# Fusion of High Resolution Multispectral Imagery in Vulnerable Coastal and Land Ecosystems

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## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

#### 2.1. Study Area

#### 2.2. Datasets

#### 2.3. Image Fusion Methodology

#### 2.3.1. Image Fusion Methods

- Fast intensity hue saturation (FIHS) [48]: It uses the spectral bands to estimate the new component I. The spatial detail is extracted, computing the difference between the PAN band and the new component I. The spatial detail is injected into any number of bands.
- Hyperspherical color sharpening (HCS): This pansharpening algorithm is designed specifically for WV-2 by [49] based on the transformation between any native color space and the hyperspherical color space. Once transformed into HCS, the intensity can be scaled without changing the color, essential for the HCS pansharpening algorithm [15,50]. The transformation to HCS can be made from any native color space.
- Based on modulation transfer function: The modulation transfer function (MTF) is a function of the sensor spatial frequency response, describing the resolution of an imaging system [28]. Generalized Laplacian pyramid (GLP) is an extension of the Laplacian pyramid where a scale factor different from two is used [10]. Finally, in high pass modulation (HPM), the PAN image is multiplied by each band of the original MS image and normalized by a low pass filtered version of the PAN image in order to estimate the enhanced MS image bands.
- Weighted wavelet ‘à trous’ method through fractal dimension maps (WAT⊗FRAC) [14]: This method is based on the wavelet ‘à trous’ algorithm. A mechanism that controls the trade-off between the spatial and spectral quality by introducing a weighting factor (α
_{i}) for the PAN wavelet coefficients is established. However, this factor only discriminates between different spectral bands, but not between different land covers; therefore, the authors proposed a new approach [51], defining a different weight factor α_{i}(x, y) for each point of each band. α_{i}(x, y) was defined as a fractal dimension map (FDM) with the same size as the original image. A preliminary analysis was carried out using three different window sizes for the windowing process: 7, 15 and 27.

#### 2.3.2. Quality Evaluation Methodology

- The Zhou index (Table 3, Equation (5)) measures the spatial quality computing correlation between the high pass filtered fused image ($FU{S}_{i}^{high\_pass}$) and PAN ($PA{N}^{high\_pass}$) image for each band.

#### 2.4. Classification Maps

## 3. Results

#### 3.1. Visual Evaluation

#### 3.2. Quantitative Evaluation of Pansharpened Images

#### 3.2.1. Shrubland Ecosystems

#### 3.2.2. Coastal Ecosystems

#### 3.2.3. Mixed Ecosystems

#### 3.2.4. Individual Band Quality Map Analysis

#### 3.3. Thematic Maps of Shrubland Ecosystems

## 4. Conclusions

## Acknowledgments

## Author Contributions

## Conflicts of Interest

## References

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**Figure 1.**Study areas from the Canary Islands: (

