Developing an ecological visualization system for biodiversity and water quality data / Cham Hui

Cham , Hui (2022) Developing an ecological visualization system for biodiversity and water quality data / Cham Hui. PhD thesis, Universiti Malaya.

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      Abstract

      Information visualization is an essential tool for effective communication and interpretation. When opposed to numerical quantities, comprehending information through graphics is easier. Google Earth can be used to create a useful monitoring site visualization system. However, research in web-based visualization systems is still lacking, and it deserves to be addressed. The research aims to create a web-based system that depicts the Water Quality Index (WQI) and the biodiversity index on Google Earth. For easy interpretation of water quality conditions, as well as species richness and biodiversity indexes, the system utilized graphical representation through various forms and colors. pH, dissolved oxygen, chemical oxygen demand, biochemical oxygen demand, total suspended solids, and ammonia nitrogen are all used in the stand and manage WQI for water quality visualization. For the biodiversity element, the program includes common biodiversity indexes such as Species Richness, Shannon Index, Simpson Index, and Hill Numbers. Citizen science has contributed to the collection of biodiversity data that is useful for biodiversity site conservation and preservation. By combining graphical components, the applicability of site biodiversity indexes can be improved. Previous research that attempted to integrate the calculation of biodiversity indices into biodiversity monitoring systems lacked the visual element. This unique study aims to create an online module that integrates citizen science biodiversity data with a visualization component. A graphical depiction of the system output is shown. It uses a variety of forms and colors to make water quality and diversity status easier to understand. It promotes environmental protection and improved interpretation of data, aiding biologists and environmentalists to better und the environment. The web-based system prototype can be accessed at the following website: http://www.umlivinglabsystem.com/.

      Item Type: Thesis (PhD)
      Additional Information: Thesis (PhD) - Faculty of Science, Universiti Malaya, 2022.
      Uncontrolled Keywords: Water quality index; Shannon index; Simpson index; Hill numbers; Citizen science index
      Subjects: Q Science > Q Science (General)
      Q Science > QH Natural history > QH301 Biology
      Divisions: Faculty of Science
      Depositing User: Mr Mohd Safri Tahir
      Date Deposited: 29 Jan 2024 04:09
      Last Modified: 29 Jan 2024 04:09
      URI: http://studentsrepo.um.edu.my/id/eprint/14752

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