首页> 中文期刊>西北师范大学学报(自然科学版) >基于HA N TS算法的疏勒河流域荒漠化时空动态监测

基于HA N TS算法的疏勒河流域荒漠化时空动态监测

     

摘要

以干旱区内陆疏勒河流域为研究区,先应用HANTS算法对时间序列植被指数进行去噪和重构,再分别利用一元线性回归分析法和扰动指数算法对土地荒漠化的空间分布规律和时间变化规律进行研究.结果表明,HANTS算法能有效地对时间序列植被指数数据集进行平滑和滤波,降低噪声的影响,重新构建吻合疏勒河流域植被物候特征的时间序列植被指数数据集;该流域土地荒漠化状况总体趋于改善,荒漠化空间分布主要呈现南部上游山区显著改善,中部中下游平原轻微改善,北部马鬃山山区重度恶化的规律;该流域荒漠化时间变化呈现不规则的微小波动,且与空气相对湿度变化存在显著的负相关关系.%Harmonic analysis of time series(HANTS)was applied to reduce noise in MOD13Q1 time series data from 2000 to 2016.Base on the restructured MOD13Q1 time series data,temporal and spatial dynamic changes of desertification in Shule River Basin were studied by applying unary linear regression analysis and disturbance index algorithm.The study found that HANTS smooths and filters IEVtime series data effectively.The condition on desertification in the upstream area is improving,while the conditions is getting worse in Mazong Mountain area,and the condition is changing slightly in middle and dow nstream area.The temporal changes of desertification fluctuates smoothly in some ranges,and a significant negative correlation is found between temporal changes of desertification and relative air humidity.

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