A Spectral Unmixing Method with Ensemble Estimation of Endmembers: Application to Flood Mapping in the Caprivi Floodplain
"> Figure 1
<p>Location of the study area.</p> "> Figure 2
<p>Yearly cycle of Zambezi river: (<b>a</b>) Discharge hydrograph; and (<b>b</b>) Water level for the period from 2008 to 2011. The dotted line shows the flood threshold whereas the black circles point out the flooding events considered in this study.</p> "> Figure 3
<p>NDWI calculated from (<b>a</b>) TM and (<b>b</b>) MERIS images acquired on 17 April 2008 as sampled along four transects (<b>c</b>–<b>f</b>).</p> "> Figure 4
<p>NDVI calculated from (<b>a</b>) TM and (<b>b</b>) MERIS images acquired on 17 April 2008 as sampled along four transects (<b>c</b>–<b>f</b>).</p> "> Figure 5
<p>Scatter plot of TM versus MERIS NDVI and NDWI over water and vegetation features.</p> "> Figure 6
<p>Histograms of (<b>a</b>) NDWI and (<b>b</b>) NDVI as generated from MERIS and TM images acquired on 17 April 2008.</p> "> Figure 7
<p>Scatter plot of green versus NIR spectral reflectance of an endmembers sample selected automatically from (<b>a</b>) TM and (<b>b</b>) MERIS images on 17 April 2008.</p> "> Figure 8
<p>Different extents of (<b>a</b>) soil, (<b>b</b>) vegetation and (<b>c</b>) water endmembers selected by the automatic procedure explained in <a href="#sec2dot6-remotesensing-09-01013" class="html-sec">Section 2.6</a> from TM (red shade) and MERIS images (blue shade) on 17 April 2008 over TM true color composite (RGB).</p> "> Figure 9
<p>Medians (black diamonds) and interquartile range (IQR, red diamonds) of the <math display="inline"> <semantics> <mrow> <msub> <mi>γ</mi> <mi>w</mi> </msub> </mrow> </semantics> </math> distributions calculated with the proposed index based spectral unmixing (IBSU) method for the Caprivi study area from TM and MERIS images on 17 April 2008 by changing randomly water (<b>a</b>,<b>b</b>), vegetation (<b>c</b>,<b>d</b>) and soil (<b>e</b>,<b>f</b>) endmembers.</p> "> Figure 10
<p>(<b>a</b>) Medians; (<b>b</b>) inter-quartile range of ensemble <math display="inline"> <semantics> <mrow> <msub> <mi>γ</mi> <mi>w</mi> </msub> </mrow> </semantics> </math> calculated over the study area as function of runs number included in the ensemble.</p> "> Figure 11
<p><math display="inline"> <semantics> <mrow> <msub> <mi>γ</mi> <mi>w</mi> </msub> </mrow> </semantics> </math> calculated with the 17 April 2008 (<b>a</b>) TM and (<b>b</b>) MERIS images, compared to the <math display="inline"> <semantics> <mrow> <msub> <mi>γ</mi> <mi>w</mi> </msub> </mrow> </semantics> </math> derived from the (<b>c</b>) 22 May 2009 and (<b>d</b>) 23 May 2009 MERIS images.</p> "> Figure 11 Cont.
<p><math display="inline"> <semantics> <mrow> <msub> <mi>γ</mi> <mi>w</mi> </msub> </mrow> </semantics> </math> calculated with the 17 April 2008 (<b>a</b>) TM and (<b>b</b>) MERIS images, compared to the <math display="inline"> <semantics> <mrow> <msub> <mi>γ</mi> <mi>w</mi> </msub> </mrow> </semantics> </math> derived from the (<b>c</b>) 22 May 2009 and (<b>d</b>) 23 May 2009 MERIS images.</p> "> Figure 12
<p>Mean fractional abundance estimated by spectral indices unmixing method over the 1.2 km × 1.2 km cells of an arbitrary grid in (<b>a</b>) April 2008 and (<b>b</b>) May 2009 images indices based spectral unmixing.</p> "> Figure 13
<p>Histograms of <math display="inline"> <semantics> <mrow> <msub> <mi>γ</mi> <mi>w</mi> </msub> </mrow> </semantics> </math> retrieved with MERIS and TM data: (<b>a</b>) IBSU on 17 April 2008; (<b>b</b>) LSU on 17 April 2008; (<b>c</b>) IBSU on 22 (TM) (MERIS) and 23 May 2009; (<b>d</b>) LSU on 22 (TM) and 23 (MERIS) May 2009.</p> "> Figure 14
<p><math display="inline"> <semantics> <mrow> <msub> <mi>γ</mi> <mi>w</mi> </msub> </mrow> </semantics> </math> maps as produced by applying (<b>a</b>) IBSU and (<b>b</b>) LSU on the 17 April 2008 TM image, compared to (<b>c</b>) IBSU and (<b>d</b>) LSU applied to the MERIS image of the same date.</p> "> Figure 14 Cont.
