首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >POLINSAR BASED SCATTERING INFORMATION RETRIEVAL FOR FOREST ABOVEGROUND BIOMASS ESTIMATION
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POLINSAR BASED SCATTERING INFORMATION RETRIEVAL FOR FOREST ABOVEGROUND BIOMASS ESTIMATION

机译:基于POLINSAR的森林植被生物量估计的散射信息反演。

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Forests play a crucial role in storing carbon and are of paramount importance in maintaining global carbon cycle. Assessment of forest biomass at regional and global level is vital for understanding and monitoring health of both tree species and entire cover. Changes in forest biomass are caused by human activities, natural factors and variations in climate. Forest biomass measurement is necessary for gauging the changes in forest ecosystems. Remote sensing is indispensable for mapping forest biophysical parameters. Microwaves are capable of collecting data even in case of cloud cover as the microwaves are of long wavelength. Microwaves help in retrieving scattering information of target. The goal of this research was to map aboveground biomass (AGB) over Barkot forest range in Dehradun, India. The current work focuses on the retrieval of PolInSAR based scattering information for the estimation of aboveground biomass. Radarsat-2 fully Polarimetric C-band data was used for the estimation of AGB in Barkot forest area. A semi-empirical model, which is Extended Water Cloud Model (EWCM) was utilized for AGB estimation. EWCM considers ground-stem interactions. Due to overestimation of volume scattering, polarization orientation angle shift correction was implemented on the PolInSAR pair. Field biomass data was utilized for accuracy assessment. The results show that coefficient of determination (Rsup2/sup) value of 0.47, Root Mean Square Error (RMSE) of 56.18 (t?hasup?1/sup) and accuracy of 72% was obtained between modelled biomass against field measured biomass. Hence, it can be inferred from the obtained results that PolInSAR technique, in combination with semi-empirical modelling approach, can be implemented for estimating forest biomass.
机译:森林在碳储存中起着至关重要的作用,对维持全球碳循环至关重要。在区域和全球范围内对森林生物量的评估对于理解和监测树木和整个植被的健康至关重要。森林生物量的变化是由人类活动,自然因素和气候变化引起的。森林生物量测量对于衡量森林生态系统的变化是必要的。遥感对于绘制森林生物物理参数是必不可少的。微波即使在云层覆盖的情况下也能够收集数据,因为微波的波长较长。微波有助于检索目标的散射信息。这项研究的目的是在印度Dehradun的Barkot森林范围内绘制地上生物量(AGB)。目前的工作集中在基于PolInSAR的散射信息的检索上,以估算地上生物量。 Radarsat-2完全极化C波段数据用于估算巴科特森林地区的AGB。半经验模型是扩展水云模型(EWCM),用于AGB估算。 EWCM考虑地干相互作用。由于高估了体积散射,因此在PolInSAR对上执行了极化取向角偏移校正。利用田间生物量数据进行准确性评估。结果表明,确定系数(R 2 )值为0.47,均方根误差(RMSE)为56.18(t?ha ?1 ),准确度为72%在建模的生物量与现场测得的生物量之间获得了因此,从获得的结果可以推断出,可以将PolInSAR技术与半经验建模方法相结合来实现森林生物量的估算。

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