{"title":"A dataset of 250m-resolution NDVI of spatio-temporal variations of vegetation in the growing season on the Mongolian Plateau (2001–2021)","authors":"","doi":"10.11922/11-6035.csd.2022.0058.zh","DOIUrl":null,"url":null,"abstract":"The Mongolian Plateau has a great impact on the ecological security in northern China. Vegetation has an important indicator effect on climate change and ecological environment. The spatial-temporal pattern and trend of vegetation are important indicators for evaluating regional ecological conditions. Based on MOD13Q1 NDVI data, we used R language to call Google Earth Engine service for monthly maximum synthesis in this study. And we then used R language terra package to complete the annual mean synthesis of the growing season, coefficient of variation calculation, Theil-Sen median trend analysis, Mann-Kendall test and Hurst index calculation, so as to form a dataset of 250m-resolution NDVI of spatio-temporal variations of vegetation in the growing season on the Mongolian Plateau (2001–2021). The dataset contains the spatial and temporal variation patterns and trend characteristics of vegetation on the Mongolian Plateau. Through data sharing, it can provide data support for scientific understanding of temporal and spatial variation of vegetation cover on the Mongolian Plateau.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"China Scientific Data","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.11922/11-6035.csd.2022.0058.zh","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The Mongolian Plateau has a great impact on the ecological security in northern China. Vegetation has an important indicator effect on climate change and ecological environment. The spatial-temporal pattern and trend of vegetation are important indicators for evaluating regional ecological conditions. Based on MOD13Q1 NDVI data, we used R language to call Google Earth Engine service for monthly maximum synthesis in this study. And we then used R language terra package to complete the annual mean synthesis of the growing season, coefficient of variation calculation, Theil-Sen median trend analysis, Mann-Kendall test and Hurst index calculation, so as to form a dataset of 250m-resolution NDVI of spatio-temporal variations of vegetation in the growing season on the Mongolian Plateau (2001–2021). The dataset contains the spatial and temporal variation patterns and trend characteristics of vegetation on the Mongolian Plateau. Through data sharing, it can provide data support for scientific understanding of temporal and spatial variation of vegetation cover on the Mongolian Plateau.