Cunliffe Andrew M, Anderson Karen, Boschetti Fabio, Brazier Richard E, Graham Hugh A, Myers-Smith Isla H, Astor Thomas, Boer Matthias M, Calvo Leonor G, Clark Patrick E, Cramer Michael D, Encinas-Lara Miguel S, Escarzaga Stephen M, Fernández-Guisuraga José M, Fisher Adrian G, Gdulová Kateřina, Gillespie Breahna M, Griebel Anne, Hanan Niall P, Hanggito Muhammad S, Haselberger Stefan, Havrilla Caroline A, Heilman Phil, Ji Wenjie, Karl Jason W, Kirchhoff Mario, Kraushaar Sabine, Lyons Mitchell B, Marzolff Irene, Mauritz Marguerite E, McIntire Cameron D, Metzen Daniel, Méndez-Barroso Luis A, Power Simon C, Prošek Jiří, Sanz-Ablanedo Enoc, Sauer Katherine J, Schulze-Brüninghoff Damian, Šímová Petra, Sitch Stephen, Smit Julian L, Steele Caiti M, Suárez-Seoane Susana, Vargas Sergio A, Villarreal Miguel, Visser Fleur, Wachendorf Michael, Wirnsberger Hannes, Wojcikiewicz Robert
Department of Geography College of Life and Environmental Sciences University of Exeter Exeter UK.
Environment and Sustainability Institute University of Exeter Penryn UK.
Remote Sens Ecol Conserv. 2022 Feb;8(1):57-71. doi: 10.1002/rse2.228. Epub 2021 Jul 7.
Non-forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, and are highly sensitive to climatic changes. Yet these ecosystems are poorly represented in remotely sensed biomass products and are undersampled by in situ monitoring. Current global change threats emphasize the need for new tools to capture biomass change in non-forest ecosystems at appropriate scales. Here we developed and deployed a new protocol for photogrammetric height using unoccupied aerial vehicle (UAV) images to test its capability for delivering standardized measurements of biomass across a globally distributed field experiment. We assessed whether canopy height inferred from UAV photogrammetry allows the prediction of aboveground biomass (AGB) across low-stature plant species by conducting 38 photogrammetric surveys over 741 harvested plots to sample 50 species. We found mean canopy height was strongly predictive of AGB across species, with a median adjusted of 0.87 (ranging from 0.46 to 0.99) and median prediction error from leave-one-out cross-validation of 3.9%. Biomass per-unit-of-height was similar but different plant functional types. We found that photogrammetric reconstructions of canopy height were sensitive to wind speed but not sun elevation during surveys. We demonstrated that our photogrammetric approach produced generalizable measurements across growth forms and environmental settings and yielded accuracies as good as those obtained from in situ approaches. We demonstrate that using a standardized approach for UAV photogrammetry can deliver accurate AGB estimates across a wide range of dynamic and heterogeneous ecosystems. Many academic and land management institutions have the technical capacity to deploy these approaches over extents of 1-10 ha. Photogrammetric approaches could provide much-needed information required to calibrate and validate the vegetation models and satellite-derived biomass products that are essential to understand vulnerable and understudied non-forested ecosystems around the globe.
以灌木、草本植物为主的非森林生态系统提供包括碳固存和放牧草料在内的生态系统服务，并且对气候变化高度敏感。然而，这些生态系统在遥感生物量产品中的代表性不足，且实地监测的采样也不够充分。当前的全球变化威胁凸显了开发新工具以在适当尺度上捕捉非森林生态系统生物量变化的必要性。在此，我们开发并应用了一种利用无人机（UAV）图像进行摄影测量高度的新方案，以测试其在全球分布的田间试验中提供生物量标准化测量的能力。我们通过对741个已收割地块进行38次摄影测量调查，对50个物种进行采样，评估了从无人机摄影测量推断出的冠层高度是否能够预测低生长植物物种的地上生物量（AGB）。我们发现，平均冠层高度对各物种的AGB具有很强的预测性，调整后的中位数为0.87（范围从0.46至0.99），留一法交叉验证的中位数预测误差为3.9%。单位高度的生物量在不同植物功能类型中相似但存在差异。我们发现，冠层高度的摄影测量重建对风速敏感，但对测量期间太阳高度不敏感。我们证明，我们的摄影测量方法在不同生长形式和环境条件下都能得出可推广的测量结果，其精度与实地测量方法相当。我们证明，使用标准化的无人机摄影测量方法能够在广泛的动态和异质生态系统中提供准确的AGB估计。许多学术和土地管理机构具备在1 - 10公顷范围内应用这些方法的技术能力。摄影测量方法可为校准和验证植被模型以及卫星衍生生物量产品提供急需的信息，而这些对于了解全球脆弱且研究不足的非森林生态系统至关重要。
