The study on monitoring the water body range of Baiyangdian and the change of wetland information by means of remote sensing is of great significance to ensure the ecological security of Xiong’an New Area. This paper was conducted using the GF-2 remote sensing data on March and October 2018. The study was to provide an extraction model basing on NDVI-NDWI method, which compare with traditional supervised classification method. The selected sample points by using visual interpretation verified the extracted wetland information. The results show that the classification and extraction of Baiyangdian wetland information are carried out by using the model and supervised classification method respectively, and the wetland area (in which) is obtained in March. The precision of the sample points and the extracted wetland information are all above 90%, and the NDVI-NDWI method is constructed based on the NDVI-NDWI method. The extraction model is more accurate. Since the bare waters in March were 102.31 km2, 28.27 km2 more than in October; the area of aquatic plants extracted in October increased significantly from 122.57 km2 in March to 154.5 km2. It can be seen that the information of Baiyangdian wetland changes with the growth of aquatic plants. The model established by the institute can accurately extract the information of Baiyangdian wetland and provide a scientific reference for the planning and management of Xiong’an New District.

As a regulator of ecological environment, Baiyangdian Wetland is in a pivotal position in constructing the blue-green space (BGS) of Xiong’an New Area in China. This study aims to reveal the spatiotemporal changes of the BGS in Baiyangdian Wetland from 2016 to 2021. It uses Google Earth Engine (GEE) to calculate NDVI and NDWI based on Sentinel-2 Satellite remote sensing data and extracts the blue-green space by a classification model driven by NDVI and NDWI. Moreover, the land-use transfer matrix and landscape pattern indices are applied for evaluating the BGS changes in the wetland. According to the results, vegetation in the wetland shows no obvious spatial transfer. From 2016 to 2020, the BGS proportion in the wetland showed a stable increase, with the blue space getting larger by 10.8%. The indicators of the Number of Patches (NP), Patch Density (PD), Largest Patch Index (LPI), Contagion, and Landscape Shape Index (LSI) of the wetland decreased, suggesting a better ecological environment since the establishment of Xiong’an New Area in 2017. Based on the results, the author makes the following conclusion: the construction of BGS in Baiyangdian Wetland results in a well-organized ecological environment. The study provides a reference for building Xiong’an New Area and monitoring BGS changes in other regions.