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基于多源数据的天山北坡典型草地植被覆盖度遥感反演与变化特征研究

艾尼玩·艾买尔 布苏丽坦·奥斯曼 阿仁 阿斯娅·曼力克 李晓敏 贠静 塞米热·吾斯曼 玉素甫江·如素力

草食家畜Issue(2):51-63,13.
草食家畜Issue(2):51-63,13.DOI:10.16863/j.cnki.1003-6377.2026.02.006

基于多源数据的天山北坡典型草地植被覆盖度遥感反演与变化特征研究

Remote Sensing Inversion and Change Characteristics of Vegetation Coverage in Typical Grasslands on the Northern Slope of the Tianshan Mountains Based on Multi-Source Data

艾尼玩·艾买尔 1布苏丽坦·奥斯曼 2阿仁 1阿斯娅·曼力克 1李晓敏 1贠静 1塞米热·吾斯曼 3玉素甫江·如素力2

作者信息

  • 1. 新疆畜牧科学院草业研究所,新疆 乌鲁木齐 830011||新疆畜牧科学院天山北坡草地生态环境野外定位观测研究站,新疆 乌鲁木齐 830011
  • 2. 新疆师范大学地理科学与旅游学院,新疆 乌鲁木齐 830017
  • 3. 新疆畜牧科学院天山北坡草地生态环境野外定位观测研究站,新疆 乌鲁木齐 830011
  • 折叠

摘要

Abstract

[Objective]This study aimed to construct remote sensing inversion models for typical grassland vegetation coverage based on multi-source remote sensing data including UAV imagery,Landsat 8 OLI,and Sentinel-2.[Methods]Combining vegetation indices such as NDVI,MSAVI,RVI and PVI,the inversion models were optimized using pixel binary model,generalized linear regression,and random forest regression method.[Results]For the inversion accuracy in non-growing season:the MSAVI regression model achieved an R² of 0.78 with an RMSE of 6.4%.After random forest optimization,the R² of the ensemble model(MSAVI+PVI)increased to 0.83 and RMSE dropped to 5.8%,significantly enhancing the identification capability for low-coverage grasslands.For the comparison of inversion accuracy in growth season:Sentinel-2 data outperformed Landsat 8 OLI in accuracy,with its random forest model achieving an R² of 0.821 versus Landsat 8 OLI's 0.794.Support Vector Machine(SVM)model demonstrated optimal performance,with SVM-RF(random forest feature selection)achieving and R² of 0.856 and an RMSE of 4.2%on Sentinel-2 data,a 12.3%improvement over the traditional method.For the spatio-temporal variation characteristics:the grassland coverage showed an overall decline from 2019 to 2024,with high-coverage areas(>60%)decreasing by 23.5%,low-coverage areas(25%to 35%)increasing by 18.7%,and medium-coverage areas(40%to 50%)rising by 11.2%.[Conclusion]The inversion accuracy of grassland coverage in arid regions can be enhanced by multi-source data fusion and machine learning algorithms.Data support was provided by the study for ecological monitoring and degradation management.

关键词

植被覆盖度/多源数据/机器学习/遥感反演/天山北坡

Key words

vegetation coverage/multi-source data/machine learning/remote sensing inversion/northern slope of the Tianshan Mountains

分类

农业科技

引用本文复制引用

艾尼玩·艾买尔,布苏丽坦·奥斯曼,阿仁,阿斯娅·曼力克,李晓敏,贠静,塞米热·吾斯曼,玉素甫江·如素力..基于多源数据的天山北坡典型草地植被覆盖度遥感反演与变化特征研究[J].草食家畜,2026,(2):51-63,13.

基金项目

中央财政林草科技推广示范项目"退化草原评价与修复治理模式示范与推广项目"(新[2024]TG06号) (新[2024]TG06号)

新疆维吾尔自治区公益性科研院所基本科研业务经费资助项目(ky202480) (ky202480)

草食家畜

1003-6377

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