Exploring the Dunes: The Correlations between Vegetation Cover Pattern and Morphology for Sediment Retention Assessment Using Airborne Multisensor Acquisition
Abstract
:1. Introduction
2. Study Area
3. Materials and Methods
3.1. Materials
3.1.1. Airborne LIDAR Altimeter
3.1.2. Hyperspectral Airborne Imagery
3.1.3. Field Measurements
3.2. Methodology
- -
- step 1, a discrete pixel-based analysis to explore the whole system metrics and behavior. The processing is based on the algorithm named ‘FHyL (Field spectral libraries, airborne Hyperspectral images and LiDAR altimetry) module 3’, an algorithm comprising four main modules and two pre-processing steps: Each module differs according to the analyzed coastal sphere, i.e., the terrestrial or the aquatic, and according to the sensors’ data integration sequence [31,45];
- -
- step 2, a continuous lag-based analysis to explore the relationships between landscape cover and geomorphology;
- -
- step 3, a correlation analysis.
3.2.1. Step 1: Discrete Pixel-based Analysis
3.2.2. Step 2: Continuous Lag-Based Analysis
3.2.3. Step 3: Correlation Analysis between Landform and Landscape Metrics
4. Results
4.1. Step 1 and Step 2: Dune Morphology
4.2. Step 1 and Step 2: Dune Cover Patterns
4.3. Step 3: Dune Landforms and Landscape Correlations
5. Discussion
6. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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LiDAR HawkEye II | |
---|---|
Topographic Frequency | 64,000 Hz |
Altitude | From 250 to 500 m |
Swath | From 100 to 330 m |
Topographic point density | From 1 to 4 points for m2 |
Accuracy of Topographic survey | Horizontal: ±0.5 m (Vertical: ±0.15 m |
MIVIS – Multispectral Infrared Visible Imaging Spectrometer | ||
---|---|---|
Wavelength (μm) | Spectral resolution (μm) | |
Spectrometer I, VIS | 0.4–0.8 | 0.2 in 20 bands |
Spectrometer II, NIR | 1.2–1.5 | 0.5 in 8 bands |
Spectrometer III, MIR | 2.0–2.5 | 0.09 in 64 bands |
Spectrometer IV, TIR | 8.2–12.7 | 3.4–5.4 in 10 bands |
scan/s 25 (1500 m flight altitude) | 3 × 3 m spatial resolution | |
Digital accuracy | 12 bit × pixel, ±1 bit |
Primary Parameter (units) | How to Calculate |
---|---|
Slope (deg) | Maximum change in elevation over the distance between the cell and its eight neighbors |
Crest (m) | Maximum of dune ridge elevation |
Foot (m) | Foot results from defining a threshold on the slope |
Width (m) | By using the horizontal plane referred to mean sea level for the following distances: from the shoreline to the foredune foot (beach) from the foredune foot to the crest (foredune) from the crest to the hind dune foot (hind dune) from the foredune foot to the hind dune foot (dune) |
Profile underlying the surface (m2) | The signed area, bounded by the elevation profile of each transect, corresponds to the integral of the elevation profile. Each profile has been separately calculated along the transect for the beach, foredune, and hind dune |
Fractional Abundances (%) | Combining a maximum likelihood classification (MLL) and a linear spectral mixing analysis (LSMA) |
Detailed cover map (classified map) | Using a decision tree to apply a threshold on fractional abundances (fraction > 60%) |
Primary Parameter (unit) | How to Calculate (in the Moving Window) |
---|---|
Elevation (m) | As average value |
Sinuosity | As average value of the crest and foot lines |
Width (m2) | As average value |
Profile underlying surface | As average value of the elevation profiles’ integrals |
Cover percentage (%) | Cover percentage referred to the window extent |
Edge Density (ED) | Edge density of the cover patches. It standardizes the edge to a per-unit-area basis that facilitates comparisons among landscapes of varying size. |
Landscape Shape Index (LSI) | Measure of the perimeter-to-area ratio for the whole landscape. The minimum value of LSI is always equal to 1 when the landscape consists of a single patch. |
Mean fractal dimension | Fractal dimension of each patch |
Aggregation index | The ratio of the observed number of like adjacencies to the maximum possible number of like adjacencies given the proportion of the landscape comprising each patch type, given as a percentage. |
Effective mesh size | Mesh size refers to the cumulative patch area distribution and is the size of the patches when the corresponding patch type is subdivided into S patches, where S is the value of the splitting index. |
Patch Cohesion Index (PCI) | Measures of the connectivity of patch typologies. It takes into account the number of patches, the surface, and its perimeter |
Distance along Stretch (km) | Foredune Width (m) | Hind dune Width (m) | Beach Width (m) | Profile Underlying the Surface (m2) | Elevation (m) |
---|---|---|---|---|---|
1.5 | 25.4 | 100 | 29.7 | 581.6 | 4.1 |
4.5 | 36.0 | 89.5 | 12.7 | 868.0 | 4.2 |
7.5 | 21.2 | 28 | 42.4 | 410.5 | 5.0 |
10.5 | 41.5 | 70.6 | 23.1 | 1313.1 | 4.9 |
13.5 | 86.7 | 27.5 | 26.8 | 9143.5 | 7.7 |
16.5 | 36.0 | 203.7 | 26.1 | 1111.5 | 5.3 |
19.5 | 98.5 | 124.6 | 30.7 | 12,492.4 | 11.4 |
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Valentini, E.; Taramelli, A.; Cappucci, S.; Filipponi, F.; Nguyen Xuan, A. Exploring the Dunes: The Correlations between Vegetation Cover Pattern and Morphology for Sediment Retention Assessment Using Airborne Multisensor Acquisition. Remote Sens. 2020, 12, 1229. https://doi.org/10.3390/rs12081229
Valentini E, Taramelli A, Cappucci S, Filipponi F, Nguyen Xuan A. Exploring the Dunes: The Correlations between Vegetation Cover Pattern and Morphology for Sediment Retention Assessment Using Airborne Multisensor Acquisition. Remote Sensing. 2020; 12(8):1229. https://doi.org/10.3390/rs12081229
Chicago/Turabian StyleValentini, Emiliana, Andrea Taramelli, Sergio Cappucci, Federico Filipponi, and Alessandra Nguyen Xuan. 2020. "Exploring the Dunes: The Correlations between Vegetation Cover Pattern and Morphology for Sediment Retention Assessment Using Airborne Multisensor Acquisition" Remote Sensing 12, no. 8: 1229. https://doi.org/10.3390/rs12081229