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- Spatial and statistical analysis of tourism indicators – contribution to tourism accommodation planningPublication . Lemos, Carlota; Brito, ManuelIntroduction: Considering the importance of tourism in the region of Viseu Dão Lafões which is differentiated by cultural values, thermal resources and wine-growing heritage, technologies of spatial and statistical analysis are essential for strategic planning in tourism in the region. Objectives: Analyze and map the tourism supply and demand, by municipality, regarding annual tourism indicators, with integration of GIS and statistical analysis. Methods: We used data of the INE tourism indicators by municipality and the CAOP2018. GIS was used to delimit the study area, georeferentiation and spatial analysis. Descriptive analysis of differences in tourism indicators between municipalities was integrated applying Kruskal-Wallis test (α = 5%) and cluster analysis. The software SPSS (version 25) and ARCGIS (version 10.5) were used. Results: In the tourism accommodation sector, there are statistically significant differences between municipalities in accommodation capacity, number of guests and overnight stays, total revenue and net bed occupancy rate, especially the differences from Carregal do Sal and Oliveira de Frades to S. Pedro do Sul and Viseu. By cluster analysis applied to every and each indicator under study, the municipalities can be grouped in 4 clusters, despite individual differences. We produced digital cartography to support the main results from spatial and statistical analysis. Conclusion: Despite tourism growth in the region, our study shows statistical differences in the indicators analyzed between municipalities.
- GIS-Based clustering for characterization and implantation of vineyards in region of Távora-VarosaPublication . Brito, Manuel; Lemos, CarlotaIntroduction: In 1989, the Távora-Varosa region was awarded the Denomination of origin, the first national wine-growing region demarcated for the production of sparkling wines. The morphological characteristics allow to create fresh wines with good acidity. Thus, it was intended to characterize and map the region in terms of elevation, slope, aspect and vineyard implantation. Material & Methods: For the delimitation, the specifications of IVV1, CAOP2 and RDD3 limits were used. The altitude data were obtained from ASTER GDEM4. Slope and aspect maps were produced and the region was subdivided into a polygon fishnet 30x30m. The vineyard areas were obtained from COS20155. A cluster analysis with integration of the descriptive analysis using ARCGIS (v10.5) and SPSS (v25). Results: There was an average elevation of 664.03m, maximum of 1106m and minimum of 193m, average slope of 9.210 and maximum of 45.040, being approximately 40% of the area of vineyard located above 600m. We agrouped the region in 7 clusters according to the study variables and produced a digital cartography to support the analysis results. Conclusion: This study designed of a tool to support decision-making for the implementation of vineyard areas depending on the characteristics for the final product.