DOI: 10.57760/sciencedb.33612
title: Global 1km Resolution 2000-2024 Annual Maximum Composite Normalized Difference Vegetation Index (NDVI) Dataset
title: 全球1km分辨率2000-2024逐年最大值合成归一化植被指数（NDVI）数据集

description:  The Normalized Difference Vegetation Index (NDVI), a classic indicator of vegetation photosynthetic activity, is uniquely sensitive to changes in chlorophyll content. This study, based on the MODIS MOD13A2 061 data product, uses the Google Earth Engine cloud platform to implement maximum value composite, projection transformation, and time series analysis of NDVI data at 1 km resolution. The coefficient of variation (CV) is used to detect the dispersion of the data, and the Sen-Median trend analysis is combined for bilateral trend detection to analyze the degree of data change, along with Hurst index calculation. A global maximum value composite NDVI change dataset for 2000–2024 was constructed. This dataset can provide fundamental data support for research such as carbon cycle modeling and drought monitoring.The dataset includes four compressed files: (1) Global 1 km Resolution Annual Maximum Composite NDVI Data (2000-2024).zip, containing 25 TIFF files named NDVI_1000M_Year.tif, with a data size of 27.0 GB (unzipped); (2) Global 1 km Spatial Resolution Annual Maximum Composite NDVI Spatiotemporal Variation Patterns.zip, which contains annual vegetation change trend (Global_NDVI_Trend.tif), significance information (Ndvi_Max_z.tif), and trend significance results (NDVI_T-S_Significance.tif), with a data size of 4.62 GB (unzipped); (3) Global 1 km Resolution Annual Maximum Composite NDVI Spatial Variability Feature Data.zip, which contains vegetation change variability feature (Global_NDVI_CV.tif), with a data size of 726 MB (unzipped); (4) Global 1 km Resolution Annual Maximum Composite NDVI Persistence Data.zip, which contains vegetation change persistence detection results (Global_NDVI_Hurst.tif), with a data size of 723 MB (unzipped).
description:  The Normalized Difference Vegetation Index (NDVI), a classic indicator of vegetation photosynthetic activity, is uniquely sensitive to changes in chlorophyll content. This study, based on the MODIS MOD13A2 061 data product, uses the Google Earth Engine cloud platform to implement maximum value composite, projection transformation, and time series analysis of NDVI data at 1 km resolution. The coefficient of variation (CV) is used to detect the dispersion of the data, and the Sen-Median trend analysis is combined for bilateral trend detection to analyze the degree of data change, along with Hurst index calculation. A global maximum value composite NDVI change dataset for 2000–2024 was constructed. This dataset can provide fundamental data support for research such as carbon cycle modeling and drought monitoring.The dataset includes four compressed files: (1) Global 1 km Resolution Annual Maximum Composite NDVI Data (2000-2024).zip, containing 25 TIFF files named NDVI_1000M_Year.tif, with a data size of 27.0 GB (unzipped); (2) Global 1 km Spatial Resolution Annual Maximum Composite NDVI Spatiotemporal Variation Patterns.zip, which contains annual vegetation change trend (Global_NDVI_Trend.tif), significance information (Ndvi_Max_z.tif), and trend significance results (NDVI_T-S_Significance.tif), with a data size of 4.62 GB (unzipped); (3) Global 1 km Resolution Annual Maximum Composite NDVI Spatial Variability Feature Data.zip, which contains vegetation change variability feature (Global_NDVI_CV.tif), with a data size of 726 MB (unzipped); (4) Global 1 km Resolution Annual Maximum Composite NDVI Persistence Data.zip, which contains vegetation change persistence detection results (Global_NDVI_Hurst.tif), with a data size of 723 MB (unzipped).