Effectiveness of tree count estimation in Sugi and Hinoki plantations using aerial orthophotos and deep learning

Authors

Naoto Matsumura (ORCID: https://orcid.org/0000-0002-4205-6307)
Yuki Hirose (ORCID: https://orcid.org/0000-0001-6879-7886)

Institutions

Forest Research Institute (IN)
Mie University (JP)

Publication Details

Journal: Japanese Journal of Forest Planning
Published: 2025-03-04
DOI: https://doi.org/10.20659/jjfp.a20241201
Primary Topic: Remote Sensing and LiDAR Applications
Type: article
Field-Weighted Citation Impact: 0.00

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

Effectiveness of tree count estimation in Sugi and Hinoki plantations using aerial orthophotos and deep learning

Naoto Matsumura, Yuki Hirose

Mar 4, 2025

Japanese Journal of Forest Planning

Remote Sensing and LiDAR Applications

article

Effectiveness of tree count estimation in Sugi and Hinoki plantations using aerial orthophotos and deep learning

Naoto Matsumura, Yuki Hirose

March 4, 2025article en

Abstract

No abstract available for this paper.

Japanese Journal of Forest PlanningVol. 59(1)

Forest Research Institute (IN), Mie University (JP)

Zero hunger

Openalex Percentile: Top 97%

Remote Sensing and LiDAR Applications

DOI Open Access PDF OpenAlex

AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Effectiveness of tree count estimation in Sugi and Hinoki plantations using aerial orthophotos and deep learning — Naoto Matsumura, Yuki Hirose · Japanese Journal of Forest Planning (2025) | TGRS Research Map | TGRS