Methodologies and Uncertainties in the Use of the Terrestrial Chlorophyll Index for the Sentinel-3 Mission
A methodology is described for the validation of Medium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) data over heterogeneous land surfaces in an agricultural region in Southern Italy. The approach involves the use inverse canopy reflectance modeling techniques to deri...
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| Format: | Article |
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MDPI AG
2012-04-01
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| Series: | Remote Sensing |
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| Online Access: | http://www.mdpi.com/2072-4292/4/5/1112 |
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| author | Ewa Kwiatkowska Dulce Lajas Paul J. Curran Jadunandan Dash Francesco Vuolo |
| author_facet | Ewa Kwiatkowska Dulce Lajas Paul J. Curran Jadunandan Dash Francesco Vuolo |
| author_sort | Ewa Kwiatkowska |
| collection | DOAJ |
| description | A methodology is described for the validation of Medium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) data over heterogeneous land surfaces in an agricultural region in Southern Italy. The approach involves the use inverse canopy reflectance modeling techniques to derive maps of canopy chlorophyll content (CCC) and leaf area index (LAI) at fine spatial resolution. Indirect field measurements are used for validation of the fine spatial resolution data. Subsequently, these maps are aggregated based on a regular grid at 1 km spatial resolution to validate MERIS Level 2 MTCI (300 m). RapidEye satellite sensor data with a pixel size of 6.5 m are used for this purpose. Based on a set of independent ground measurements, fine spatial resolution maps achieved an <em>R<sup>2</sup></em> = 0.78 and RMSE = 0.39 for CCC and <em>R</em><sup>2</sup> = 0.76 and RMSE = 0.64 for LAI. The relationship between MERIS L2 MTCI and CCC [g∙m<sup>−2</sup>] achieved a coefficient of determination of 0.74 and it resulted to be extremely statistically significant (<em>p</em>-value < 0.001). Additionally, a relative validation of two other satellite products at medium resolution spatial scale, namely MERIS leaf area index (LAI) and Moderate Resolution Imaging Spectrometer (MODIS) LAI was performed by comparison with the fine spatial resolution LAI map. Results indicated a better accuracy in LAI estimation of MERIS (RMSE = 0.33) compared to MODIS (RMSE = 0.81) data. |
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| id | doaj.art-7f5695d861bc4325a8d237078d297803 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-04-11T18:26:32Z |
| publishDate | 2012-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-7f5695d861bc4325a8d237078d2978032022-12-22T04:09:37ZengMDPI AGRemote Sensing2072-42922012-04-01451112113310.3390/rs4051112Methodologies and Uncertainties in the Use of the Terrestrial Chlorophyll Index for the Sentinel-3 MissionEwa KwiatkowskaDulce LajasPaul J. CurranJadunandan DashFrancesco VuoloA methodology is described for the validation of Medium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) data over heterogeneous land surfaces in an agricultural region in Southern Italy. The approach involves the use inverse canopy reflectance modeling techniques to derive maps of canopy chlorophyll content (CCC) and leaf area index (LAI) at fine spatial resolution. Indirect field measurements are used for validation of the fine spatial resolution data. Subsequently, these maps are aggregated based on a regular grid at 1 km spatial resolution to validate MERIS Level 2 MTCI (300 m). RapidEye satellite sensor data with a pixel size of 6.5 m are used for this purpose. Based on a set of independent ground measurements, fine spatial resolution maps achieved an <em>R<sup>2</sup></em> = 0.78 and RMSE = 0.39 for CCC and <em>R</em><sup>2</sup> = 0.76 and RMSE = 0.64 for LAI. The relationship between MERIS L2 MTCI and CCC [g∙m<sup>−2</sup>] achieved a coefficient of determination of 0.74 and it resulted to be extremely statistically significant (<em>p</em>-value < 0.001). Additionally, a relative validation of two other satellite products at medium resolution spatial scale, namely MERIS leaf area index (LAI) and Moderate Resolution Imaging Spectrometer (MODIS) LAI was performed by comparison with the fine spatial resolution LAI map. Results indicated a better accuracy in LAI estimation of MERIS (RMSE = 0.33) compared to MODIS (RMSE = 0.81) data.http://www.mdpi.com/2072-4292/4/5/1112Envisat-MERISMERIS Terrestrial Chlorophyll Index (MTCI)canopy chlorophyll content (CCC)leaf area index (LAI)Sentinel-3OLCI Terrestrial Chlorophyll Index (OTCI) |
| spellingShingle | Ewa Kwiatkowska Dulce Lajas Paul J. Curran Jadunandan Dash Francesco Vuolo Methodologies and Uncertainties in the Use of the Terrestrial Chlorophyll Index for the Sentinel-3 Mission Remote Sensing Envisat-MERIS MERIS Terrestrial Chlorophyll Index (MTCI) canopy chlorophyll content (CCC) leaf area index (LAI) Sentinel-3 OLCI Terrestrial Chlorophyll Index (OTCI) |
| title | Methodologies and Uncertainties in the Use of the Terrestrial Chlorophyll Index for the Sentinel-3 Mission |
| title_full | Methodologies and Uncertainties in the Use of the Terrestrial Chlorophyll Index for the Sentinel-3 Mission |
| title_fullStr | Methodologies and Uncertainties in the Use of the Terrestrial Chlorophyll Index for the Sentinel-3 Mission |
| title_full_unstemmed | Methodologies and Uncertainties in the Use of the Terrestrial Chlorophyll Index for the Sentinel-3 Mission |
| title_short | Methodologies and Uncertainties in the Use of the Terrestrial Chlorophyll Index for the Sentinel-3 Mission |
| title_sort | methodologies and uncertainties in the use of the terrestrial chlorophyll index for the sentinel 3 mission |
| topic | Envisat-MERIS MERIS Terrestrial Chlorophyll Index (MTCI) canopy chlorophyll content (CCC) leaf area index (LAI) Sentinel-3 OLCI Terrestrial Chlorophyll Index (OTCI) |
| url | http://www.mdpi.com/2072-4292/4/5/1112 |
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