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Close-Range Remote Sensing of Forests: The state of the art, challenges, and opportunities for systems and data acquisitions

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, Yunsheng Wang, Juha Hyyppä

2022IEEE Geoscience and Remote Sensing Magazine138 citationsDOI

Abstract

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.

Topics & Concepts

BottleneckRemote sensingComputer scienceField (mathematics)LimitingScale (ratio)Range (aeronautics)Reliability (semiconductor)Environmental scienceData scienceGeographyEngineeringCartographyAerospace engineeringEmbedded systemPower (physics)MathematicsQuantum mechanicsMechanical engineeringPhysicsPure mathematicsRemote Sensing and LiDAR ApplicationsRemote Sensing in AgricultureForest ecology and management