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<p>i-Tree Eco is gaining popularity in Japan for valuing ecosystem services, but its application requires diameter at breast height (DBH) measurements, which are challenging to obtain using unmanned aerial vehicle (UAV)-based photogrammetric surveys. This study aimed to develop and compare models for estimating the value of ecosystem services either directly from UAV-derived tree height and crown diameter or indirectly via DBH estimation. This research focused on a satoyama forest in Central Japan, where Japanese cedar (<i>Cryptomeria japonica</i>) and Japanese cypress (<i>Chamaecyparis obtusa</i>) occur locally and were selected as the target species for analysis. Four models (linear and nonlinear) were constructed and evaluated based on UAV-LiDAR-derived tree attributes. The ecosystem services assessed included carbon storage, annual carbon sequestration, and air pollution removal. Among these, air pollution removal was estimated with the highest accuracy, while carbon-related services showed lower precision due to DBH estimation errors. The nonlinear model that directly estimated service values without DBH input provided the most balanced performance. These findings demonstrate the potential of UAV-based methods as efficient tools for ecosystem service valuation and sustainable satoyama management, offering a scalable and cost-effective alternative where traditional field measurements are limited.</p>

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Monetary valuation of tree ecosystem services using i-Tree Eco and UAV: development of a model eliminating the need for DBH data

  • 期刊论文

  • 发表日期：

    2025年10月8日

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  • Norikazu Eguchi,
  • Shunji Yachi,
  • Takatsugu Hirayama,
  • Eisaku Seguchi,
  • Jun Yajima

摘要

i-Tree Eco is gaining popularity in Japan for valuing ecosystem services, but its application requires diameter at breast height (DBH) measurements, which are challenging to obtain using unmanned aerial vehicle (UAV)-based photogrammetric surveys. This study aimed to develop and compare models for estimating the value of ecosystem services either directly from UAV-derived tree height and crown diameter or indirectly via DBH estimation. This research focused on a satoyama forest in Central Japan, where Japanese cedar (Cryptomeria japonica) and Japanese cypress (Chamaecyparis obtusa) occur locally and were selected as the target species for analysis. Four models (linear and nonlinear) were constructed and evaluated based on UAV-LiDAR-derived tree attributes. The ecosystem services assessed included carbon storage, annual carbon sequestration, and air pollution removal. Among these, air pollution removal was estimated with the highest accuracy, while carbon-related services showed lower precision due to DBH estimation errors. The nonlinear model that directly estimated service values without DBH input provided the most balanced performance. These findings demonstrate the potential of UAV-based methods as efficient tools for ecosystem service valuation and sustainable satoyama management, offering a scalable and cost-effective alternative where traditional field measurements are limited.