Haga, Chihiro

Haga, Chihiro

Specially Appointed Assistant Professor

GE lab, Osaka University

Engineering for Living in Harmony with Nature

Hi! I’m an engineer in the landscape ecology domain using data science techniques to realize a society where the diverse values of nature are included in decision-making. I also aim to contribute to the achievement of local SDGs through the social implementation of my research. For each theme, networking among young scholars/practitioners in related areas, such as ecology, environmental systems, and environmental policy, is very important. I’m welcome for a new collaboration.

Interests
  • Scenario analysis of Biodiversity and Ecosystem Services
  • Process-based forest landscape change modeling
  • Acoustic monitoring
Education
  • PhD of Engineering in Environmental Engineering, 2021

    Osaka University

  • Master of Engineering in Environmental Engineering, 2018

    Osaka University

  • Bachelor of Engineering in Environmental Engineering, 2016

    Osaka University

Skills

Forest Landscape Modeling

Application / Development

R

Geo-spatial analysis / Statistics / Data visualization

Python

Geo-spatial analysis / Machine learning / Optimization

ArcGIS / Q-GIS

Geo-spatial analysis

Software development

Python, C#, R, and Julia on Win/Ubuntu/Mac

Language

English (fluent) / Japanese (native)

Photography

OM-D E-M5 Mark II

Experience

 
 
 
 
 
Specially Appointed Assistant Professor / 特任助教 (常勤)
Apr 2024 – Present Osaka, Japan
Renewable energy and landscape management for living in harmony with nature
 
 
 
 
 
Specially Appointed Researcher / 特任研究員 (常勤)
Apr 2021 – Mar 2024 Osaka, Japan
Nexus analysis of local SDGs in the context of landscape management
 
 
 
 
 
Collaborative Researcher / 共同研究員
Apr 2021 – Mar 2022 Tokyo, Japan
Development of a Forest Landscape Simulation Model for Assessing Disturbance Impacts on Forest Ecosystems in Shiga Prefecture
 
 
 
 
 
Research Fellow (DC-1) of JSPS / 日本学術振興会 特別研究員DC-1
Apr 2018 – Mar 2021 Osaka, Japan
Development of a Social-Ecological Systems Model for Scenario Analysis of Biodiversity and Ecosystem Services at Local Scale

Recent Publications

(2023). Modeling desirable futures at local scale by combining the nature futures framework and multi-objective optimization.

Cite Project Project DOI URL

(2023). Does Deep Learning Enhance the Estimation for Spatially Explicit Built Environment Stocks through Nighttime Light Data Set? Evidence from Japanese Metropolitans.

Cite DOI URL

(2022). Modeling Tree Recovery in Wind-Disturbed Forests with Dense Understory Species under Climate Change. Ecological Modelling.

Cite DOI

(2022). Modelling a Landscape Using Nature Futures Framework: A Case Study in Japan. World Biodiversity Forum 2022.

Cite Project Project

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