Mapping local knowledge through spatial text mining

Lee, Jae-hyuck

doi:10.1007/s11355-023-00541-1

Cited by 1 publication

(1 citation statement)

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“…This study used spatial text mining to spatially represent the local knowledge according to the respective ecosystem service. The technique was utilized to analyze and map ecosystem services expressed as local knowledge for each ecological asset in spatial text mining process based on factor analysis 9 , 29 . This study collected ecological knowledge, used spatial text mining in steps 2 through 4, and validated it in step 5.…”

Section: Methodsmentioning

confidence: 99%

Ecosystem service evaluation based on local knowledge of residents using spatial text-mining

Lee,

Ahn

2023

Sci Rep

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This study aims to evaluate the ecosystem services of Upo wetland, one of the best-known Ramsar sites in Korea, reflecting the characteristics of the ecological assets and local knowledges in the area. Application of spatial text-mining begins with collecting local perceptions and knowledge of residents on the 17 ecological assets of Upo site and surrounding area. Our results identified five important ecosystem services: flood control during heavy rainfall, water purification by aquatic plants, cultural and natural heritages, agricultural products and water provision for crop cultivation. GIS created a map where these ecosystem services were linked to the locations of 17 ecological assets. This map showed which ecosystem service is associated with particular ecological assets and their characteristics from residents’ perspectives. Mapping local knowledge using the spatial text-mining is able to identify multi-functional bases which provide various ecosystem services in the same location simultaneously. Identification of multi-functional bases can provide information for local government to design an effective and comprehensive management plan considering physical-cultural geography of ecosystem services.

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Section: Methodsmentioning

confidence: 99%