d3d76fa7-d1da-472b-920a-3ff2bca90290 English MD_CharacterSetCode_utf8 Individual item (e.g. a one-off academic paper or single website) British Geological Survey Contact for the metadata enquiries@bgs.ac.uk pointOfContact 2024-11-07 ISO19115 2003/Cor.1:2006 Arc SDM - Spatial Data Modeller for ArcGIS and Spatial Analyst 2008-03-01 creation 2008-03-01 publication 2010-07-01 revision 10 MICA WP3 2018-11-03T15:16:00 Record extracted from Batch 3 spreadsheet MICA_B3-5 https://www.mica-project.eu/ No other citation details provided Spatial Data Modeller, SDM, is a collection of tools for use with GIS software for adding categorical maps with interval, ordinal, or ratio scale maps to produce a predictive map of where something of interest is likely to occur. The tools include the data-driven methods of Weights of Evidence, Logistic Regression, and two supervised and one unsupervised neural network methods, and categorical tools for a knowledge-driven method Fuzzy Logic. All of the tools have help files that include references to publications discussing the applications of the methods implemented in the tool. Several of the tools create output rasters, tables, or files that require the user to enter a name. Default values are provided in most cases to serve as suggestions of the style of naming that has been found useful. These names, following ArcGIS conventions, can be changed to meet the user’s needs. To make all of the features of SDM work properly it is required that several Environment parameters are set. See the discussion of Environment Settings below for the details. The Weights of Evidence, WofE, and Logistic Regression, LR, tools addresses area as the count of unit cells. It is assumed in the WofE and LR tools that the data has spatial units of meters. If your data has other spatial units, these WofE and LR tools may not work properly. Website: http://www.ige.unicamp.br/sdm/ Purpose for data generation is not known University of Campinas Contact for the resource described by the metadata Campinas 13083-970 Brazil http://www.ige.unicamp.br/sdm/ WWW:LINK-1.0-http--link http://www.ige.unicamp.br/sdm/ Link for further information on the resource Party that supplies the resource https://resources.bgs.ac.uk/images/minerals/micaGraphic/B3/MICA_B3-5.JPG MICA dataCentre Recent (includes data from 2006 onwards) MICA ontology (TemporalScheme) 2 General descriptive information / Website / Other (Website) MICA ontology (DataScheme) 2 Requirement for data generation: Voluntary Method of data or information generation: Academic research Exploration GEMET Concepts 2014-07-25 revision 2 Mineral exploration MICA ontology (DomainScheme) 2 Regional reconnaissance MICA ontology (DomainScheme) 2 2D predictive mapping MICA ontology (DomainScheme) 2 Mineral resources potential assessment/estimating undiscovered resources MICA ontology (DomainScheme) 2 Exploration MICA ontology (ValueSupplyChainScheme) 2 Regional reconnaissance MICA ontology (ValueSupplyChainScheme) 2 Available for free for all purposes Not confidential English geoscientificInformation economy Not applicable Other group of countries (please provide more details) Individual item (e.g. a one-off academic paper or single website) Data uncertainty Are any uncertainty measures provided (e.g. standard errors, confidence intervals, etc.)? false Quality assurance procedures Are quality assurance procedures described? false Information generation methods Are data or information generation methods formally described? true Record review Reviewed by: British Geological Survey Record validation false Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 Organisation source implies that information should be of good quality Metadata is distributed with a CC BY-ND 4.0 (Attribution-NoDerivs 4.0 International) licence