**a**) Teide National Park; (

**b**) Corralejo and Islote de Lobos Natural Park; and (

**c**) Maspalomas Natural Reserve.

**Figure 2.**PAN and MS scenes of WorldView-2 images (512 × 512 pixels for the MS image): (

**a**,

**d**) shrub land ecosystem; (

**b**,

**e**) coastal ecosystem; (

**c**,

**f**) mixed ecosystem with urban area and inner water lagoon.

**Figure 4.**True color fused images of the shrubland region: (

**a**) original MS; (

**b**) FIHS; (

**c**) HCS; (

**d**) MTF_GLP_HPM; (

**e**) WAT⊗FRAC with a window size of seven.

**Figure 5.**True color fused images of the coastal region: (

**a**) original MS; (

**b**) FIHS; (

**c**) HCS; (

**d**) MTF_GLP_HPM; (

**e**) WAT⊗FRAC with a window size of 27.

**Figure 6.**True color fused images of the mixed ecosystem with an urban region: (

**a**) original MS; (

**b**) FIHS; (

**c**) HCS; (

**d**) MTF_GLP_HPM; (

**e**) WAT⊗FRAC with a window size of 15.

**Figure 7.**False color fused images using Bands 8, 7 and 1 color composition (bands outside the PAN range): (

**a**) original MS; (

**b**) FIHS; (

**c**) HCS; (

**d**) MTF_GLP_HPM; (

**e**) WAT⊗FRAC.

**Figure 8.**Results of the quality indices for the shrubland ecosystem fused image considering the three different MS band combinations (blue: total bands; red: Bands 2–6; green: Bands 1, 7 and 8). X-axis: panharpening algorithms and Y-axis: range values of each quality indices (SAM: better value closer to 0; Spectral and Spatial ERGAS: better values closer to 0; FC: values between 0 and 1, better closer to 1; Zhou: values between 0 and 1, better closer to 1; Q8: values between 0 and 1, better closer to 1).

**Figure 9.**Results of the quality indices for the coastal ecosystem fused image considering the three different MS band combinations (blue: total bands; red: Bands 2–6; green: Bands 1, 7 and 8). X-axis: panharpening algorithms and Y-axis: range values of each quality indices (SAM: better value closer to 0; Spectral and Spatial ERGAS: better values closer to 0; FC: values between 0 and 1, better closer to 1; Zhou: values between 0 and 1, better closer to 1; Q8: values between 0 and 1, better closer to 1).

**Figure 10.**Results of the quality indices for the mixed ecosystem fused image considering the three different MS band combinations (blue: total bands; red: Bands 2–6; green: Bands 1, 7 and 8). X-axis: panharpening algorithms and Y-axis: range values of each quality indices (SAM: better value closer to 0; Spectral and Spatial ERGAS: better values closer to 0; FC: values between 0 and 1, better closer to 1; Zhou: values between 0 and 1, better closer to 1; Q8: values between 0 and 1, better closer to 1).

**Figure 11.**Fused image with the WAT⊗FRAC of the shrubland ecosystem and its quality maps for each band (scale from 0–1, zero being less fusion quality and one the highest fusion quality).

**Figure 12.**Fused image with FIHS of the coastal ecosystem and its quality maps for each band (scale from 0–1, zero being less fusion quality and one the higher fusion quality).

**Figure 13.**Fused image with WAT⊗FRAC of the mixed ecosystem and its quality maps for each band. Scale from 0–1, zero being less fusion quality and one the higher fusion quality.

**Figure 14.**Zoom of the original MS (

**a**) and WAT⊗FRAC fused image (

**b**) of the thematic maps obtained by the OBIA-SVM classifier applied to the multispectral image (

**c**) and WAT⊗FRAC fused image (

**d**) in the shrubland ecosystem.

Imaging Mode | Panchromatic | Multispectral |
---|---|---|

Spatial Resolution | 0.46 m | 1.84 m |

Spectral Range | 450–800 nm | 400–450 nm (coastal) |

450–510 nm (blue) | ||

510–580 nm (green) | ||

585–625 nm (yellow) | ||

630–690 nm (red) | ||

705–745 nm (red edge) | ||

770–895 nm (near IR 1) | ||

860–1040 nm (near IR 2) |

Worldview-2 Image | Coordinates | Acquisition Date |
---|---|---|

Teide National Park | 28°18′16″ N, 16°33′50″ W | 16 May 2011 |

Maspalomas Natural Reserve | 27°44′12″ N, 15°35′52″ W | 17 January 2013 |

Corralejo and Islote de Lobos Natural Park | 28°43′52″ N, 13°50′37″ W | 28 October 2010 |

Quality Indices | Equation | Reference | Equation |
---|---|---|---|

Spectral Angle Mapper | ${\mathrm{cos}}^{-1}\frac{{{\displaystyle \sum}}_{i=1}^{nband}FU{S}_{i}\text{}M{S}_{i}}{\sqrt{{{\displaystyle \sum}}_{i=1}^{nband}FU{S}_{i}^{2}}\sqrt{{{\displaystyle \sum}}_{i=1}^{nband}M{S}_{i}^{2}}}$ | [22] | (1) |

