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首页> 外文会议>Asian conference on remote sensingACRS >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：从无人机光学和TLS数据中提取的森林树参数比较热带雨水和温带林中数据

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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：有一种成本效益和准确的方法，可以评估用于估计地上生物量（AGB）/碳储备的参数，无论是复杂的多层热带雨林和温带林。乳房高度（DBH）的树​​高和直径是作为生物量估计方程的输入所需的重要森林参数，并且可以通过各种方法获得，例如直接场测量。然而，测量树高度和DBH的现场测量是耗时的，限于无法访问的区域和相当昂贵的区域。随着遥感技术的进步，各种数据集已被用于评估AGB，包括机载LIDAR或有时被称为机载激光扫描仪（ALS），但该数据并不总是可用的，以便获得定期监控。单独的无人机（UAV）和地面激光扫描仪（TLS）技术的出现分别从空气和地进行，可以以合理的成本提供上层和下层顶层的准确信息，以定期监测碳储备。然而，两者都与复杂的多层热带森林中的叶子覆盖的限制有关，这些森林可以在单独使用时低估AGB。本研究旨在建立一种成本效益的方法，可确保通过补充UAV Imagerery和TLS数据来定期评估热带雨林和HEDD +及其MRV系统的AGB /碳估计的温带森林中的树木参数的合理准确性。此外，讨论了热带和温带林中技术与建模方法之间的比较。此外，对从UAV和TLS提取的结果的结构和热带雨水和温带森林的影响进行了比较。

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