Update README.md

README.md

@@ -22,7 +22,7 @@ task_categories:
 This dataset contains optical and SAR images from Sentinel-2 and Sentinel-1.
 
 ### Optical image  
-
+The Optical images were acquired from the Sentinel-2 satellite.
 ### SAR image   
 The SAR images were acquired from the Sentinel-1 satellite. Specifically, the Interferometric Wide Swath (IW) mode with a pixel size of 10 meters was used, incorporating both Vertical-Vertical (VV) and Vertical-Horizontal (VH) polarizations.The Sentinel-1 data underwent preprocessing in SNAP software, including orbit correction, thermal noise removal, radiometric calibration, and terrain correction. Finally, the data were resampled to a resolution of 10 m × 10 m to align with the selected Sentinel-2 spectral bands. 
 
@@ -32,43 +32,30 @@ The SAR images were acquired from the Sentinel-1 satellite. Specifically, the In
 
 | Property             | Description                             |
 |----------------------|-----------------------------------------|
-| Source               | Landsat-8 Satellite                     |
-| Spectral Bands       | Red, Green, Blue (RGB composite)        |
-| Spatial Resolution   | 30 meters                               |
-| Image Patch Size     | 256 × 256 pixels                        |
-| Total Image Pairs    | 683                                     |
-| Preprocessing        | Georeferenced and Cropped               |
-
----
-
-## Data Construction and Patch Sampling
+| Source               | Sentinel-1 Satellite、Sentinel-2 satellite|
+| Spatial Resolution   | 10 meters                               |
+| Image Patch Size     | 224 × 224 pixels                        |
+| Total Image Pairs    | 1286                                    |
 
-To construct a high-quality glacier change detection dataset, we first collected bi-temporal Landsat-8 imagery covering polar regions, with an original size of 8541 × 8601 pixels and a spatial resolution of 30 meters. To focus on glacier-dominated areas and exclude irrelevant background, we manually selected and cropped a subregion of 5109 × 4801 pixels. A sliding window approach with a patch size of 256 × 256 pixels and a stride of 128 pixels was then applied, resulting in 683 bi-temporal image pairs. This number is determined by the spatial extent of the region and the patch extraction strategy.
-
-The choice of 256×256 resolution was a trade-off between spatial detail and computational efficiency. Larger patches (e.g., 512×512) were avoided because they require significantly more GPU memory, reduce training speed, and tend to include a higher proportion of unchanged areas. This can lead to class imbalance, increasing the number of negative samples and causing the model to favor “no-change” predictions, ultimately lowering recall rate. In contrast, 256-sized patches ensure sufficient contextual information while maintaining a more balanced representation of change and no-change areas, thereby supporting more effective learning.
-
----
 
 ## Dataset Structure and File Organization
 
-The dataset is organized into paired folders for bitemporal image patches and corresponding change labels:
+The dataset is organized into paired folders for image patches and corresponding labels:
 ```
--Glacier-Dataset/
-├── A/ (earlier timepoint)
-│ ├── 1_1_1.png
-│ ├── 1_1_2.png
+-Glacier-Dataset/LandSea
+├── opts/ (optical image)
+│ ├── 1_1.tif
+│ ├── 1_2.tif
 │ └── ...
-├── B/ (later timepoint)
-│ ├── 1_1_1.png
-│ ├── 1_1_2.png
+├── sars/ (SAR image)
+│ ├── 1_1_0.tif
+│ ├── 1_1_1.tif
+│ ├── 1_2_0.tif
+│ ├── 1_2_1.tif
 │ └── ...
 ├── labels/
-│ ├── 1_1_1.png
-│ ├── 1_1_2.png
-│ └── ...
-├── samples/
-│ ├── greenland_A.png
-│ ├── greenland_B.png
+│ ├── 1_1.tif
+│ ├── 1_2.tif
 │ └── ...
 └── README.md
 ```