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首页> 外文会议>Asian conference on remote sensing;ACRS >COMPARISON OF FOREST TREE PARAMETERS EXTRACTED FROM UAV OPTICAL AND TLS DATA IN BOTH TROPICAL RAIN AND TEMPERATE FORESTS
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COMPARISON OF FOREST TREE PARAMETERS EXTRACTED FROM UAV OPTICAL AND TLS DATA IN BOTH TROPICAL RAIN AND TEMPERATE FORESTS

机译：从热带雨林和温带森林的无人机光学和TLS数据中提取森林树参数的比较

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There is a great need for a cost-effective and accurate method to assess the parameters for estimating above-ground biomass (AGB)/carbon stock, both in complex multi-layered tropical rain-forest and in temperate forests. The tree height and Diameter at Breast Height (DBH) are important forest parameters required as inputs for biomass estimation equation and can be obtained through various methods such as direct field measurement. However, measuring tree height and DBH by field surveying is time-consuming, limited to inaccessible areas and rather expensive. With the advancement of remote sensing technology, various datasets have been used to assess AGB including airborne LiDAR or sometimes called Airborne Laser Scanner (ALS) but this data is not always available and expensive to acquire for regular monitoring. The emergent of Unmanned Aerial Vehicle (UAV) and Terrestrial Laser Scanner (TLS) technologies, which operate from air and ground respectively, can provide accurate information of upper and lower canopy layers at a reasonable cost for regular monitoring of carbon stock. However, both are associated with the limitation of foliage coverage in the complex multi-layer tropical forest which can underestimate AGB when used separately. This study aimed at establishing a cost-effective method that ensures reasonable accuracy for regular assessment of tree parameters in tropical rain-forest and temperate forests for AGB/carbon estimation for REDD+ and its MRV system by complementing UAV imagery and TLS data. Furthermore, a comparison between the techniques and modeling approach in both the tropical and temperate forest are discussed. Moreover, a comparison is made of the effect of the structure and the condition of both tropical rain and temperate forests on the results extracted from UAV and TLS.
机译：在复杂的多层热带雨林和温带森林中，迫切需要一种经济高效且准确的方法来评估用于估算地上生物量（AGB）/碳储量的参数。树高和胸高直径（DBH）是重要的森林参数，是生物量估算方程的输入，可以通过多种方法（例如直接野外测量）获得。但是，通过野外测量来测量树木的高度和DBH是费时的，限于无法进入的区域，而且相当昂贵。随着遥感技术的进步，已经使用了各种数据集来评估AGB，包括机载LiDAR或有时被称为机载激光扫描仪（ALS），但是这些数据并不总是可用，而且要进行常规监控也很昂贵。分别从空中和地面运行的无人飞行器（UAV）和陆地激光扫描仪（TLS）技术的出现，可以以合理的成本提供上下冠层的准确信息，以便定期监测碳储量。然而，这两者都与复杂的多层热带森林中的树叶覆盖率的限制有关，当单独使用时，这可能会低估AGB。这项研究旨在建立一种经济有效的方法，通过补充无人机图像和TLS数据，确保合理评估常规雨林和温带森林树木参数的准确性，以对REDD +及其MRV系统进行AGB /碳估算。此外，还讨论了热带和温带森林中的技术和建模方法之间的比较。此外，比较了热带雨林和温带森林的结构和条件对从无人机和TLS提取的结果的影响。

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