A dataset of temporal-spatial FVC in the Ring Tarim Basin from 1990 to 2021

Yiming Feng, Kun Qiao, Shiang Feng, Lei Xi, Zhao Qi, Lan Lan
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Abstract

The Tarim Basin is an area with extremely fragile ecology and severe desertification subject to the ravages of human activities. As an important index of desertification monitoring, vegetation coverage can well reflect the luxuriant degree of surface vegetation. The monitoring of regional vegetation coverage is the basis of mastering the dynamic change of desertification and analyzing the causes of desertification. Using LANDSAT vegetation growth season (April-October) images from 1990 to 2021 as data sources, we obtained seven vegetation coverage data sets from 1990 to 2021 in the Ring Tarim Basin based on GEE remote sensing cloud platform. We intercepted the upper and lower thresholds of NDVI by adopting 0.5% confidence level to get the NDVI values of pure vegetation cover pixels and pure soil cover pixels, so as to remove the effect of the interannual climate differences on vegetation coverage calculation, and ensure the consistency in the calculation of vegetation coverage for each year. The observation work was carried out in 109 UAV orthorectified sample plots. In the following of data pre-processing, we obtained FVC values as validation samples by using a combined algorithm (vegetation index method and Otsu algorithm). The precision of the dataset is R2 = 0.79 and the linear expression is y = 0.8126x - 0.0267. This dataset can provide data support for the research of desertification change and driving mechanism.
1990 - 2021年塔里木环盆地植被覆盖度时空数据集
塔里木盆地是一个生态极其脆弱、沙漠化严重、人类活动肆虐的地区。植被覆盖率作为荒漠化监测的重要指标,可以很好地反映地表植被的茂盛程度。区域植被覆盖率监测是掌握荒漠化动态变化、分析荒漠化成因的基础。基于GEE遥感云平台,以1990~2021年的LANDSAT植被生长季(4~10月)图像为数据源,获得了环塔里木盆地1990~2021年间的7个植被覆盖数据集。我们采用0.5%的置信水平截取NDVI的上下限,得到纯植被覆盖像素和纯土壤覆盖像素的NDVI值,以消除年际气候差异对植被覆盖计算的影响,确保每年植被覆盖率计算的一致性。观测工作在109个无人机正射校正样本区进行。在接下来的数据预处理中,我们使用组合算法(植被指数法和Otsu算法)获得FVC值作为验证样本。数据集的精度为R2=0.79,线性表达式为y=0.8126x-0.0267。该数据集可以为荒漠化变化及其驱动机制的研究提供数据支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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