Spectral signature analysis of false positive burned area detection from agricultural harvests using Sentinel-2 data
Accurate mapping of burned area is of key importance for fire emissions modeling and post-fire rehabilitation planning. In this research, Sentinel-2 data were used to analyze the difference in spectral signature between burned area and false positives from agricultural harvests. 26 fires that were m...
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| Format: | Article |
| Language: | English |
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Elsevier
2021-05-01
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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/S0303243421000027 |
| _version_ | 1811328848318431232 |
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| author | Daan van Dijk Sorosh Shoaie Thijs van Leeuwen Sander Veraverbeke |
| author_facet | Daan van Dijk Sorosh Shoaie Thijs van Leeuwen Sander Veraverbeke |
| author_sort | Daan van Dijk |
| collection | DOAJ |
| description | Accurate mapping of burned area is of key importance for fire emissions modeling and post-fire rehabilitation planning. In this research, Sentinel-2 data were used to analyze the difference in spectral signature between burned area and false positives from agricultural harvests. 26 fires that were mapped in the field using Global Navigation Satellite System during 2017 and 2018 were analyzed over California and Utah, USA. Individual Sentinel-2 bands and a wide range of commonly used spectral indices for burned area were tested using a spectral separability index. The separability index assessed discrimination between the classes burned area and 1) unburned area and 2) area in agricultural land that were flagged as false positive from agricultural harvest. Separability values higher than one indicate good separation and the higher the values, the better the separation. For each class, we first determined the multitemporal difference, i.e. the absolute value of the pre-minus-post-change value. Second, we compared with other classes by using the spectral separability index. We found that for the burned-to-unburned comparison the near and shortwave infrared spectral regions and spectral indices that make use of these spectral regions, were the best discriminators (separability (M) values of approximately 2), corroborating findings from earlier works. For the burned-to-agricultural false positive comparison Sentinel-2 bands 4 and 5, corresponding with the Red and Red-edge spectral regions, were the best discriminator (M−values greater than 2). Consequently, spectral indices containing the Red band show a similar strong separability of agricultural false positives. The results from our research reveal an additional layer of information that could be exploited to minimize false positives in agricultural lands in space-borne burned area products. |
| first_indexed | 2024-04-13T15:33:22Z |
| format | Article |
| id | doaj.art-a8a032a6d0d54ecfb1b68beee34deb17 |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-04-13T15:33:22Z |
| publishDate | 2021-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-a8a032a6d0d54ecfb1b68beee34deb172022-12-22T02:41:20ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322021-05-0197102296Spectral signature analysis of false positive burned area detection from agricultural harvests using Sentinel-2 dataDaan van Dijk0Sorosh Shoaie1Thijs van Leeuwen2Sander Veraverbeke3Faculty of Science, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, North Holland, The Netherlands; Corresponding author.VanderSat, Wilhelminastraat 43a, 2011 VK Haarlem, The NetherlandsVanderSat, Wilhelminastraat 43a, 2011 VK Haarlem, The NetherlandsFaculty of Science, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, North Holland, The NetherlandsAccurate mapping of burned area is of key importance for fire emissions modeling and post-fire rehabilitation planning. In this research, Sentinel-2 data were used to analyze the difference in spectral signature between burned area and false positives from agricultural harvests. 26 fires that were mapped in the field using Global Navigation Satellite System during 2017 and 2018 were analyzed over California and Utah, USA. Individual Sentinel-2 bands and a wide range of commonly used spectral indices for burned area were tested using a spectral separability index. The separability index assessed discrimination between the classes burned area and 1) unburned area and 2) area in agricultural land that were flagged as false positive from agricultural harvest. Separability values higher than one indicate good separation and the higher the values, the better the separation. For each class, we first determined the multitemporal difference, i.e. the absolute value of the pre-minus-post-change value. Second, we compared with other classes by using the spectral separability index. We found that for the burned-to-unburned comparison the near and shortwave infrared spectral regions and spectral indices that make use of these spectral regions, were the best discriminators (separability (M) values of approximately 2), corroborating findings from earlier works. For the burned-to-agricultural false positive comparison Sentinel-2 bands 4 and 5, corresponding with the Red and Red-edge spectral regions, were the best discriminator (M−values greater than 2). Consequently, spectral indices containing the Red band show a similar strong separability of agricultural false positives. The results from our research reveal an additional layer of information that could be exploited to minimize false positives in agricultural lands in space-borne burned area products.http://www.sciencedirect.com/science/article/pii/S0303243421000027Sentinel-2Burned areaFireAgricultureHarvestSpectral indices |
| spellingShingle | Daan van Dijk Sorosh Shoaie Thijs van Leeuwen Sander Veraverbeke Spectral signature analysis of false positive burned area detection from agricultural harvests using Sentinel-2 data International Journal of Applied Earth Observations and Geoinformation Sentinel-2 Burned area Fire Agriculture Harvest Spectral indices |
| title | Spectral signature analysis of false positive burned area detection from agricultural harvests using Sentinel-2 data |
| title_full | Spectral signature analysis of false positive burned area detection from agricultural harvests using Sentinel-2 data |
| title_fullStr | Spectral signature analysis of false positive burned area detection from agricultural harvests using Sentinel-2 data |
| title_full_unstemmed | Spectral signature analysis of false positive burned area detection from agricultural harvests using Sentinel-2 data |
| title_short | Spectral signature analysis of false positive burned area detection from agricultural harvests using Sentinel-2 data |
| title_sort | spectral signature analysis of false positive burned area detection from agricultural harvests using sentinel 2 data |
| topic | Sentinel-2 Burned area Fire Agriculture Harvest Spectral indices |
| url | http://www.sciencedirect.com/science/article/pii/S0303243421000027 |
| work_keys_str_mv | AT daanvandijk spectralsignatureanalysisoffalsepositiveburnedareadetectionfromagriculturalharvestsusingsentinel2data AT soroshshoaie spectralsignatureanalysisoffalsepositiveburnedareadetectionfromagriculturalharvestsusingsentinel2data AT thijsvanleeuwen spectralsignatureanalysisoffalsepositiveburnedareadetectionfromagriculturalharvestsusingsentinel2data AT sanderveraverbeke spectralsignatureanalysisoffalsepositiveburnedareadetectionfromagriculturalharvestsusingsentinel2data |