Using RapidEye and MODIS Data Fusion to Monitor Vegetation Dynamics in Semi-Arid Rangelands in South Africa
Image time series of high temporal and spatial resolution capture land surface dynamics of heterogeneous landscapes. We applied the ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) algorithm to multi-spectral images covering two semi-arid heterogeneous rangeland study sites...
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-05-01
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| Series: | Remote Sensing |
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| Online Access: | http://www.mdpi.com/2072-4292/7/6/6510 |
| _version_ | 1818974183773700096 |
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| author | Andreas Tewes Frank Thonfeld Michael Schmidt Roelof J. Oomen Xiaolin Zhu Olena Dubovyk Gunter Menz Jürgen Schellberg |
| author_facet | Andreas Tewes Frank Thonfeld Michael Schmidt Roelof J. Oomen Xiaolin Zhu Olena Dubovyk Gunter Menz Jürgen Schellberg |
| author_sort | Andreas Tewes |
| collection | DOAJ |
| description | Image time series of high temporal and spatial resolution capture land surface dynamics of heterogeneous landscapes. We applied the ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) algorithm to multi-spectral images covering two semi-arid heterogeneous rangeland study sites located in South Africa. MODIS 250 m resolution and RapidEye 5 m resolution images were fused to produce synthetic RapidEye images, from June 2011 to July 2012. We evaluated the performance of the algorithm by comparing predicted surface reflectance values to real RapidEye images. Our results show that ESTARFM predictions are accurate, with a coefficient of determination for the red band 0.80 < R2 < 0.92, and for the near-infrared band 0.83 < R2 < 0.93, a mean relative bias between 6% and 12% for the red band and 4% to 9% in the near-infrared band. Heterogeneous vegetation at sub-MODIS resolution is captured adequately: A comparison of NDVI time series derived from RapidEye and ESTARFM data shows that the characteristic phenological dynamics of different vegetation types are reproduced well. We conclude that the ESTARFM algorithm allows us to produce synthetic remote sensing images at high spatial combined with high temporal resolution and so provides valuable information on vegetation dynamics in semi-arid, heterogeneous rangeland landscapes. |
| first_indexed | 2024-12-20T15:36:01Z |
| format | Article |
| id | doaj.art-fa3cdbf6e6c2494f87357db47a30922a |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-20T15:36:01Z |
| publishDate | 2015-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-fa3cdbf6e6c2494f87357db47a30922a2022-12-21T19:35:26ZengMDPI AGRemote Sensing2072-42922015-05-01766510653410.3390/rs70606510rs70606510Using RapidEye and MODIS Data Fusion to Monitor Vegetation Dynamics in Semi-Arid Rangelands in South AfricaAndreas Tewes0Frank Thonfeld1Michael Schmidt2Roelof J. Oomen3Xiaolin Zhu4Olena Dubovyk5Gunter Menz6Jürgen Schellberg7Center for Remote Sensing of Land Surfaces, University of Bonn, Walter-Flex-Str. 3, 53113 Bonn, GermanyCenter for Remote Sensing of Land Surfaces, University of Bonn, Walter-Flex-Str. 3, 53113 Bonn, GermanyRemote Sensing Centre, Environment and Resource Sciences, Department of Science, Information Technology, Innovation and the Arts, GPO Box 5078, Brisbane, Queensland 4001, AustraliaInstitute of Crop Science and Resource Conservation (INRES), University of Bonn, Katzenburgweg 5, 53115 Bonn, GermanyEcosystem Science and Sustainability, Colorado State University, NESB 108, 1499 Campus Delivery, Fort Collins, CO 805239, USACenter for Remote Sensing of Land Surfaces, University of Bonn, Walter-Flex-Str. 3, 53113 Bonn, GermanyCenter for Remote Sensing of Land Surfaces, University of Bonn, Walter-Flex-Str. 3, 53113 Bonn, GermanyCenter for Remote Sensing of Land Surfaces, University of Bonn, Walter-Flex-Str. 3, 53113 Bonn, GermanyImage time series of high temporal and spatial resolution capture land surface dynamics of heterogeneous landscapes. We applied the ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) algorithm to multi-spectral images covering two semi-arid heterogeneous rangeland study sites located in South Africa. MODIS 250 m resolution and RapidEye 5 m resolution images were fused to produce synthetic RapidEye images, from June 2011 to July 2012. We evaluated the performance of the algorithm by comparing predicted surface reflectance values to real RapidEye images. Our results show that ESTARFM predictions are accurate, with a coefficient of determination for the red band 0.80 < R2 < 0.92, and for the near-infrared band 0.83 < R2 < 0.93, a mean relative bias between 6% and 12% for the red band and 4% to 9% in the near-infrared band. Heterogeneous vegetation at sub-MODIS resolution is captured adequately: A comparison of NDVI time series derived from RapidEye and ESTARFM data shows that the characteristic phenological dynamics of different vegetation types are reproduced well. We conclude that the ESTARFM algorithm allows us to produce synthetic remote sensing images at high spatial combined with high temporal resolution and so provides valuable information on vegetation dynamics in semi-arid, heterogeneous rangeland landscapes.http://www.mdpi.com/2072-4292/7/6/6510RapidEyeMODISESTARFMimage fusiondata blendingvegetation dynamicshigh spatial and temporal resolutiontime series |
| spellingShingle | Andreas Tewes Frank Thonfeld Michael Schmidt Roelof J. Oomen Xiaolin Zhu Olena Dubovyk Gunter Menz Jürgen Schellberg Using RapidEye and MODIS Data Fusion to Monitor Vegetation Dynamics in Semi-Arid Rangelands in South Africa Remote Sensing RapidEye MODIS ESTARFM image fusion data blending vegetation dynamics high spatial and temporal resolution time series |
| title | Using RapidEye and MODIS Data Fusion to Monitor Vegetation Dynamics in Semi-Arid Rangelands in South Africa |
| title_full | Using RapidEye and MODIS Data Fusion to Monitor Vegetation Dynamics in Semi-Arid Rangelands in South Africa |
| title_fullStr | Using RapidEye and MODIS Data Fusion to Monitor Vegetation Dynamics in Semi-Arid Rangelands in South Africa |
| title_full_unstemmed | Using RapidEye and MODIS Data Fusion to Monitor Vegetation Dynamics in Semi-Arid Rangelands in South Africa |
| title_short | Using RapidEye and MODIS Data Fusion to Monitor Vegetation Dynamics in Semi-Arid Rangelands in South Africa |
| title_sort | using rapideye and modis data fusion to monitor vegetation dynamics in semi arid rangelands in south africa |
| topic | RapidEye MODIS ESTARFM image fusion data blending vegetation dynamics high spatial and temporal resolution time series |
| url | http://www.mdpi.com/2072-4292/7/6/6510 |
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