瓶颈
遥感
计算机科学
领域(数学)
航程(航空)
比例(比率)
环境科学
限制
可靠性(半导体)
数据科学
地理
工程类
地图学
航空航天工程
嵌入式系统
功率(物理)
纯数学
物理
机械工程
量子力学
数学
作者
Xinlian Liang,Antero Kukko,Ivan Balenović,Ninni Saarinen,Samuli Junttila,Ville Kankare,Markus Holopainen,Martin Mokroš,Peter Surový,Harri Kaartinen,Luka Jurjević,Eija Honkavaara,Roope Näsi,Jingbin Liu,Markus Hollaus,Jiaojiao Tian,Xiaowei Yu,Jie Pan,Shangshu Cai,Juho‐Pekka Virtanen
标识
DOI:10.1109/mgrs.2022.3168135
摘要
Remote sensing-based forest investigation and monitoring have become more affordable and applicable in the past few decades. The current bottleneck limiting practical use of the vast volume of remote sensing data lies in the lack of affordable, reliable, and detailed field references, which are required for necessary calibrations of satellite and aerial data and calibrations of relevant allometric models. Conventional field investigations are mostly limited to a small scale, using a small quantity of observations. Rapid development in close-range remote sensing has been witnessed during the past two decades, i.e., in the constant decrease of the costs, size, and weight of sensors; steady improvements in the availability, mobility, and reliability of platforms; and progress in computational capacity and data science. These advances have paved the way for turning conventional expensive and inefficient manual forest in situ data collections into affordable and efficient autonomous observations.
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