Spectral ERGAS | $100\frac{h}{l}\sqrt{\frac{1}{nband}{\displaystyle {\displaystyle \sum}_{i=1}^{nband}}{\left(\frac{rms{e}_{i}\left(MS\right)}{M{S}_{i}}\right)}^{2}}$ | [23] | (2) |

Spatial ERGAS | $100\frac{h}{l}\sqrt{\frac{1}{nband}{\displaystyle {\displaystyle \sum}_{i=1}^{nband}}{\left(\frac{rms{e}_{i}\left(PAN\right)}{PA{N}_{i}}\right)}^{2}}$ | [24] | (3) |

Frequency Comparison | $\frac{1}{nband}{\displaystyle {\displaystyle \sum}_{i=1}^{nband}}cor{r}_{i}\left(dc{t}_{nxn}^{AC}\left(PAN\right),dc{t}_{nxn}^{AC}\left(FU{S}_{i}\right)\right)$ | [25] | (4) |

Zhou | $\frac{1}{nband}{\displaystyle {\displaystyle \sum}_{i=1}^{nband}}cor{r}_{i}\left(PA{N}^{hig{h}_{pass}},FU{S}_{i}^{hig{h}_{pass}}\right)$ | [26] | (5) |

Q8 | ${\displaystyle \sum}_{i=1}^{nband}}\frac{4{\mathsf{\sigma}}_{MS,FUS}mea{n}_{MS}mea{n}_{FUS}}{{\mathsf{\sigma}}_{MS}^{2}+{\mathsf{\sigma}}_{FUS}^{2}\left[{\left(mea{n}_{MS}\right)}^{2}+{\left(mea{n}_{FUS}\right)}^{2}\right]$ | [27] | (6) |

_{i}represents the fused image; MS

_{i}is the i-th band of the MS image; PAN

_{i}is the PAN image; h and l represent the spatial resolution of the PAN and MS images, respectively; $dc{t}_{nxn}^{AC}$ is the discrete cosine transform computed in blocks of nxn pixels, and $cor{r}_{i}$ defines the cross-correlation of the i-th band; $FU{S}_{i}^{high\_pass}$ is the high pass filtered fused image, and $PA{N}^{high\_pass}$ is the high pass filtered PAN image; σ is the variance of the MS and FUS image.

**Table 4.**Quality results for the complete WV-2 bands and the shrubland ecosystem (best results in bold). SAM: spectral angle mapper; FC: frequency comparison; Spec.: spectral; Spat.: spatial.

Spectral Quality | Spatial Quality | Global Quality | Borda Count Rank | ||||||
---|---|---|---|---|---|---|---|---|---|

SAM | Spectral ERGAS | Spatial ERGAS | FC | Zhou | Q8 | Global | Spec. | Spat. | |

FIHS | 3.78 | 1.68 | 0.89 | 0.84 | 0.72 | 0.90 | 13 | 4 | 6 |

HCS | 3.52 | 0.39 | 0.91 | 0.77 | 0.67 | 0.93 | 14 | 7 | 2 |

MTF_GLP_HPM | 3.87 | 0.33 | 0.89 | 0.81 | 0.71 | 0.92 | 16 | 6 | 4 |

WAT⊗FRAC | 4.19 | 1.44 | 0.82 | 0.86 | 0.89 | 0.90 | 17 | 3 | 8 |

**Table 5.**Quality results for the complete WV-2 bands and the coastal ecosystem (best results in bold). SAM: spectral angle mapper; FC: frequency comparison; Spec.: spectral; Spat.: spatial.

