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Gis-based Landscape Appreciation Model

Gis-based Landscape Appreciation Model. First steps towards the development of GLAM version 3 Sjerp de Vries Landscape Centre, Alterra, Wageningen The Netherlands. Background.

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Gis-based Landscape Appreciation Model

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  1. Gis-based Landscape Appreciation Model First steps towards the development of GLAM version 3 Sjerp de Vries Landscape Centre, Alterra, Wageningen The Netherlands

  2. Background • GLAM is a model that predicts the attractiveness of the countryside to local residents, based solely on physical characteristics of the landscape on which information is available in national GIS-databases • Version 2 uses four indicators, each with five levels: Naturalness, Historical distinctiveness, Urbanization, Skyline disturbance. • Spatial resolution of the model: 250 x 250 meters (6.25 ha) • Predictive validity is reasonable: 47% of variance explained • In average rating of a demarcated area (>> 6.25 ha) • By people living in or near to it • Problem: usability to evaluate policy measures is still low, because small changes often do not lead to different indicator values

  3. Research questions and method • Level of spatial detail is quite acceptable, but how to improve the sensitivity of the model to more subtle/smaller changes in the physical appearance of the landscape? • Step 1: recalibrate the model based on recently gathered data on landscape appreciation (larger dataset, more areas rated) • Additional indicators available (relief, noise/fragmentation) • Weight of the indicators (regression) • Validation of individual indicators based on aspect ratings • Step 2: error analysis using recalibrated model • Where do predictions deviate most from actual attractiveness scores? • Is there some structure to be discerned in the direction or size of errors? • Spatial clustering • Type of landscape

  4. (Un)planned deliverables • Recalibrated version of GLAM 2 • Based on more/better data • Specific ideas on how to improve GLAM • Redesign existing indicators • Develop additional indicators • Project proposal for developing GLAM version 3 • Actual new & improved version of GLAM: GLAM 3 • Still unplanned; next year

  5. Main results thus far • Recalibrated version of GLAM 2 available • Based on study “Beleving naar gebieden” • About 300 demarcated areas rated by people living nearby • Explained variance: 38% (lower than in previous validation phase!) • Naturalness of the areas as main focus • Adding average rating of naturalness: explained variance 76% • Correlation GIS-indicator with rating of naturalness: r = 0.61 • Quite reasonable already • Correlation of rating of naturalness with prediction error: r = 0.57 • But very important to improve it further • Next steps • Looking at spatial pattern of errors (what is wrong with naturalness?) • Use second dataset for cross validation purposes

  6. International position • Operational model at national level quite rare/unique • Article published on GLAM 2 in international journal • Forest, Snow & Landscape Research, 2007 • Some others working on similar topics (GIS – appreciation/values) • Switzerland: Wald, Schnee und Landschaft (Hunziker, Buchecker) • Finland: METLA (Tyrvainen); Helsinki University of Technology (Kyttä) • Denmark: Forest and Landscape Denmark (Skov-Petersen) • Timely: • European Landscape Convention • Democratising landscape (Fairclough, 2002) • Landscape & Leisure (Dirk Sijmons) • Discussion: experts versus ordinary citizens

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