Rodrigues, M.; Arsénio, P.; Paço, T.A. The Use of Drought-Tolerant Vegetation on Green Roofs: A Method for the Digital Photographic Monitoring of Its Development. Horticulturae2024, 10, 106.
Rodrigues, M.; Arsénio, P.; Paço, T.A. The Use of Drought-Tolerant Vegetation on Green Roofs: A Method for the Digital Photographic Monitoring of Its Development. Horticulturae 2024, 10, 106.
Rodrigues, M.; Arsénio, P.; Paço, T.A. The Use of Drought-Tolerant Vegetation on Green Roofs: A Method for the Digital Photographic Monitoring of Its Development. Horticulturae2024, 10, 106.
Rodrigues, M.; Arsénio, P.; Paço, T.A. The Use of Drought-Tolerant Vegetation on Green Roofs: A Method for the Digital Photographic Monitoring of Its Development. Horticulturae 2024, 10, 106.
Abstract
The increased number of buildings in urban areas limits the creation of vegetated areas, leading to the search for alternatives to create spaces to promote contact with nature. In this context, green roofs have been increasingly studied. These structures have specific microclimatic condi-tions requiring an accurate study of the most appropriate vegetation to use. This study aims to analyze the long-term viability of vegetation installed on an experimental green roof open-air lab. This analysis was done through images obtained from photographic records and later in-serted into the ImageJ program, to identify species and evaluate the area covered by vegetation. Only a few of the species that were planted in the test beds over the years have persisted to the present, while other species have spontaneously appeared. Also, surveys were used to learn about people's preferences for the vegetation on these test beds. These showed that people favor recognizable plants with plenty of vibrantly colored blossoms. It was feasible to choose the best plants for green roofs in the studied conditions as a result of the analysis, taking into account the ground cover percentage by vegetation, its persistence, and the preferences of the respondents.
Keywords
native plants; digital image analysis; population preferences; ImageJ
Subject
Biology and Life Sciences, Agricultural Science and Agronomy
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
