Integrating Remote Sensing and GIS Application for Natural Resource Management

A Hands-on Practical Session for M.Sc. Students

From June 26th to June 30th, 2023, the Institute of Forestry, Hetauda Campus  in collaboration with the Center for Environmental and Sustainable Agricultural Research (CESAR), a dynamic and comprehensive practical session was conducted for M.Sc. students in Forestry, Wildlife, Protected Area Management and Biodiversity Conservation. This session focused on integrating Remote Sensing (RS) and Geographic Information Systems (GIS) to enhance students' expertise in Natural Resource Management (NRM). Led by esteemed trainers Shiva Pokhrel and Dinesh Mani Bhandari, the program aimed to provide advanced training, practical skills, and interdisciplinary knowledge to the participating students. During the practical session, the students:

  • Learned essential skills in collecting, processing, and organizing geospatial data from diverse sources.
  • Acquired knowledge of fundamental concepts and principles in RS and GIS for NRM.
  • Explored RS interpretation techniques and gained familiarity with various sources of global data relevant to NRM applications.
  • Received guidance on data preprocessing techniques to ensure data quality and efficient database design.
  • Developed a deeper understanding of the integration of RS and GIS for enhanced NRM expertise.
  • Enhanced their practical skills through hands-on exercises and case studies.
  • Explored the role of RS and GIS in Forestry, Wildlife, Protected Area Management, and Biodiversity Conservation.
  • Acquired interdisciplinary knowledge and an interdisciplinary approach to NRM.
  • Developed a broader perspective on sustainable resource management practices.
  • Benefitted from the expertise and guidance provided by the trainers from CESAR.
  • Developed a strong foundation for utilizing RS and GIS tools in NRM.

 

Thank you to all the participants, trainers, and organizers for making this training program a success.

CESAR July 12, 2023
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