Collaborative Estimation of Aboveground Forest Biomass Using P-Band and X-Band Interferometric Synthetic Aperture Radar Based on Feature Optimization

IF 4.7 2区地球科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Pub Date : 2024-10-01 DOI:10.1109/JSTARS.2024.3472096

Yunmei Ma;Lei Zhao;Erxue Chen;Zengyuan Li;Yaxiong Fan;Kunpeng Xu;Han Wang

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Abstract

Accurate estimation of forest aboveground biomass (AGB) is crucial for research on terrestrial carbon cycling and global climate change. In this study, we introduce an improved approach for estimating forest AGB combining P-band and X-band interferometric synthetic aperture radar (InSAR) data. Forest AGB was estimated by combining unbiased forest height and volume backscatter intensity. For forest height, a multilayer model and subaperture decomposition technology were used to remove the penetration bias of the X-band and reduce the effects of forest scatterers on the extraction of a pure understory terrain phase based on P-band, respectively. For volume backscatter intensity, a ground cancellation algorithm based on P-band InSAR was used to eliminate ground scattering contributions unrelated to forest AGB. The proposed method was validated using airborne P-band InSAR data and spaceborne X-band InSAR data gathered over the study area on the Saihanba Forest Farm in Hebei, China. The unbiased forest height and volume backscatter intensity had stronger correlations with forest AGB than estimates derived from unimproved features. The proposed method returned high-precision estimates of forest AGB with an accuracy of 83.73%, an improvement of 8.80% over an estimate derived from unoptimized features. Additionally, AGB estimates combined with forest height and backscatter intensity were greater than those based on a single feature, with the contribution of the former is greater than that of the latter.

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基于特征优化的 P 波段和 X 波段干涉合成孔径雷达地面森林生物量协同估算

准确估算森林地上生物量（AGB）对陆地碳循环和全球气候变化研究至关重要。在本研究中，我们介绍了一种结合 P 波段和 X 波段干涉合成孔径雷达 (InSAR) 数据估算森林 AGB 的改进方法。通过结合无偏的森林高度和体积反向散射强度来估算森林 AGB。在森林高度方面，使用了多层模型和子孔径分解技术，以消除 X 波段的穿透偏差，并减少森林散射体对基于 P 波段提取纯林下地形相位的影响。在体积反向散射强度方面，使用了基于 P 波段 InSAR 的地面消除算法，以消除与森林 AGB 无关的地面散射贡献。利用在中国河北塞罕坝林场研究区域上空采集的机载 P 波段 InSAR 数据和机载 X 波段 InSAR 数据，对所提出的方法进行了验证。与未改进的地貌特征相比，无偏的森林高度和体积反向散射强度与森林AGB的相关性更强。所提出的方法可获得高精度的森林 AGB 估计值，准确率达 83.73%，比未优化地物得出的估计值提高了 8.80%。此外，结合森林高度和反向散射强度得出的 AGB 估计值高于基于单一特征得出的估计值，前者的贡献大于后者。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 地学-成像科学与照相技术

CiteScore

9.30

自引率

10.90%

发文量

563

审稿时长

4.7 months

期刊介绍： The IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing addresses the growing field of applications in Earth observations and remote sensing, and also provides a venue for the rapidly expanding special issues that are being sponsored by the IEEE Geosciences and Remote Sensing Society. The journal draws upon the experience of the highly successful “IEEE Transactions on Geoscience and Remote Sensing” and provide a complementary medium for the wide range of topics in applied earth observations. The ‘Applications’ areas encompasses the societal benefit areas of the Global Earth Observations Systems of Systems (GEOSS) program. Through deliberations over two years, ministers from 50 countries agreed to identify nine areas where Earth observation could positively impact the quality of life and health of their respective countries. Some of these are areas not traditionally addressed in the IEEE context. These include biodiversity, health and climate. Yet it is the skill sets of IEEE members, in areas such as observations, communications, computers, signal processing, standards and ocean engineering, that form the technical underpinnings of GEOSS. Thus, the Journal attracts a broad range of interests that serves both present members in new ways and expands the IEEE visibility into new areas.