dor_id: 4133101
506.#.#.a: Público
590.#.#.d: Los artículos enviados a la revista "Geofísica Internacional", se juzgan por medio de un proceso de revisión por pares
510.0.#.a: Consejo Nacional de Ciencia y Tecnología (CONACyT); Scientific Electronic Library Online (SciELO); SCOPUS, Dialnet, Directory of Open Access Journals (DOAJ); Geobase
561.#.#.u: https://www.geofisica.unam.mx/
650.#.4.x: Físico Matemáticas y Ciencias de la Tierra
336.#.#.b: article
336.#.#.3: Artículo de Investigación
336.#.#.a: Artículo
351.#.#.6: http://revistagi.geofisica.unam.mx/index.php/RGI
351.#.#.b: Geofísica Internacional
351.#.#.a: Artículos
harvesting_group: RevistasUNAM
270.1.#.p: Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx
590.#.#.c: Open Journal Systems (OJS)
270.#.#.d: MX
270.1.#.d: México
590.#.#.b: Concentrador
883.#.#.u: https://revistas.unam.mx/catalogo/
883.#.#.a: Revistas UNAM
590.#.#.a: Coordinación de Difusión Cultural
883.#.#.1: https://www.publicaciones.unam.mx/
883.#.#.q: Dirección General de Publicaciones y Fomento Editorial
850.#.#.a: Universidad Nacional Autónoma de México
856.4.0.u: http://revistagi.geofisica.unam.mx/index.php/RGI/article/view/789/1353
100.1.#.a: Murat, Valerie; Rivera, Alfonso; Pouliot, Jacynthe; Miranda-salas, Marcelo; Savard, Martine M.
524.#.#.a: Murat, Valerie, et al. (2004). Aquifer vulnerability mapping and GIS: A proposal to monitor uncertainty associated with spatial data processing. Geofísica Internacional; Vol. 43 Núm. 4: Octubre 1, 2004; 551-565. Recuperado de https://repositorio.unam.mx/contenidos/4133101
245.1.0.a: Aquifer vulnerability mapping and GIS: A proposal to monitor uncertainty associated with spatial data processing
502.#.#.c: Universidad Nacional Autónoma de México
561.1.#.a: Instituto de Geofísica, UNAM
264.#.0.c: 2004
264.#.1.c: 2004-10-01
653.#.#.a: Monitoreo de incertidumbre; análisis de vulnerabilidad; recursos subterráneos; SIG; DRASTIC; Uncertainty monitoring; vulnerability analysis; groundwater resources; GIS; DRASTIC model
506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC-SA 4.0 Internacional, https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico revistagi@igeofisica.unam.mx
884.#.#.k: http://revistagi.geofisica.unam.mx/index.php/RGI/article/view/789
001.#.#.#: 063.oai:revistagi.geofisica.unam.mx:article/789
041.#.7.h: spa
520.3.#.a: An aquifer assessment was undertaken by the Geological Survey of Canada to estimate the sustainability and aquifer vulnerability in the St. Lawrence Lowlands of south western Quebec. The DRASTIC model and GIS was used to calculate and produce vulnerability maps. A detailed monitoring of data processing was performed to control the accuracy of the vulnerability maps. Overall estimates involved identifying errors and uncertainty associated with spatial and descriptive data used to run the model. The data analysed was related to wells, drillings, thematic maps, and also multiple processing data including errors and uncertainty attributed to calculations of the hydraulic conductivity, data interpolations, intersections of spatial data layers, etc. A categorization system using the Unified Modeling Language (UML) was proposed to categorize spatial data with respect to the degree and sources of possible uncertainties. This article presents the categorization system used, an example of an application for an study area and a discussion around its usefulness in controlling data processing (GIS and model integration). This work shows that uncertainty associated with spatial data processing and integrating data to a numerical system can be very significant, the main ambiguity occurring when cleaning data, interpolating, classifying and overlaying. Uncertainty characterization on the data processes was a valuable source of information. Monitoring the uncertainty associated with spatial data processing is almost more important to assemble than the model itself. However uncertainty monitoring may be complex and subjective and in fact it is rarely done on a regular basis mainly because it requires much more efforts compare to simply running the model.doi: https://doi.org/10.22201/igeof.00167169p.2004.43.4.789
773.1.#.t: Geofísica Internacional; Vol. 43 Núm. 4: Octubre 1, 2004; 551-565
773.1.#.o: http://revistagi.geofisica.unam.mx/index.php/RGI
022.#.#.a: ISSN-L: 2954-436X; ISSN impreso: 0016-7169
310.#.#.a: Trimestral
300.#.#.a: Páginas: 551-565
264.#.1.b: Instituto de Geofísica, UNAM
doi: https://doi.org/10.22201/igeof.00167169p.2004.43.4.789
handle: 0097ce5368d8d45c
harvesting_date: 2023-06-20 16:00:00.0
856.#.0.q: application/pdf
file_creation_date: 2022-07-08 08:56:19.0
file_modification_date: 2022-07-15 18:36:12.0
file_creator: Valerie Murat
file_name: 852311d79dec2ce03a769a54065407d6eaf7f9ff71ca03300d5b4b4d44a59fee.pdf
file_pages_number: 16
file_format_version: application/pdf; version=1.3
file_size: 3411863
245.1.0.b: Aquifer vulnerability mapping and GIS: A proposal to monitor uncertainty associated with spatial data processing
last_modified: 2023-06-20 16:00:00
license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es
license_type: by-nc-sa
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