黄河三角洲典型盐沼植被时空分布数据集(1999-2020)研发

Development of a Dataset of the Spatial-temporal Distribution of Typical Salt Marsh Vegetation in the Yellow River Delta(1999-2020)

以盐地碱蓬、芦苇、互花米草为代表的黄河三角洲典型盐沼植被,在维持生物多样性、提供重要栖息地、降低暴雨径流、调节气候等方面提供多种生态服务功能。研究其分布和演替趋势对整个生态系统的结构保护与管理具有重要意义。本数据集在黄河三角洲开展研究,基于GoogleEarthEngine(GEE)大数据平台,利用1999-2020年2,068景LandsatTM/ETM/OLI、Sentinel-2 MSI光学数据和Sentinel-1 SAR雷达数据,结合盐沼植被的物候季相特征,构建全生长期的多特征空间。利用递归特征消除的特征优选算法筛选出最佳特征组合,利用随机森林算法进行1999-2020年黄河三角洲典型盐沼植物种群的分类,进一步分析获得典型盐沼植被时空分布数据集。该数据集覆盖区域为黄河三角洲河口湿地,栅格数据空间分辨率分别为10 m。数据存储为.tif格式,共包含64个数据文件,数据量为172 MB(压缩为1个文件,31.7 MB)。

The typical salt marsh vegetation in the Yellow River Delta,which is represented by Suaeda salsa,Phragmites australis,and Spartina alterniflora,provides a variety of ecological services such as maintaining biodiversity,providing important habitats,reducing storm runoff,and regulating the climate.The study of its distribution and succession is of great significance for the conservation and management of the entire ecosystem.A dataset of the typical salt marsh vegetation in the Yellow River Delta was created and analyzed.Based on 2,068 Landsat TM/ETM/OLI,Sentinel-2 MSI optical data,and Sentinel-1 SAR data from 1999 to 2020,a comprehensive set of salt marsh vegetation features during the entire growth period was constructed used the Google Earth Engine platform.The best feature combination was selected using the recursive feature elimination feature optimization algorithm and was applied in a random forest classification model to obtain the final map.Then,the spatial-temporal distribution dataset of typical salt marsh vegetation was analyzed.The dataset mainly covers the estuarine wetlands of the Yellow River Delta,with spatial resolutions of 10 m and 30 m.The data storage is in.tif format,and the projection coordinate system is WGS_1984_UTM_Zone_50N.It contains 16 data files,and the amount of data is 172 MB(compressed to a single file,31.7 MB).