Regional Applicability of Forest Height and Aboveground Biomass Models for the Geoscience Laser Altimeter System

IF 1.5 4区农林科学 Q2 FORESTRY

Forest Science Pub Date : 2024-04-10 DOI:10.1093/forestscience/54.6.647

Dirk Pflugmacher, Warren Cohen, Robert Kennedy, Michael Lefsky

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Abstract

Accurate estimates of forest aboveground biomass are needed to reduce uncertainties in global and regional terrestrial carbon fluxes. In this study we investigated the utility of the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud and land Elevation Satellite for large-scale biomass inventories. GLAS is the first spaceborne lidar sensor that will provide global estimates of forest height. We compared accuracy and regional variability of GLAS height estimates with data from the US Forest Service Inventory and Analysis (FIA) program and found that current GLAS algorithms provided generally accurate estimates of height. GLAS heights were on average 2–3 m lower than FIA estimates. To translate GLAS-estimated heights into forest biomass will require general allometric equations. Analysis of the regional variability of forest height-biomass relationships using FIA field data indicates that general nonspecies specific equations are applicable without a significant loss of prediction accuracy. We developed biomass models from FIA data and applied them to the GLAS-estimated heights. Regional estimates of forest biomass from GLAS differed between 39.7 and 58.2 Mg ha−1 compared with FIA.

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地球科学激光测高仪系统的森林高度和地上生物量模型的区域适用性

为了减少全球和区域陆地碳通量的不确定性，需要对森林地上生物量进行精确估算。在这项研究中，我们调查了冰云陆地高程卫星上的地球科学激光测高系统（GLAS）在大规模生物量清查中的实用性。GLAS 是首个可提供全球森林高度估计值的星载激光雷达传感器。我们将 GLAS 高度估算的准确性和区域变异性与美国林务局清查和分析（FIA）计划的数据进行了比较，发现目前的 GLAS 算法提供的高度估算基本准确。GLAS 估算的高度比 FIA 估算的高度平均低 2-3 米。要将 GLAS 估算的高度转化为森林生物量，需要使用一般的计量方程。利用森林资源评估实地数据对森林高度-生物量关系的区域变异性进行的分析表明，一般的非物种特异性方程是适用的，而且不会明显降低预测精度。我们根据 FIA 数据开发了生物量模型，并将其应用于 GLAS 估算的高度。与 FIA 相比，GLAS 对森林生物量的区域估算值相差 39.7 至 58.2 兆克/公顷。

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来源期刊

Forest Science 农林科学-林学

CiteScore

2.80

自引率

7.10%

发文量

审稿时长

3 months

期刊介绍： Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management. Forest Science is published bimonthly in February, April, June, August, October, and December.