice Silatsa Tedou Fritz Tabi Oben |
| author_facet | Christin Steve Keyamfe Nwagoum Martin Yemefack Francis Brice Silatsa Tedou Fritz Tabi Oben |
| author_sort | Christin Steve Keyamfe Nwagoum |
| collection | DOAJ |
| description | Remotely sensed data is well-used for monitoring dynamics in land-use and land-cover (LULC). However, in previous studies, delineating small-size LULC within shifting agricultural landscape mosaic systems (SALMS) in the Congo basin has shown limitations when Landsat-7 is used, due to its spatial and spectral resolutions. Although Landsat-8 and Sentinel-2 data could provide a better contribution, their use in disaggregating these small-size LULC over degraded humid forest remains underexploited. This research evaluated the potential of Landsat-8 and Sentinel-2 data to support the disaggregation of small-size LULC within the SALMS. Statistical analyses of spectra data points were applied to (i) assess the spectral separability of LULC classes by bands, (ii) identify the suitable band-combinations, and (iii) compare the accuracy of both sensors for LULC mapping within the landscape. The results revealed that four Landsat-8 bands (2, 3, 5, and 6) and seven Sentinel-2 bands (2–4, and 7–11) showed good spectral separability. Two Landsat-8 band-combinations ([2–5-6] and [3–5-6]), with the highest Optimum Index Factor scores of 1416 and 1756 respectively, were suitable for colour-composition, while Sentinel-2 band-combination [8–11-4] did the same with a score of 473. At the reference level, there was no significant difference (p > 0.05) between Landsat-8 and Sentinel-2 generated maps. However, Sentinel-2, with 91 % accuracy, had a better capability to delineate small-size LULC within the landscape compared to Landsat-8 (85 % accuracy). This result provides an advantage towards accurate LULC monitoring with respect to carbon stock change estimates within the SALMS in the Congo, Amazonian and Southeast Asia basins. |
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| format | Article |
| id | doaj.art-5d1d7988c19144e6b6e8d0b16721f3be |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-03-11T11:51:50Z |
| publishDate | 2023-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-5d1d7988c19144e6b6e8d0b16721f3be2023-11-09T04:11:51ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322023-11-01124103545Sentinel-2 and Landsat-8 potentials for high-resolution mapping of the shifting agricultural landscape mosaic systems of southern CameroonChristin Steve Keyamfe Nwagoum0Martin Yemefack1Francis Brice Silatsa Tedou2Fritz Tabi Oben3Department of mining, petroleum and gas exploration, National Advanced School of Mines and Petroleum Industries (ENSMIP), University of Maroua, P.O. Box 08, Kaele, Cameroon; Department of Soil Science, Faculty of Agronomy and Agricultural Sciences (FASA), University of Dschang, P.O. Box: 222, Dschang, Cameroon; Corresponding author at: P.O. Box 08, Kaele, Cameroon.Institute of Agricultural Research for Development (IRAD), P.O. Box 2067, Yaounde, CameroonDepartment of Soil Science, Faculty of Agronomy and Agricultural Sciences (FASA), University of Dschang, P.O. Box: 222, Dschang, Cameroon; Sustainable Tropical Actions (STA), a non-profit organization dedicated to the protection of the environment and fight against climate change, Yaoundé CameroonDepartment of Soil Science, Faculty of Agronomy and Agricultural Sciences (FASA), University of Dschang, P.O. Box: 222, Dschang, CameroonRemotely sensed data is well-used for monitoring dynamics in land-use and land-cover (LULC). However, in previous studies, delineating small-size LULC within shifting agricultural landscape mosaic systems (SALMS) in the Congo basin has shown limitations when Landsat-7 is used, due to its spatial and spectral resolutions. Although Landsat-8 and Sentinel-2 data could provide a better contribution, their use in disaggregating these small-size LULC over degraded humid forest remains underexploited. This research evaluated the potential of Landsat-8 and Sentinel-2 data to support the disaggregation of small-size LULC within the SALMS. Statistical analyses of spectra data points were applied to (i) assess the spectral separability of LULC classes by bands, (ii) identify the suitable band-combinations, and (iii) compare the accuracy of both sensors for LULC mapping within the landscape. The results revealed that four Landsat-8 bands (2, 3, 5, and 6) and seven Sentinel-2 bands (2–4, and 7–11) showed good spectral separability. Two Landsat-8 band-combinations ([2–5-6] and [3–5-6]), with the highest Optimum Index Factor scores of 1416 and 1756 respectively, were suitable for colour-composition, while Sentinel-2 band-combination [8–11-4] did the same with a score of 473. At the reference level, there was no significant difference (p > 0.05) between Landsat-8 and Sentinel-2 generated maps. However, Sentinel-2, with 91 % accuracy, had a better capability to delineate small-size LULC within the landscape compared to Landsat-8 (85 % accuracy). This result provides an advantage towards accurate LULC monitoring with respect to carbon stock change estimates within the SALMS in the Congo, Amazonian and Southeast Asia basins.http://www.sciencedirect.com/science/article/pii/S1569843223003692Heterogeneous landscapeLandsat-8Sentinel-2Small-size LULC disaggregationSpectra data points |
| spellingShingle | Christin Steve Keyamfe Nwagoum Martin Yemefack Francis Brice Silatsa Tedou Fritz Tabi Oben Sentinel-2 and Landsat-8 potentials for high-resolution mapping of the shifting agricultural landscape mosaic systems of southern Cameroon International Journal of Applied Earth Observations and Geoinformation Heterogeneous landscape Landsat-8 Sentinel-2 Small-size LULC disaggregation Spectra data points |
| title | Sentinel-2 and Landsat-8 potentials for high-resolution mapping of the shifting agricultural landscape mosaic systems of southern Cameroon |
| title_full | Sentinel-2 and Landsat-8 potentials for high-resolution mapping of the shifting agricultural landscape mosaic systems of southern Cameroon |
| title_fullStr | Sentinel-2 and Landsat-8 potentials for high-resolution mapping of the shifting agricultural landscape mosaic systems of southern Cameroon |
| title_full_unstemmed | Sentinel-2 and Landsat-8 potentials for high-resolution mapping of the shifting agricultural landscape mosaic systems of southern Cameroon |
| title_short | Sentinel-2 and Landsat-8 potentials for high-resolution mapping of the shifting agricultural landscape mosaic systems of southern Cameroon |
| title_sort | sentinel 2 and landsat 8 potentials for high resolution mapping of the shifting agricultural landscape mosaic systems of southern cameroon |
| topic | Heterogeneous landscape Landsat-8 Sentinel-2 Small-size LULC disaggregation Spectra data points |
| url | http://www.sciencedirect.com/science/article/pii/S1569843223003692 |
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