Data for "Shifts, trends, and drivers of lake color across China since the 1980s"

This dataset includes data and relevant Python scripts used for investigating the shifts, trends, and drivers of lake color in China. Scripts: GEE_ExportChinaLake_SR.py and GEE_pull_functions.py are used for accessing the Landsat SR dataset from the Google Earth Engine Platform. Process_to_CNLakeSR.py:After downloading the exported CSV files to the local directory, we can use the script to generate CNLakeSR dataset mentioned in the paper. GEE_ERA5_grab.txt includes a GEE code link to download ERA-5 data. We also shared ERA-5 data used for our anlaysis here (ERA5_*.csv). Datasets: The dataset for the final analysis is included in Dominant_wavelength_time_series.csv. The trends from M-K analysis is included in MK_trend_wavelength.csv The meteorological dataset of each lake, including air temperature, wind speed, and precipitation from the ERA5 dataset, includes ERA5_*.csv here The annual NDVI time series of each lake in Landsat_mean_ndvi_1984_2021.csv.

本数据集包含用于探究中国湖泊颜色变化、演变趋势及其驱动因子的相关数据与配套Python脚本。
脚本部分：GEE_ExportChinaLake_SR.py与GEE_pull_functions.py用于从谷歌地球引擎（Google Earth Engine，GEE）平台调取Landsat SR（Landsat地表反射率）数据集。Process_to_CNLakeSR.py：将导出的CSV文件下载至本地目录后，即可通过该脚本生成论文中提及的CNLakeSR数据集。GEE_ERA5_grab.txt包含一条用于下载ERA5数据的GEE代码链接，本研究分析所用的ERA5数据已在此处共享，对应文件为ERA5_*.csv。
数据集详情：最终分析所用数据集存储于Dominant_wavelength_time_series.csv文件中；Mann-Kendall（M-K）趋势分析所得的趋势结果存储于MK_trend_wavelength.csv文件中；各湖泊的气象数据集（包含ERA5数据集提供的气温、风速与降水量）对应文件为本次共享的ERA5_*.csv；各湖泊1984年至2021年的年度归一化植被指数（Normalized Difference Vegetation Index, NDVI）时间序列数据存储于Landsat_mean_ndvi_1984_2021.csv文件中。