The purpose of this study was to present possibilities of using available Volunteered Geographic Information (VGI) created by users of Flickr to monitor activity in the forest areas within the Warsaw agglomeration. The paper indicates which forest complexes (municipal or agglomeration) were most frequently visited as well as the dates of the greatest use of forest areas in daily, weekly and monthly terms. The study objects include forest areas located in Warsaw and in 52 communes constituting the Warsaw agglomeration. The Kampinos National Park (KPN), which is under strong recreational pressure from the inhabitants of Warsaw agglomeration, was also analysed. In total, we used 1180 images from the Flickr portal in the study. The most visited place was the Kampinos National Park (18.7%), then the forest area in the Legionowo commune (10.7%), which constitute one large forest complex with forests in Choszczówka. Large, compact municipal forest complexes (e.g. Bielański and Linde (8.2%), Sobieski (7.4%) and Kabaty (5.3%)), as well as forests within the Mazowiecki Landscape Park (6.3%) were also very popular. Fraction of photos taken in municipal forests of Warsaw as well as in the agglomeration and KPN forests was larger on Saturdays and Sundays than on business days. It amounted to 51.7% and 59.3%, in forests of a given category respectively. Pictures from the agglomeration and KPN forest areas were most often taken in May (13.8%), while the least often in December (3.3%). Fraction of people visiting municipal forests of Warsaw was the largest in December (12.3%) and the lowest in July (5.0%). On a daily basis, the most activity in both categories was recorded between 11−18. The use of VGI data from the Flickr portal enabled spatial and temporal analysis of user activity in urban and suburban forests. The results obtained confirm current research using survey forms, but in contrast to them, they show the actual places visited for recreation. It should be emphasized that due to the privacy policy of portals, VGI data do not contain information about the metric and status of the user, which makes the analyses inadequate for the entire population.

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