利用无人机系统的高分辨率图像估计热带自然森林碎片的结构属性

IF 0.7 4区 地球科学 Q4 GEOSCIENCES, MULTIDISCIPLINARY Earth Sciences Research Journal Pub Date : 2022-05-11 DOI:10.15446/esrj.v26n1.95405
Johnny Alexander Vega Gutiérrez, S. Palomino-Ángel, J. Anaya
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引用次数: 0

摘要

结构属性是森林的基本生物物理参数,可用于生态和环境监测和规划。树冠高度是估计地上生物量和碳储量等几个生物物理参数的重要输入,可能与森林退化、森林砍伐和减排有关。因此,准确估计冠层高度是气候变化研究和REDD+倡议中的一个关键问题。无人驾驶飞机系统的VHR图像已被研究为在局部尺度上估计冠层高度的低成本平均值,但估计的准确性是决定其效用的一个因素。我们评估了无人驾驶飞机系统的VHR图像得出结构属性的能力,特别是位于安第斯山脉山麓的自然热带森林碎片中的树冠面积和高度,该森林碎片位于南美洲生物地理乔科地区的潮湿热带森林中。该地区是世界上生物多样性最强的地区之一,具有高度的地方性,但自然资源损失的风险也更高。我们使用从运动结构的方法来推导森林碎片的树冠高度模型,并应用均值偏移算法来识别单个树冠。准确性评估是使用来自实地活动的参考数据和VHR图像的视觉解释进行的。树冠高度模型的垂直误差群体的估计均方根误差为3.6米。描绘树冠的总准确率为73.9%。我们发现,使用VHR图像,可以识别并容易地监测特定的树木和树冠间隙,这是保护计划中的重要一步。我们还讨论了这些发现在零散森林背景下的有用性,以及激光雷达系统的价格和这种方法的准确性之间的权衡。
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Structural attributes estimation in a natural tropical forest fragment using very high-resolution imagery from unmanned aircraft systems
Structural attributes are fundamental biophysical parameters of forest, useful for ecological and environmental monitoring and planning. Canopy height is an important input for the estimation of several biophysical parameters as aboveground biomass and carbon stock, and can be related with forest degradation, deforestation, and emission reduction. Thus, an accurate canopy height estimation is a crucial issue in climate change studies and REDD+ initiatives. VHR imagery from unmanned aircraft systems has been studied as a low cost mean for canopy height estimation at local scales, but the accuracy in the estimation is a factor that determines its utility. We evaluated the ability of VHR imagery from unmanned aircraft systems to derive structural attributes, specifically tree-crown area and height, in a natural tropical forest fragment located in the foothills of the Andes Mountains, in the humid tropical forests of the region known as Biogeographic Chocó, South America. The region is one of the most biodiverse areas of the world and has a high level of endemism, but it is also at higher risk of natural-resource loss. We used a structure from motion approach to derive canopy height models of the forest fragment, and we applied mean-shift algorithms to identify single tree crowns. The accuracy assessment was performed using reference data derived from field campaigns and visually interpretation of VHR imagery. The estimated root-mean-square error of the population of vertical errors for the canopy height model was 3.6 m. The total accuracy for delineating tree crowns was 73.9%. We found that using VHR imagery, specific trees and canopy gaps can be identified and easily monitored, which is an important step in conservation programs. We also discuss the usefulness of these findings in the context of fragmented forests and the tradeoffs between the price of a LIDAR system and the accuracy of this approach.
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来源期刊
Earth Sciences Research Journal
Earth Sciences Research Journal 地学-地球科学综合
CiteScore
1.50
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: ESRJ publishes the results from technical and scientific research on various disciplines of Earth Sciences and its interactions with several engineering applications. Works will only be considered if not previously published anywhere else. Manuscripts must contain information derived from scientific research projects or technical developments. The ideas expressed by publishing in ESRJ are the sole responsibility of the authors. We gladly consider manuscripts in the following subject areas: -Geophysics: Seismology, Seismic Prospecting, Gravimetric, Magnetic and Electrical methods. -Geology: Volcanology, Tectonics, Neotectonics, Geomorphology, Geochemistry, Geothermal Energy, ---Glaciology, Ore Geology, Environmental Geology, Geological Hazards. -Geodesy: Geodynamics, GPS measurements applied to geological and geophysical problems. -Basic Sciences and Computer Science applied to Geology and Geophysics. -Meteorology and Atmospheric Sciences. -Oceanography. -Planetary Sciences. -Engineering: Earthquake Engineering and Seismology Engineering, Geological Engineering, Geotechnics.
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