Update README.md

README.md

@@ -49,18 +49,18 @@ A detailed description and visualization of each layer are provided below.
 
 ## LiDAR
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/651d578a1819d9e5754ffc47/Fgf8shGa1FP4aAUpFfWb0.png)
-LiDAR layer was created from DEM with 1x1 meter resolution. 
- - The <b>raw</b> folder contains unprocessed input data.
- - The <b>processed</b> folder contains normalized data where minimum value for normalization was set to 0.0 and maximum to the highest point of Biele Karpaty 916.335.
+The LiDAR layer was derived from a Digital Elevation Model (DEM) with a spatial resolution of 1×1 meter. 
+ - The <b>raw</b> folder contains the original, unprocessed elevation data.
+ - The <b>processed</b> folder contains normalized elevation data. Normalization was performed using a minimum value of 0.0 and a maximum value equal to the highest point in the Biele Karpaty region: 916.335 meters.
 
 ## Landslides
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/651d578a1819d9e5754ffc47/pnWHsqUNtcA0rA5GCxGWU.png)
-Landslides layer was created by experts from State Geological Institute of Dionýz Štúr and presents the ground truth. The value one symbolizes the pixel with landslide.
-The <b>raw</b> and the <b>processed</b> folder contains identical data.
+The Landslides layer represents ground truth data, manually annotated by experts from the State Geological Institute of Dionýz Štúr. A pixel value of <b>1</b> indicates the presence of a landslide.
+The data in both the <b>raw</b> and <b>processed</b> folders are identical, as no additional processing was applied to this layer.
 
 ## Curvature
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/651d578a1819d9e5754ffc47/H1r3Gb1Fho2h-Unc7gy6e.png)
-before the calculation of curvature, the DEM was smoothened by kernel of size 3x3 to eliminate the noise. The curvature layer was calculated as follows (see image below for the legend): 
+The Curvature layer was calculated from the DEM after applying a smoothing filter to reduce noise. A 3×3 kernel was used to smooth the DEM before curvature computation. The curvature was computed using the following formula (see accompanying image for the legend):
  - A = (Z1 + Z9) / 2 - Z5
  - B = (Z7 + Z9) / 2 - Z5
  - C = (Z2 + Z8) / 2 - Z5
@@ -68,15 +68,29 @@ before the calculation of curvature, the DEM was smoothened by kernel of size 3x
  - Curvature = A + B + C + D
 
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/651d578a1819d9e5754ffc47/yTA2LxPIXivCDI91R6DlU.png)
-The distance L was set to 10 meters to cover wider area and have smoother output.
- - The <b>raw</b> folder contains the data with the above mentioned formula applied. The edges with artifacts were cropped from dataset. Values above 0 presents convexe surfaces. Values below 0 presents concave surfaces.
- - The data in <b>processed</b> folder were clipped with value +-2 - e.g. the values below -2 were set to -2 and the values above 2 were set to 2. Finally, the data is normalized to values from interval [0, 1] by setting the minimum value to -2 and the maximum to 2.The values below 0.5 then presents concave surfaces and the values above 0.5 presents convexe surfaces.
+A fixed distance L = 10 meters was used to ensure the output captures broader terrain features and appears smoother.
+ - The <b>raw</b> folder contains curvature values directly computed from the formula above.
+   - Edge artifacts were cropped.
+   - Positive values indicate convex surfaces.
+   - Negative values indicate concave surfaces.
+ - The <b>processed</b> folder contains a clipped and normalized version:
+   - Values were clipped to the range [-2, 2].
+   - The clipped values were then normalized to the [0, 1] range using:
+     - Minimum = -2 → maps to 0.0
+     - Maximum = 2 → maps to 1.0
+   - In the normalized data:
+     - Values below 0.5 represent concave surfaces
+     - Values above 0.5 represent convex surfaces
 
 ## Hillshade
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/651d578a1819d9e5754ffc47/sNOv4JhLJA0rvGHYYPtVo.png)
-The hillshade layer was created from DEM by using multidirectional hillshade function in QGIS and by applying 45° vertical angle.
- - The <b>raw</b> folder contains RGB image with pixel values from 0 to 196.
- - The <b>processed</b> folder contains a selected single band from RGB image. CLAHE filter from OpenCV library with clip limit set to 20 and tile grid size set to 8x8 was applied to this band to enhance contrast and the output was normalized to values in interval [0, 1]. 
+The Hillshade layer was generated from the DEM using the multidirectional hillshade function in QGIS, with a 45° vertical angle to simulate natural illumination.
+ - The <b>raw</b> folder contains an RGB image with pixel values ranging from 0 to 196.
+ - The <b>processed</b> folder includes a single selected band extracted from the RGB image. The following enhancements were applied:
+   - CLAHE (Contrast Limited Adaptive Histogram Equalization) filter from the OpenCV library:
+     - Clip limit: 20
+     - Tile grid size: 8×8
+   - The output was then normalized to the [0, 1] interval.
 
 ## NDVI
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/651d578a1819d9e5754ffc47/o0AwliWCg5QA6ZlsRGf99.png)
@@ -84,12 +98,15 @@ TODO
 
 ## Roughness
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/651d578a1819d9e5754ffc47/qcLbwXT_n_uQpywolUX7N.png)
-The roughness layer was created from DEM by using roughness function in QGIS. 
- - The <b>raw</b> folder contains single band data with unchanged values.
- - The <b>processed</b> folder contains the normalized data to interval [0,1]. Before the normalization the clipping limit 20 was set for the maximum value of rughness (values above 20 were set to 20) and the band was tranformed by np.log(roughness_band + 1.0). Minimum was then set to 0 and the maximum to np.log(21).
+The Roughness layer was derived from the DEM using the roughness function in QGIS, which measures the variability of elevation within a local neighborhood.
+ - The <b>raw</b> folder a single-band raster with the original roughness values, unprocessed.
+ - The <b>processed</b> folder contains a normalized version of the data. The following processing steps were applied:
+   - Clipping: Values above 20 were clipped to 20 to reduce the influence of extreme outliers.
+   - Logarithmic transformation: The clipped values were transformed using: np.log(roughness + 1.0)
+   - Normalization: minimum value set to 0, maximum value set to np.log(21), resulting values were scaled to the range [0, 1]
 
 ## Slope
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/651d578a1819d9e5754ffc47/jnLfos8FD2t9-gcvmDtgM.png)
-The slope layer was created from DEM by using slope function in QGIS.
- - The <b>raw</b> folder contains single band data with unchanged values (degrees of slope inclination).
- - The <b>processed</b> folder contains the normalized data to interval [0,1] where the minimum was set to 0 degrees and maximum to 90 degrees.
+The Slope layer was derived from the DEM using the slope function in QGIS, which calculates the steepness of the terrain in degrees.
+ - The <b>raw</b> folder contains a single-band raster with the original slope values expressed in degrees of inclination.
+ - The <b>processed</b> folder contains a normalized version of the data: minimum value set to 0°, maximum value set to 90°, values were scaled linearly to the range [0, 1].