Monitoring the Early Growth of Pinus and Eucalyptus Plantations Using a Planet NICFI-Based Canopy Height Model: A Case Study in Riqueza, Brazil

Abstract

Monitoring the height of secondary forest regrowth is essential for assessing ecosystem recovery, but current methods rely on field surveys, airborne or UAV LiDAR, and 3D reconstruction from high-resolution UAV imagery, which are often costly or limited by logistical constraints. Here, we address the challenge of scaling up canopy height monitoring by evaluating a recent deep learning model, trained on data from the Amazon and Atlantic Forests, developed to extract canopy height from RGB-NIR Planet NICFI imagery. The research questions are as follows: (i) How are canopy height estimates from the model affected by slope and orientation in natural forests, based on a large and well-balanced experimental design? (ii) How effectively does the model capture the growth trajectories of Pinus and Eucalyptus plantations over an eight-year period following planting? We find that the model closely tracks Pinus growth at the parcel scale, with predictions generally within one standard deviation of UAV-derived heights. For Eucalyptus, while growth is detected, the model consistently underestimates height, by more than 10 m in some cases, until late in the cycle when the canopy becomes less dense. In stable natural forests, the model reveals seasonal artifacts driven by topographic variables (slope × aspect × day of year), for which we propose strategies to reduce their influence. These results highlight the model’s potential as a cost-effective and scalable alternative to field-based and LiDAR methods, enabling broad-scale monitoring of forest regrowth and contributing to innovation in remote sensing for forest dynamics assessment.

Plant phenotyping relevance

RGB-NIR衛星画像から樹冠高を推定するモデルを評価し、UAV由来の高さと比較検証している。植物の形態形質である樹冠高の取得手法が研究の中心である。

Code and data availability

No paper-specific public asset qualifies. The Data Availability Statement says most data are available only on request; the canopy height map is a Planet-NICFI derivative under a license, and NICFI imagery is commercial. No author code, model checkpoints, or phenotype/trait data deposit with a public authors' URL is in

No evidence-backed public reproduction asset is currently recorded.