Spectral Quality | Spatial Quality | Global Quality | Borda Count Rank | ||||||
---|---|---|---|---|---|---|---|---|---|

SAM | Spectral ERGAS | Spatial ERGAS | FC | Zhou | Q8 | Global | Spec. | Spat. | |

FIHS | 1.77 | 2.91 | 2.36 | 0.85 | 0.83 | 0.98 | 19 | 8 | 7 |

HCS | 1.81 | 1.73 | 2.64 | 0.64 | 0.71 | 0.98 | 10 | 15 | 2 |

MTF_GLP_HPM | 1.64 | 1.22 | 2.61 | 0.72 | 0.73 | 0.98 | 17 | 18 | 4 |

WAT⊗FRAC | 1.93 | 2.63 | 2.54 | 0.78 | 0.88 | 0.98 | 14 | 15 | 7 |

**Table 6.**Quality results for the complete WV-2 bands and the mixed ecosystem (best results in bold). SAM: spectral angle mapper; FC: frequency comparison; Spec.: spectral; Spat.: spatial.

Spectral Quality | Spatial Quality | Global Quality | Borda Count Rank | ||||||
---|---|---|---|---|---|---|---|---|---|

SAM | Spectral ERGAS | Spatial ERGAS | FC | Zhou | Q8 | Global | Spec. | Spat. | |

FIHS | 7.11 | 2.98 | 2.08 | 0.89 | 0.73 | 0.93 | 12 | 2 | 6 |

HCS | 5.66 | 1.73 | 2.23 | 0.80 | 0.61 | 0.96 | 13 | 6 | 2 |

MTF_GLP_HPM | 5.62 | 1.72 | 2.23 | 0.81 | 0.61 | 0.96 | 17 | 8 | 4 |

WAT⊗FRAC | 6.88 | 2.85 | 2.05 | 0.93 | 0.98 | 0.95 | 18 | 4 | 8 |

**Table 7.**Quality results for Bands 1–8 using the best algorithms for each scene. Best results are in bold.

Q8, Block Size: 64 | Shrubland Ecosystem | Coastal Ecosystem | Mixed Ecosystem |
---|---|---|---|

Q8 Value for WAT⊗FRAC_w7 | Q8 Value for FIHS | Q8 value for WAT⊗FRAC_15 | |

B1 (Coastal Blue) | 0.696 | 0.764 | 0.695 |

B2 (Blue) | 0.736 | 0.889 | 0.842 |

B3 (Green) | 0.878 | 0.936 | 0.905 |

B4 (Yellow) | 0.904 | 0.647 | 0.890 |

B5 (Red) | 0.872 | 0.410 | 0.851 |

B6 (Red Edge) | 0.897 | 0.395 | 0.857 |

B7 (NIR 1) | 0.841 | 0.318 | 0.845 |

B8 (NIR 2) | 0.881 | 0.239 | 0.832 |

Classification Techniques | Support Vector Machine | |
---|---|---|

Pansharpening Algorithms | Overall Accuracy | Kappa |

MS | 80.61% | 0.72 |

FIHS | 83.72% | 0.76 |

HCS | 82.72% | 0.75 |

MTF_GLP_HPM | 83.18% | 0.75 |

WAT⊗FRAC | 89.39% | 0.85 |

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Ibarrola-Ulzurrun, E.; Gonzalo-Martin, C.; Marcello-Ruiz, J.; Garcia-Pedrero, A.; Rodriguez-Esparragon, D.
Fusion of High Resolution Multispectral Imagery in Vulnerable Coastal and Land Ecosystems. *Sensors* **2017**, *17*, 228.
https://doi.org/10.3390/s17020228

**AMA Style**

Ibarrola-Ulzurrun E, Gonzalo-Martin C, Marcello-Ruiz J, Garcia-Pedrero A, Rodriguez-Esparragon D.
Fusion of High Resolution Multispectral Imagery in Vulnerable Coastal and Land Ecosystems. *Sensors*. 2017; 17(2):228.
https://doi.org/10.3390/s17020228

**Chicago/Turabian Style**

Ibarrola-Ulzurrun, Edurne, Consuelo Gonzalo-Martin, Javier Marcello-Ruiz, Angel Garcia-Pedrero, and Dionisio Rodriguez-Esparragon.
2017. "Fusion of High Resolution Multispectral Imagery in Vulnerable Coastal and Land Ecosystems" *Sensors* 17, no. 2: 228.
https://doi.org/10.3390/s17020228