A Multi-Scale Flood Monitoring System Based on Fully Automatic MODIS and TerraSAR-X Processing Chains
Abstract
:1. Introduction
2. Methodology
2.1. MODIS Flood Service
2.1.1. Pre-Processing of MODIS and Auxiliary Data
Level 1A (MOD 01), Level 1B (MOD 02), and Geolocation Datasets (MOD 03)
MODIS Level 2 Corrected Reflectance Product
Projection
Post-Processing with GDAL
Auxiliary Datasets
2.1.2. Thematic Analysis
- Computing of spectral indices
- Initial thresholding of the spectral bands and indices
- Post-processing including the integration of auxiliary data
- Region growing
- Improved separation between water and cloud shadows
Computing of Spectral Indices
Initial Thresholding of the Spectral Bands and Indices
- Determination of cloud-cover areas based on a threshold of ≥0.27 from the blue reflectance band. The cloud positions are subsequently used for a geometry-based detection of cloud shadows.
- Classification of non-flooded areas by using an EVI >0.3.
- Initial identification of water-related pixels based on the derived indices using two criteria, which combine the EVI (≤0.3) and the DVEL (≤0.05), as well as the EVI (≤0.05) and the LSWI (≤0.0) respectively.
- Separation of water-related areas into flood surfaces (EVI ≤ 0.1) and mixed pixels (0.1 < EVI ≤ 0.3). A mixed pixel denotes a pixel that contains more than one thematic land-cover element of interest, which is a common phenomenon in moderate resolution MODIS data.
Post-Processing Including the Integration of Auxiliary Data
Region Growing
Improved Separation between Water and Cloud Shadows
2.1.3. Dissemination of Classification Results
2.2. TerraSAR-X Flood Service
2.2.1. Pre-Processing of TerraSAR-X and Auxiliary Data
2.2.2. Thematic Analysis
Automatic Tile-Based Thresholding
Post-Classification
2.2.3. Dissemination of Classification Results
3. Experimental Results
3.1. Study Area and Dataset
3.2. Results and Discussion
- The flood extent is much smaller for the AOI in Albania/Montenegro. Therefore, MODIS data could only be used for a rough estimation of the actual flood extent. The MODIS derived flood mask is considerably underestimated since mixed areas are very prevalent. In contrast it is possible to derive detailed information about the flooding and to map even small tributaries with an extent lower the spatial resolution of the MODIS images using TerraSAR-X. Therefore, the number of flood pixels identified by TerraSAR-X data only is nearly 17% higher compared to the test site in Russia.
- In comparison to the test area in Russia the cloud coverage at the time of the MODIS acquisition is much higher. Cloud shadows are partly located over flood-affected areas. This leads to an underestimation of the MODIS-derived flood extent due to the reduced spectral separability of water surfaces and cloud shadow areas.
- In the northern part of Lake Scutari in Montenegro, the flooding is extensively covered with vegetation. The X-band SAR signal is very sensitive to flooded vegetation in this region due to the double bounce effect between the water surface and the lower parts of the vegetation. This results in a very high signal return and consequently an underestimation of the flood extent. In contrast the MODIS flood processor is less sensitive to protruding vegetation and is able detect more flood surfaces in this region. This explains the high percentage of flood pixels derived by using the MODIS data (see Figure 7).
4. Conclusion
Acknowledgments
Conflicts of Interest
References
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Band | Bandwidth (nm) | Resolution (m) | Primary Use |
---|---|---|---|
1 (ρRED) | 620–670 | 250 | Absolute Land Cover Transformation, Chlorophyll |
2 (ρNIR) | 841–876 | 250 | Cloud Amount, Vegetation Land Cover Transformation |
3 (ρBLUE) | 459–479 | 500 | Soil/Vegetation Differences |
4 (ρGREEN) | 545–565 | 500 | Green Vegetation |
6 (ρSWIR) | 1628–1652 | 500 | Snow/Cloud Differences |
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Martinis, S.; Twele, A.; Strobl, C.; Kersten, J.; Stein, E. A Multi-Scale Flood Monitoring System Based on Fully Automatic MODIS and TerraSAR-X Processing Chains. Remote Sens. 2013, 5, 5598-5619. https://doi.org/10.3390/rs5115598
Martinis S, Twele A, Strobl C, Kersten J, Stein E. A Multi-Scale Flood Monitoring System Based on Fully Automatic MODIS and TerraSAR-X Processing Chains. Remote Sensing. 2013; 5(11):5598-5619. https://doi.org/10.3390/rs5115598
Chicago/Turabian StyleMartinis, Sandro, André Twele, Christian Strobl, Jens Kersten, and Enrico Stein. 2013. "A Multi-Scale Flood Monitoring System Based on Fully Automatic MODIS and TerraSAR-X Processing Chains" Remote Sensing 5, no. 11: 5598-5619. https://doi.org/10.3390/rs5115598