Sürdürülebilir Kalkınma Amaçları
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- MakaleAçık Erişim2023Assessing Spatio-Temporal Change and Dynamics of Forest Ecosystem Succession Using Patch Analysis
Sivrikaya, Fatih; Çakir, Gunay
Aim of study: This study focuses on creating a secondary forest succession (SFS) map between 1972 and 2014 according to the Clementsian theory based on land cover, assessing the spatio-temporal pattern of forest succession change, and determining the factors affecting the forest ecosystem.Area of study: This study was conducted at the cermik Forest Enterprise (FE) in Diyarbakir city, located in the Southeastern Anatolia Region of Turkiye.Material and methods: Clementsian theory, Remote Sensing (RS), and Geographical Information System (GIS) were used to generate the SFS map. Patch Analyst 4.0 was used to determine changes in spatiotemporal patterns with landscape indices.Main results: The total forested area increased from 32405.1 ha (13% of the study area) in 1972 to 45054.7 ha (18% of the study area) in 2014, with a net increase of 12649.6 ha. It was determined that the progressive succession area was 87736.7 ha, the regressive succession area was 39216.5 ha, and the unchanged succession area was approximately 129989.6 ha. The number of patches increased over a 42 -year period.Research highlights: The forest ecosystem was more fragmented, with patches becoming more irregular, complex, and edgy.
- MakaleAçık Erişim2018Comparison of landscape metrics for three different level land cover/land use maps
Sertel, Elif; Topaloğlu, Raziye Hale; Şallı, Betül; Algan, Irmak Yay; Aksu, Gül Aslı
This research aims to investigate how different landscape metrics are affected by the enhancement of the thematic classes in land cover/land use (LC/LU) maps. For this aim, three different LC/LU maps based on three different levels of CORINE (Coordination of Information on The Environment) nomenclature were created for the selected study area using GEOBIA (Geographic Object Based Image Analysis) techniques. First, second and third level LC/LU maps of the study area have five, thirteen and twenty-seven hierarchical thematic classes, respectively. High-resolution Spot 7 images with 1.5 m spatial resolution were used as the main Earth Observation data to create LC/LU maps. Additional geospatial data from open sources (OpenStreetMap and Wikimapia) were also integrated to the classification in order to identify some of the 2nd and 3rd level LC/LU classes. Classification procedure was initially conducted for Level 3 classes in which we developed decision trees to be used in object-based classification. Afterwards, Level 3 classes were merged to create Level 2 LC/LU map and then Level 2 classes were merged to create the Level 1 LC/LU map according to CORINE nomenclature. The accuracy of Level 1, Level 2, Level 3 maps are calculated as; 93.50%, 89.00%, 85.50% respectively. At the last stage, several landscape metrics such as Number of Patch (NP), Edge Density (ED), Largest Patch Index (LPI), Euclidean Nearest Neighbor Distance (ENN), Splitting Index (SPLIT) and Aggregation Index (AI) metrics and others were calculated for different level LC/LU maps and landscape metrics values were compared to analyze the impact of changing thematic details on landscape metrics. Our results show that, increasing the thematic detail allows landscape characteristics to be defined more precisely and ensure comprehensive assessment of cause and effect relationships between classes.