Information Categorization for Canopy Mapping using Quality Control (QC) Tool – Affinity Diagram (KJ Method)

Abstract

Canopy mapping involves the process of accurately delineating and assessing the distribution and extent of green spaces, trees, and vegetation within a designated area. Understanding the canopy's characteristics holds paramount importance, as it plays a critical role in supporting biodiversity, regulating microclimates, and mitigating the adverse impacts of urbanization on the environment. This research paper focuses on exploring the practical application of the KJ method and collaborative brainstorming to gather and organize relevant information for canopy mapping. The study engaged six undergraduate students, under the guidance of a faculty member specialized in geoinformatics, in a productive brainstorming session, generating twenty-one diverse ideas related to canopy mapping. Through a methodical process of iterative refinement and consensus-building, the students effectively grouped these ideas into four distinct categories: "Data Sources," "Canopy Estimation Process," "Canopy Map Development," and "Accuracy Assessment." The resulting Affinity Diagram served as a clear and well-structured representation of the research paper's key aspects, harnessing the collective intelligence of the team to organize complex information and facilitate the precise mapping of tree canopies. This collaborative approach proved instrumental in enhancing the project's efficiency and effectiveness, promoting a cooperative environment that fosters innovation and informed decision-making.