| Records |
| Author |
Ploner, A.; Brandenburg, C., |
| Title |
Modelling the Dependency between Visitor Numbers and Meteorological Variables via Regression Trees |
Type |
|
| Year |
2002 |
Publication |
Monitoring and Management of Visitor Flows in Recreational and Protected Areas |
Abbreviated Journal |
|
| Volume |
MMV 1 - Proceedings |
Issue |
|
Pages |
225-232 |
| Keywords |
MMV1 |
| Abstract |
We propose using regression trees as a flexible and intuitive tool for modelling the relationship between weather conditions and day to day changes of the visitor load in outdoor recreation areas. Regression trees offer a number of advantages when compared e.g. to linear models, specifically by outlining different seasonal and meteorological scenarios. When applied to video monitoring data from the Lobau, an Austrian nature conservation area, good regression tree models for the total number of visitors and the counts for some visitor categories (bikers, hikers, swimmers) were found, while other categories could not be adequately represented (dog walkers, joggers). The regression trees indicate a strong relationship between weather and total visitor numbers, as well as weather and the number of bikes and swimmers, respectively. The relationship to weather was found to be only slight for hikers and dog walkers, and completely absent for joggers. In general, the use of derived meteorological quantities in form of thermic comfort indices for characterizing weather conditions results in better models than the use of directly observable meteorological quantities. |
| Call Number |
ILEN @ m.sokopp @ 480 |
Serial |
2303 |
| Permanent link to this record |
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| Author |
Brandenburg, C.; Ploner, A., |
| Title |
Models to Predict Visitor Attendance Levels and the Presence of Specific User Groups |
Type |
|
| Year |
2002 |
Publication |
Monitoring and Management of Visitor Flows in Recreational and Protected Areas |
Abbreviated Journal |
|
| Volume |
MMV 1 - Proceedings |
Issue |
|
Pages |
166-172 |
| Keywords |
MMV1 |
| Abstract |
This paper proposes approaches to modeling visitor flows in the context of weather and outdoor recreation. The nature conservation area and area under investigation the Lobau, which is a part of the Danube Floodplains National Park, lies in close proximity to the large conurbation of Vienna, the capital city of Austria. This circumstance presents the managers and researchers of the Lobau with a variety of challenging problems, due to the high number of visitors and the multifaceted visitor structure. An ecologically and economically sustainable management of the recreation and conservation area Lobau requires a profound knowledge of the uses visitors make of this area and a reliable prediction of the potential numbers of visitors. The investigation of the prognostic model is based on the results of a visitor monitoring project. Within this project, video-cameras were installed at several entrance points to the Lobau to monitor recreational activities throughout one year. The prognostic models were based on the dependence of the daily number of visitors on external factors such as weather and day of the week. Using a linear regression, these relationships were investigated and used to predict visitor loads. For the model, a distinction was made between workdays and weekends and/or holidays. The weather was considered in a very differentiated way: Meteorological elements, i.e. air temperature, cloud cover, precipitation, appear directly as parameters in the models as well as indirectly in thermal comfort indices, e.g. the Physiological Equivalent Temperature (PET). Reliable models can be obtained for the daily totals of visitors as well as for specific user groups with high visitor loads, i.e. hikers and bikers. The day of the week has the greatest influence on the daily totals of visitors as well as on individual user groups. The numbers of bikers and hikers depend heavily on the Physiological Equivalent Temperature. The effects of precipitation and cloud cover during the preceding seven days are small. The usage patterns of joggers and dog walkers are more difficult to model as they are less influenced by the day of the week and weather related factors. |
| Call Number |
ILEN @ m.sokopp @ 462 |
Serial |
2294 |
| Permanent link to this record |
