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International Conference on Urban Forestry and Statistics - (ICUFS-27)

3rd - 4th April 2027 , Naples - Italy

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Call For Papers

The (ICUFS-27) emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Forestry, Statistics, Environmental Sustainability are explored to promote cross-domain knowledge exchange and collaborative innovation.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Statistical methods in urban forestry
  • Econometric analysis of urban green spaces
  • Impact of urban forestry on biodiversity
  • Statistical modeling of tree growth patterns
  • Urban forestry and climate change statistics
  • Econometric evaluation of urban forestry policies
  • Statistical analysis of urban air quality
  • Urban forestry and public health statistics
  • Statistical techniques for forest inventory analysis
  • Econometric modeling of urban ecosystems
  • Statistical assessment of urban heat islands
  • Urban forestry's economic impact analysis
  • Statistical methods for community forestry programs
  • Econometric analysis of land use changes
  • Statistical modeling of urban wildlife habitats
  • Urban forestry and social equity statistics
  • Statistical challenges in urban forestry research
  • Econometric evaluation of green infrastructure
  • Statistical analysis of urban forestry practices
  • Urban forestry and ecosystem service valuation

Assessment

All submissions will undergo peer review to ensure quality and interdisciplinary relevance. Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.