Influence of image pixel resolution on canopy cover estimation in poplar plantations from field, aerial and satellite optical imagery

F. Chianucci, N. Puletti, M. Grotti, C. Bisaglia, F. Giannetti, E. Romano, M. Brambilla, W. Mattioli, Giovanna Cabassi, S. Bajocco, Linyuan Li, G. Chirici, P. Corona, C. Tattoni
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引用次数: 8

Abstract

Accurate estimates of canopy cover (CC) are central for a wide range of forestry studies. As direct measurements are impractical, indirect optical methods have often been used to estimate CC from the complement of gap fraction measurements obtained with restricted-view sensors. In this short note we evaluated the influence of the image pixel resolution (ground sampling distance; GSD) on CC estimation in poplar plantations obtained from field (cover photography; GSD < 1 cm), unmanned aerial (UAV; GSD <10 cm) and satellite (Sentinel-2; GSD = 10 m) imagery. The trial was conducted in poplar tree plantations in Northern Italy, with varying age and canopy cover. Results indicated that the coarser resolution available from satellite data is suitable to obtain estimates of canopy cover, as compared with field measurements obtained from cover photography; therefore, S2 isrecommended for larger scale monitoring and routine assessment of canopy cover in poplar plantations. The higher resolution of UAV compared with Sentinel-2 allows finer assessment of canopy structure, which could also be used for calibrating metrics obtained from coarser-scale remote sensing products, avoiding the need of ground measurements.
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从野外、航空和卫星光学图像看图像像素分辨率对杨树人工林冠层覆盖度估计的影响
准确估计冠层盖度(CC)对广泛的林业研究至关重要。由于直接测量是不切实际的,因此通常使用间接光学方法从受限视图传感器获得的间隙分数测量的补集中估计CC。在这篇短文中,我们评估了图像像素分辨率(地面采样距离;GSD)在杨树人工林CC估算中的应用(覆盖摄影;GSD < 1 cm),无人机(UAV;GSD <10 cm)和卫星(Sentinel-2;GSD = 10 m)图像。试验在意大利北部不同树龄和树冠盖度的杨树种植园进行。结果表明,与野外测量结果相比,卫星数据提供的较粗分辨率适合于估算冠层覆盖度;因此,S2可用于杨树人工林林冠覆盖的大规模监测和常规评价。与Sentinel-2相比,无人机的更高分辨率允许对冠层结构进行更精细的评估,这也可以用于校准从较粗尺度遥感产品获得的度量,避免了对地面测量的需要。
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来源期刊
Annals of Silvicultural Research
Annals of Silvicultural Research Agricultural and Biological Sciences-Forestry
CiteScore
2.70
自引率
0.00%
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