Determination of carbon emissions resulting from land use changes in the European Side of Istanbul

Changes in land cover and land use and the investigation of these changes are crucial to understand the relationship between human and the earth. Land cover represents the physical and vital activities of the area. Land use refers to human behaviors and the influences in the region. Land use and land cover, which affects vital activities and diversities directly of the world have been changing rapidly because of the effects of both people and climate warming. Recently, there are many studies about land use and land cover change around the world. Carbon emissions resulted from land cover and land-use change also necessitated the monitoring of these changes in detail. These changes can be investigate using both terrestrial methods and remote sensing technologies. Investigating land cover and land use using remote sensing data and methods have more advantages than terrestrial methods because they require less time and cost. Spatial and temporal monitoring of land cover change through remote sensing is very important to understand the environmental and social processes that take place on the earth. When evaluating the data in a on a temporal basis, it is important that the compatibility, correctness and comparability of the data. Therefore input data are important in order to produce correct, reliable and consistent output data. Satellite observations are an important source of data in a variety of applications such as land cover land use change and aboveground biomass assessments (carbon stocks, emission factors and carbon stock change monitoring). There are some standards in order to investigate changes in land cover and land use in a certain accuracy and consistency. In this thesis study, Coordination of Information on the Environment (CORINE), Land use, Land-use Change, and Forestry (AKAKDO / LULUCF), Land Cover Classification System (LCCS) and Reduce Emissions From Deforestation and Forest Degradation, and Foster Conservation, Sustainable Management of Forests, and Enhancement of Forest Carbon Stocks mechanism and standards were investigated. Construction projects that have taken place in the European side of Istanbul in recent years have affected the land cover and land use, causing the visible change to occur. The Third Airport and Yavuz Sultan Selim Bridge projects, which cover a large area in Istanbul, have the biggest impact on this change. In addition to these completed projects, the Kanal Istanbul project will greatly affect Istanbul and will cause a major change in land use and land cover. Considering the changes in land cover and land use in the European side of Istanbul, a study area has been identified where large construction projects affect and/or will affect the region. The study area includes some of the districts of Sarıyer, Arnavutköy and Eyüp, covering 68207 hectares for satellite data of 2007 and 68364 hectares for satellite data of 2017. The study area is located between 41° 08 '51 "- 41° 24' 03" North Latitudes and 28° 33 '49"- 29° 08' 14" East Longitudes. The aim of this study is to determine land cover and land use in study area which is a part of the European side of Istanbul using remote sensing data and methods and then to determine carbon stocks and emissions in years between 2007 and 2017. LANDSAT satellite data are useful to determine land use and land cover change because they are accessible and consistent at certain time intervals. LANDSAT satellite data are regarded as one of the primary tools for deforestation detection. In this study, two satellite images LANDSAT 5 Thematic Mapper (TM) acquired in 12 June 2007 and LANDSAT 8 Operational Land Imager (OLI) acquired in 25 July 2017 were used. Atmospheric correction method was applied to the satellite images, in order to eliminate atmospheric and terrain effects of the earth's surface (surface reflectance, ground visibility and temperature) in the images. To determine the land cover and land use of the study area, unsupervised classification method was applied by using LANDSAT satellite images from 2007 and 2017. When the unsupervised classification method was applied, stand type maps of Istanbul in 2003 and 2012, Google Earth and interviews with experts have been considered and examined. Land use classes were determined after reviewing the CORINE Land Cover (CLC) database classification system, which is part of the CORINE project and contains information on land cover and land use. Considering that the determination of carbon stocks and emissions, satellite images were classified into eight classes which are water bodies, needle-leaved forests, broad-leaved forests, grassland, cropland, artificial surfaces, sand dunes and excavation/construction areas. After classification, accuracy assessment and change detection analysis were performed with 30 pixels per 8 classes and total 240 pixels of equally distributed random. As a result of the accuracy assessment of the classified satellite images from 2007 and 2017, the overall accuracy result was determined as %90.83 and Kappa Coefficient was 0.90. Change detection analysis was performed using the post-classification comparison method to determine the spatial distribution of the classes which have changed, and land use change, and the area changes between 2007 and 2017. Carbon emissions from land use changes have been investigated using the method described by the Intergovernmental Panel on Climate Change (IPCC). This method is used to prepare National Greenhouse Gas Inventory Report as required under the Kyoto Protocol for the United Nations Framework Convention on Climate Change Secretariat (UNFCCC Secretariat). Carbon emissions are determined separately for areas where land use which has changed and for areas where land use has not changed, considering the Land Use, Land Use Change and Forestry (AKAKDO / LULUCF) approach. According to land use types, carbon stock values are changing. Carbon pools are classified under three main categories as live biomass carbon pool, dead organic matter pool and soil. Live biomass carbon pool is defined in two categories which are above-ground biomass and below-ground biomass, dead organic matter pool is defined in two categories which are litter and deadwood. Carbon inventories of carbon pools in land use classes have been taken from different sources for the calculation of carbon emissions resulting from land cover and land use changes. Information on land use change obtained by remote sensing data and methods for determining carbon emissions was also used as input. From 2007 to 2017, the biggest reduction in area occurred in the broad-leaved forest class. Subsequently, hectare values for grassland, cropland, needle-leaved forests, water bodies, and sand düne areas have also decreased. In ten years, the land use class which grow the most is the artificial surfaces covering the roads and residential areas. In addition, excavation/contsruction areas increased due to construction projects in the study area. The largest land-use change between 2007 and 2017 occurred with 3929 hectares of land changes from grassland to artificial surfaces. On the other hand, from the grassland to the excavation/contruction areas, 1970 hectares, from the broad-leaved forests to the excavation/contruction areas, 2087 hectares and from the broad-leaved forests to the artificial surfaces 1961 hectares were transformed. Over a period of ten years, carbon stock changes were estimated, statistically analyzed, and carbon emissions determined by examining land use change in the study area. Differences due to land use changes were calculated separately in above-ground biomass, below-ground biomass, litter, deadwood and soil organic matter. Forest areas are an important source of carbon stocks and in this study, it was found that carbon emissions in the atmosphere occurred due to the decrease of forest areas between 2007 and 2017. In addition, the reduction of grassland and cropland have also affected carbon emissions. When carbon emissions from land use changes are examined, the biggest emissions are resulted from the conversion of forest areas to other land use classes. As a result of conversion from other land uses to excavation/construction areas, the highest emissions were generated with 287 thousand t C. Subsequently, the emission value of conversion from other land uses to artificial surfaces has been determined of 225 thousand t C. Between 2007 and 2017, total carbon emission was determined as 485 thousand t C.