Update README.md

README.md

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 ### 1.1. Overview
 
-This dataset provides a curated collection of multi-sensor, multi-temporal image patches focusing exclusively on agricultural land across China in 2021. The dataset contains Sentinel-1 (Sentinel-1 SAR GRD: C-band Synthetic Aperture Radar Ground Range Detected, log scaling) and Sentinel-2 (Harmonized Sentinel-2 MSI: MultiSpectral Instrument, Level-2A (SR)) imagery covering China where cropland pixel percentage is no less than 80%. Sentinel-2 images are in area of 2640 m * 2640 m. Pixel dimensions are slightly greater than 264 * 264 dependding on their geolocation. Sentinel-1 images are standardized to a uniform pixel dimension 264*264 and a consistent Coordinate Reference System (CRS) for time-series analysis. The data acquisition is governed by a rigorous workflow designed to maximize geometric and temporal consistency across four key seasonal stages.
+This project is inspired by Copernicus-Pretrain dataset (https://huggingface.co/datasets/wangyi111/Copernicus-Pretrain). However, we only focus on cropland. This dataset provides a curated collection of multi-sensor, multi-temporal image patches focusing exclusively on agricultural land across China in 2021. The dataset contains Sentinel-1 (Sentinel-1 SAR GRD: C-band Synthetic Aperture Radar Ground Range Detected, log scaling) and Sentinel-2 (Harmonized Sentinel-2 MSI: MultiSpectral Instrument, Level-2A (SR)) imagery covering China where cropland pixel percentage is no less than 80%. Sentinel-2 images are in area of 2640 m * 2640 m. Pixel dimensions are slightly greater than 264 * 264 dependding on their geolocation. Sentinel-1 images are standardized to a uniform pixel dimension 264*264 and a consistent Coordinate Reference System (CRS) for time-series analysis. The data acquisition is governed by a rigorous workflow designed to maximize geometric and temporal consistency across four key seasonal stages.
 
 ### 1.2. Data Sources