A dataset of water bodies on the saline-alkali land in western Songnen Plain from 2016 to 2023

<p indent="0mm">Due to natural and anthropogenic factors, western Songnen Plain has vast areas of saline-alkaline land, making it one of the world’s three major distribution areas of soda saline-alkaline land. Water resources play a crucial role in both human production and living activities and the natural environment, and this is especially true for the ecologically fragile saline-alkali land in western Songnen Plain. In this paper, we used Sentinel-2A/B MSI data on the Google Earth Engine (GEE) platform as the data source, selected the sample points extracted from the water bodies in western Songnen Plain. Then, we used Random Forest Classification to produce a dataset of monthly water bodies and generate the water body frequency data in western Songnen Plain from 2016 to 2023. Since the atmospherically corrected Level-2A did not cover the study area prior to 2019, the Level-2A data product was used for the period from 2019 to 2023. For the years 2016–2018, the corrected atmospheric apparent reflectance data product Level-1C was used as a supplement. After comparing the results of simultaneous data extraction, the use of Level-1C data product to supplement the missing timeframe of Level-2A data product had little effect on the classification results of water bodies. The overall accuracy of the random forest model classification in this study was 91.96%, and the kappa coefficient was 0.9128. This indicates that the dataset is highly accurate and reliable. The dataset can provide data support for water resource monitoring, saline-alkali land management, and the evaluation and promotion of efficient management models for saline -alkali in western Songnen Plain.