| dc.creator |
Arslan, Emine Seda |
|
| dc.creator |
Örücü, Ömer Kamil |
|
| dc.date |
2021-06-15T00:00:00Z |
|
| dc.date.accessioned |
2023-01-09T12:04:13Z |
|
| dc.date.available |
2023-01-09T12:04:13Z |
|
| dc.identifier |
750068a9-e289-4cee-ab83-05ffe3d166b2 |
|
| dc.identifier |
https://avesis.sdu.edu.tr/publication/details/750068a9-e289-4cee-ab83-05ffe3d166b2/oai |
|
| dc.identifier.uri |
http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/98004 |
|
| dc.description |
<p>This study will be used social media photographs for spatial analysis of recreational ecosystem services (RES) in the city of Antalya (Turkey). 7980 geo-tagged photos (commercial use & mods allowed) from the Flickr photo-sharing platform will be used for determining RES values. The species distribution model will be used for modelling hot spot areas for RES. Natural and cultural landscape values of the study area will be used as environmental variables and point data from the geo-tagged photos as presence-only data for the predicting model. MaxEnt and QGIS software will be use integrally for modelling process. Hotspots for RES will be identified and all environmental variables will be analyzed in terms of their significance degree to the model. This research is thought to contribute landscape planning and management process in terms of protecting hotspot areas with their vital characteristics. On the other hand, this study will be</p><p>presented a novel method for analyzing and mapping intangible ecosystem values.</p> |
|
| dc.language |
eng |
|
| dc.rights |
info:eu-repo/semantics/closedAccess |
|
| dc.title |
A GIS Based Approach for Predicting Recreational Ecosystem Services Hotspots |
|
| dc.type |
info:eu-repo/semantics/conferenceObject |
|