เปรียบเทียบวิธี

	Public Participation GIS (PPGIS)	Multi-Criteria Site Selection
สาขาวิชา	Urban Studies	Urban Studies
ตระกูล	Process / pipeline	MCDM
ปีกำเนิด	2006	2006
ผู้ริเริ่ม	Renee Sieber (synthesizing 1990s NCGIA work)	Jacek Malczewski (GIS-MCDA synthesis); Thomas Saaty (AHP weighting)
ประเภท	Participatory integration of local spatial knowledge into GIS	Spatial multi-criteria decision analysis for siting facilities or land uses
แหล่งต้นตำรับ	Sieber, R. (2006). Public participation geographic information systems: A literature review and framework. Annals of the Association of American Geographers, 96(3), 491–507.	Malczewski, J. (2006). GIS-based multicriteria decision analysis: a survey of the literature. International Journal of Geographical Information Science, 20(7), 703–726.
ชื่อเรียกอื่น	PPGIS, Participatory GIS, PGIS, Volunteered Geographic Mapping	GIS-MCDA, Weighted Overlay Suitability, AHP Site Suitability, Spatial Multi-Criteria Evaluation
ที่เกี่ยวข้อง	4	4
สรุป	Public participation GIS (PPGIS) is a family of practices that bring the spatial knowledge, values, and priorities of ordinary people into geographic information systems, so that community perspectives sit alongside expert and official data in planning and decision-making. Synthesized as a field by Renee Sieber in 2006, it ranges from facilitated workshops where residents mark up paper maps to web mapping platforms where thousands of people drop points marking places they value or fear. Its aim is both technical and political: to enrich spatial analysis with local knowledge and to widen who gets to shape decisions about place.	Multi-criteria site selection combines multi-criteria decision analysis (MCDA) with geographic information systems to choose where to locate a facility or land use when many, often conflicting, spatial criteria matter at once. Synthesized as GIS-based MCDA by Jacek Malczewski, it standardizes each criterion layer to a common scale, assigns the criteria importance weights — frequently via Saaty's Analytic Hierarchy Process — and combines them through weighted overlay to produce a suitability surface that ranks every candidate location. The method makes an inherently messy, value-laden siting decision explicit, reproducible, and auditable.