Modeling land use/land cover change using remote sensing and geographic information systems: case study of the Seyhan Basin,Turkey

Land use and land cover (LULC) changes affect several natural environmental factors, including soil erosion, hydrological balance, biodiversity, and the climate, which ultimately impact societal well-being. Therefore, LULC changes are an important aspect of land management. One method used to analyze LULC changes is the mathematical modeling approach. In this study, Cellular Automata and Markov Chain (CA-MC) models were used to predict the LULC changes in the Seyhan Basin in Turkey that are likely to occur by 2036. Satellite multispectral imagery acquired in the years 1995, 2006, and 2016 were classified using the object-based classification method and used as the input data for the CA-MC model. Subsequently, the post-classification comparison technique was used to determine the parameters of the model to be simulated. The Markov Chain analyses and the multi-criteria evaluation (MCE) method were used to produce a transition probability matrix and land suitability maps, respectively. The model was validated using the Kappa index, which reached an overall level of 77%. Finally, the LULC changes were mapped for the year 2036 based on transition rules and a transition area matrix. The LULC prediction for the year 2036 showed a 50% increase in the built-up area class and a 7% decrease in the open spaces class compared to the LULC status of the reference year 2016. About an 8% increase in agricultural land is also likely to occur in 2036. About a 4% increase in shrub land and a 5% decrease in forest areas are also predicted.     

Quantifying coastal inundation vulnerability of Turkey to sea-level rise

The vulnerability of low-lying coastal areas in Turkey to inundation was quantified based on the sea-level rise scenarios of 1, 2, and 3 m by 2205. Through digital elevation model (DEM) acquired by the shuttle radar topography mission (SRTM), the extent and distribution of the high to low-risk coastal plains were identified. The spatio-temporal analysis revealed the inundated coastal areas of 545, 1,286, and 2,125 km² at average rates of 5, 10, and 15 mm yr⁻¹ for 200 years, respectively. This is equivalent to minimum and maximum land losses by 2205 of 0.1–0.3% of the total area and of 1.3–5.2% of the coastal areas with elevations of less than 100 m in the country, respectively. This study provides an initial assessment of vulnerability to sea-level rise to help decision-makers, and other concerned stakeholders to develop appropriate public policies and land-use planning measures.     

Quantifying Carbon Budgets Of Conifer Mediterranean Forest Ecosystems, Turkey

Abstact Aboveground biomass, aboveground litterfall, and leaf litter decomposition of five indigenous tree stands (pure stands ofPinus brutia,Pinus nigra,Cedrus libani,Juniperus excelsa, and a mixed stand ofAbies cilicica,P. nigra, andC. libani) were measured in an eastern Mediterranean evergreen needleleaf forest of Turkey. Measurements were converted to regional scale estimates of carbon (C) stocks and fluxes of forest ecosystems, based on general non-site-specific allometric relationships. Mean C stock of the conifer forests was estimated as 97.8± 79 Mg C ha⁻¹consisting of 83.0 ± 67 Mg C ha⁻¹in the aboveground and 14.8 ± 12 Mg C ha⁻¹in the belowground biomass. The forest stands had mean soil organic carbon (SOC) and nitrogen (SON) stocks of 172.0 ± 25.7 Mg C ha⁻¹and 9.2 ± 1.2 Mg N ha⁻¹, respectively. Mean total monthly litterfall was 376.2± 191.3 kg C ha⁻¹, ranging from 641 ± 385 kg C ha⁻¹forPinus brutiato 286 ± 82 kg C ha⁻¹forCedrus libani. Decomposition rate constants (k) for pine needles were 0.0016 forCedrus libani, 0.0009 forPinus nigra, 0.0006 for the mixed stand, and 0.0005 day⁻¹forPinus brutiaand Juniperus excelsa. Estimation of components of the C budgets revealed that the forest ecosystems were net C sinks, with a mean sequestration rate of 2.0 ± 1.1 Mg C ha⁻¹ yr⁻¹ranging from 3.2 ± 2 Mg C ha⁻¹forPinus brutiato 1.6 ± 0.6 Mg C ha⁻¹forCedrus libani. Mean net ecosystem productivity (NEP) resulted in sequestration of 98.4 ± 54.1 Gg CO₂ yr⁻¹from the atmosphere when extrapolated for the entire study area of 134.2 km²(Gg = 10⁹ g). The quantitative C data from the study revealed the significance of the conifer Mediterranean forests as C sinks