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Service Description: This dataset provides a 100m resolution mosaic of Sentinel-1 12-day median coherence for the summer season (June–August) of 2019. It was generated from all 12-day image pairs acquired over the study area during this period. Radar coherence is sensitive to changes in surface conditions, including dune migration, vegetation growth, and urban construction. In the mosaic, areas with low coherence (e.g., active dunes) appear darker, while stable surfaces appear brighter. The median coherence provides a robust measure of cumulative surface dynamics across the summer season. The dataset is valuable for investigating dune movement, sand deposition patterns, seasonal landscape variability, and the broader impacts of climate change on desertification processes. Source data are available via the ASF Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter Dataset: https://asf.alaska.edu/datasets/derived/global-seasonal-sentinel-1-interferometric-coherence-and-backscatter-dataset/
A higher-resolution (15m) version of this product, based on Sentinel-1 data from Summer 2021, is also available (see Section 6.6).
Saudi_Dune_Sabkha/Coherence_Median__
Description: This dataset provides a 100m resolution mosaic of Sentinel-1 12-day median coherence for the summer season (June–August) of 2019. It was generated from all 12-day image pairs acquired over the study area during this period. Radar coherence is sensitive to changes in surface conditions, including dune migration, vegetation growth, and urban construction. In the mosaic, areas with low coherence (e.g., active dunes) appear darker, while stable surfaces appear brighter. The median coherence provides a robust measure of cumulative surface dynamics across the summer season. The dataset is valuable for investigating dune movement, sand deposition patterns, seasonal landscape variability, and the broader impacts of climate change on desertification processes. Source data are available via the ASF Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter Dataset: https://asf.alaska.edu/datasets/derived/global-seasonal-sentinel-1-interferometric-coherence-and-backscatter-dataset/
A higher-resolution (15m) version of this product, based on Sentinel-1 data from Summer 2021, is also available (see Section 6.6).
false
Extent:
XMin: 4198650.175700001
YMin: 2019332.8548581954
XMax: 5496778.320255588
YMax: 3227448.8768000007
Spatial Reference: 102100
(3857)
Initial Extent:
XMin: 4198650.175700001
YMin: 2019332.8548581954
XMax: 5496778.320255588
YMax: 3227448.8768000007
Spatial Reference: 102100
(3857)
Full Extent:
XMin: 4198650.175700001
YMin: 2019332.8548581954
XMax: 5496778.320255588
YMax: 3227448.8768000007
Spatial Reference: 102100
(3857)
Pixel Size X: 13.914379751705216
Pixel Size Y: 13.914379751705214
Band Count: 1
Pixel Type: F32
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Mensuration Capabilities: Basic
Inspection Capabilities:
Has Histograms: true
Has Colormap: false
Has Multi Dimensions : false
Rendering Rule:
Min Scale: 0
Max Scale: 0
Copyright Text:
Service Data Type: esriImageServiceDataTypeGeneric
Min Values: 0.01180642907092988
Max Values: 0.9980661573954421
Mean Values: 0.4154157087685947
Standard Deviation Values: 0.3453025767425266
Object ID Field: OBJECTID
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Default Mosaic Method: Northwest
Allowed Mosaic Methods: NorthWest,Center,LockRaster,ByAttribute,Nadir,Viewpoint,Seamline,None
SortField:
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Mosaic Operator: First
Default Compression Quality: 75
Default Resampling Method: Bilinear
Max Record Count: 1000
Max Image Height: 4100
Max Image Width: 15000
Max Download Image Count: 20
Max Mosaic Image Count: 20
Allow Raster Function: true
Allow Copy: true
Allow Analysis: true
Allow Compute TiePoints: false
Supports Statistics: true
Supports Advanced Queries: true
Use StandardizedQueries: true
Raster Type Infos:
Name: Raster Dataset
Description: Supports all ArcGIS Raster Datasets
Help:
Has Raster Attribute Table: false
Edit Fields Info: null
Ownership Based AccessControl For Rasters: null
Child Resources:
Info
Histograms
Statistics
Key Properties
Legend
Raster Function Infos
Supported Operations:
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Query
Identify
Measure
Compute Histograms
Compute Statistics Histograms
Get Samples
Compute Class Statistics
Query GPS Info
Find Images
Image to Map
Map to Image
Measure from Image
Image to Map Multiray
Query Boundary
Compute Pixel Location
Compute Angles
Validate
Project