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甘南州高寒天然草地生长状况遥感监测
引用本文:陆荫,杨淑霞,李晓红. 甘南州高寒天然草地生长状况遥感监测[J]. 草业科学, 2021, 38(1): 32-43. DOI: 10.11829/j.issn.1001-0629.2020-0092
作者姓名:陆荫  杨淑霞  李晓红
作者单位:甘肃省环境监测中心站,甘肃,兰州,730020
摘    要:以甘南州高寒天然草地为研究对象,利用2016−2019年草地地上生物量实测数据和MOD13Q1植被指数产品,构建了甘南州草地地上生物量遥感反演模型,分析了近20年(2000−2019年)甘南州高寒天然草地地上生物量的时空分布特征。结果表明:1) MODIS EVI植被指数适宜于甘南州高寒天然草地地上生物量变化监测研究,...

关 键 词:草地地上生物量  植被指数  变化趋势  高寒天然草地  甘南州  时空分布  遥感反演模型

Monitoring of grassland herbage accumulation by using remote sensing in Gannan Prefecture
LU Yin,YANG Shuxia,LI Xiaohong. Monitoring of grassland herbage accumulation by using remote sensing in Gannan Prefecture[J]. Pratacultural Science, 2021, 38(1): 32-43. DOI: 10.11829/j.issn.1001-0629.2020-0092
Authors:LU Yin  YANG Shuxia  LI Xiaohong
Abstract:This study focuses on grasslands in the Gannan Prefecture, we used the measured data of aboveground grassland biomass (AGB) and the MOD13Q1 vegetation index product from 2016 to 2019, to construct a remote sensing inversion model of grassland AGB, and further analyzed the characteristics of temporal and spatial changes in the grassland AGB in the last 20 years (from 2000 to 2019). The results showed that: 1) Our moderate resolution imaging spectroradiometer enhanced vegetation index (MODIS EVI) is suitable for grassland biomass inversion (R2 = 0.524 9, RMSE = 527.9 kg·ha?1). 2) In the past 20 years, the alpine meadows and mountain meadows showed an increasing trend, while swamp AGB decreased. 3) In the past 20 years, the grasslands in Gannan Prefecture showed a trend towards partial deterioration; the overall trend for grassland vegetation in Gannan Prefecture was positive, 66.04% of the grassland showed a trend of stabilization or recovery, 33.96% of the grassland AGB decreased, and 18.08% of the grasslands showed a continuous deterioration trend. The study results provide data support for Gannan Prefecture grassland vegetation dynamic monitoring and alpine grassland degradation restoration.
Keywords:aboveground biomass  vegetation index  variation trend  alpine natural grassland  Gannan?Prefecture  spatial and temporal distribution  remote?sensing?inversion model
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