Estimating forest volume in hilly regions with the ALOS PALSAR model’s dual polarization data
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摘要: 合成孔径雷达(SAR)技术以其独特的成像机制及其全天候、全天时成像能力,在森林生物量估测方面发挥着越来越重要的作用。利用野外实测数据分析了ALOS PALSAR双极化数据后向散射系数(HH0,HV0,HV/HH0)与云南山区松林蓄积量的关系,并分别构建简单线性、自然指数和加入地理因子的多元回归模型。研究结果表明:极化比值(HV/HH0)与蓄积量的相关系数(r=-0.407)比任何单极化(HH0和HV0分别为0.204和-0.242)都要高,加入地理因子的多元回归模型在森林蓄积量估算中有较好的精度。图3表2参12
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关键词:
- 森林测计学 /
- ALOS PALSAR /
- 森林蓄积量 /
- 地理因子
Abstract: Synthetic Aperture Radar (SAR),having a particular imaging mechanism that can acquire data at any time,has become more and more important for estimating forest biomass. In this research,based on field survey data,correlations between ALOS PALSAR dual polarization data backscattering coefficients (HH0,HV0 and V/HH0)and Yunnan pine forest volume from hilly regions were analyzed. A simple linear model,an exponential model,and a multiple regression model with terrain factors were developed. Results showed that correlation of the polarization ratio (V/HH0) to forest volume (r = -0.407) was higher than any single polarization (HH0 with r = 0.204 and HV0 with r = -0.242). Also,the multiple regression model with terrain factors was with highest accuracy.[Ch,3 fig. 2 tab. 12 ref.]-
Key words:
- forest mensuration /
- ALOS PALSAR /
- forest volume /
- geographical factors
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链接本文:
https://zlxb.zafu.edu.cn/article/doi/10.11833/j.issn.2095-0756.2012.05.005
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