<p><math display="inline"> <semantics> <mrow> <msub> <mi>γ</mi> <mi>w</mi> </msub> </mrow> </semantics> </math> maps as produced by applying (<b>a</b>) IBSU and (<b>b</b>) LSU on the 17 April 2008 TM image, compared to (<b>c</b>) IBSU and (<b>d</b>) LSU applied to the MERIS image of the same date.</p> ">
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Remote Sensing Data
2.3. Pre-Processing
2.4. Linear Spectral Unmixing
2.5. Indices-Based Spectral Unmixing
2.6. Automatic Selection of Endmembers
2.7. Accuracy Assessment
- Comparison between MERIS versus TM based obtained with the IBSU (Equations (5) and (6)) to evaluate the impact of image spatial resolution on the estimated with our method. To compare the estimated with the MERIS data with the one estimated with TM a grid was constructed with each cell being 1200 m × 1200 m. The mean of each cell was calculated for both data sets and the cell averages compared. The arbitrary 1200 m × 1200 m grid was selected to sample the same area with both TM and MERIS. Cells of this size included a sufficient number (sixteen) of MERIS pixels.
- Comparison between MERIS versus TM estimated with Equations (6) and (7) with the obtained with Equation (1).
3. Results
3.1. Detection of Water and Vegetation Features with MERIS and TM Spectral Indices
3.2. Endmember Selection
3.3. Spectral Indices-Based Unmixing versus Linear Spectral Unmixing
4. Discussion
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Image Pair | Sensor | Acquisition Date and GMT | Spatial Resolution | Temporal Resolution |
---|---|---|---|---|
Pair 1 | MERIS | 17 April 2008 08:09 | 300 m | 3 days |
TM | 17 April 2008 08:13 | 30 m | 16 days | |
Pair 2 | MERIS | 23 May 2009 08:07 | 300 m | 3 days |
TM | 22 May 2009 08:12 | 30 m | 16 days |
Image Dates | * | |||||
---|---|---|---|---|---|---|
MIS | 0.051 (±0.011) | 0.034 (±0.012) | 0.060 (±0.08) | 0.241 (±0.033) | 0.081 (±0.016) | 0.198 (±0.043) |
17 April 2008 | ||||||
TM | 0.038 (±0.049) | 0.030 (±0.021) | 0.060 (±0.011) | 0.234 (±0.034) | 0.105 (±0.016) | 0.252 (±0.026) |
17 April 2008 | ||||||
MERIS | 0.041 (±0.016) | 0.023 (±0.012) | 0.056 (±0.009) | 0.214 (±0.030) | 0.071 (±0.018) | 0.187 (±0.057) |
23 May 2009 | ||||||
TM | 0.026 (±0.046) | 0.020 (±0.017) | 0.055 (±0.011) | 0.204 (±0.033) | 0.090 (±0.019) | 0.215 (±0.029) |
22 May 2009 |
Image Date | ||
---|---|---|
MERIS 17 April 2008 | 0.69 | 0.17 |
TM 17 April 2008 | 0.67 | 0.05 |
MERIS 23 May 2009 | 0.74 | 0.05 |
TM 22 May 2009 | 0.64 | 0.00 |
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Bangira, T.; Alfieri, S.M.; Menenti, M.; Van Niekerk, A.; Vekerdy, Z. A Spectral Unmixing Method with Ensemble Estimation of Endmembers: Application to Flood Mapping in the Caprivi Floodplain. Remote Sens. 2017, 9, 1013. https://doi.org/10.3390/rs9101013
Bangira T, Alfieri SM, Menenti M, Van Niekerk A, Vekerdy Z. A Spectral Unmixing Method with Ensemble Estimation of Endmembers: Application to Flood Mapping in the Caprivi Floodplain. Remote Sensing. 2017; 9(10):1013. https://doi.org/10.3390/rs9101013
Chicago/Turabian StyleBangira, Tsitsi, Silvia Maria Alfieri, Massimo Menenti, Adriaan Van Niekerk, and Zoltán Vekerdy. 2017. "A Spectral Unmixing Method with Ensemble Estimation of Endmembers: Application to Flood Mapping in the Caprivi Floodplain" Remote Sensing 9, no. 10: 1013. https://doi.org/10.3390/rs9101013