Update README.md

README.md

@@ -95,8 +95,8 @@ All imagery and canopy height products are **spatially aligned** at **0.5 m reso
 ## ✨ Key Highlights
 - 📊 **Multi-Temporal**: 3 yearly acquisitions (RGB + NIR + NDVI)  
 - 🌈 **Multi-Spectral**: High-resolution optical imagery including RGB, NIR, and derived NDVI  
-- 🌲 **Canopy Height Models (CHM)**: LiDAR-based ALS reference data  
-- 📏 **Resolution**: 0.5 m — among the highest available at continental scale  
+- 🌲 **Canopy Height Models (CHM)**: LiDAR-based data  
+- 📏 **Resolution**: 0.5 m 
 - 🌍 **Coverage**: France-wide dataset with departmental splits  
 - 📦 **Scale**: 785k training patches, ~880 GB of data  
 
@@ -122,7 +122,6 @@ splits:
     num_examples: 785,392
     size: 880 GB
 resolution: 0.5 m
-download_size: 730 GB
 dataset_size: 880 GB
 license: apache-2.0
 ```
@@ -130,7 +129,7 @@ license: apache-2.0
 ---
 
 ## 🔬 Scientific Context
-PrediTree builds on prior canopy height mapping efforts. Compared to single-temporal or coarser-resolution datasets, it is the **first to offer multi-temporal sub-meter CHM-aligned imagery at national scale**.
+PrediTree is the **first CHM dataset to offer multi-temporal sub-meter CHM-aligned imagery**.
 
 ![Comparison with Existing Datasets](./comparison.png)