Carbon based land use land cover optimization of Seyhan basin
Is this your thesis?
This record came from a bulk archive import. If it’s yours, link it to your profile.
Abstract (EN)
The aim of the study was to optimize the carbon-based losses and gains of land cover/use to improve the function of carbon sinks and increase carbon storage in terrestrial ecosystems in the Seyhan Basin. In order to determine the total amount of carbon in this study; (i) biomass carbon, (ii) net primary productivity, (iii) soil organic carbon and (iv) litterfall carbon have been mapped using Remote Sensing (RS) and Geographic Information System (GIS). Past (2000-2010) and current (2020) land use/land cover maps of the Seyhan Basin were derived on the Google Earth Engine platform. Land use/land cover that maximize carbon were determined through the Constrained Multi-objective Optimization of Land use Allocation (CoMOLA) model using the total carbon amount and current land use/land cover maps at the last stage of the study.
Author
Nida Nur Karagedik
How to Cite
Nida Nur Karagedik (Master Thesis). Carbon based land use land cover optimization of Seyhan basin, 2022, Çukurova University.
License
Tüm Hakları Saklıdır
This work is shared under the specified license terms.
More theses from Çukurova University
- An investigation of violent and nonviolent adolescent' families in terms in terms of family fuctioning, anger and anger expression(2006)
- Adolescents who have single parents family and full family were compared in respect to their life satisfaction and quality of life(2009)
- Assessing morphological and genetic diversity among traditional African eggplant landraces and detecting salt tolerance and anther culture performance of selected accessions(2022)
- The effects of collaborative video-blog projects on Turkish EFL students' linguistic and digital literacy skills(2025)
- Cultural significance in foreign learning and teaching with special emphasis on reading comprehension through cultural schemata(1992)
- Credit risk management in banking sector: An application of variables determining credit risk in Turkish banking sector(2011)
