Thornthwaite İklim Sınıflandırma Yöntemine Göre Karadeniz Bölgesi İklim Sınır Haritasının CBS İle Üretilmesi

Çolak, Ebru; Memişoğlu, Tuğba

doi:10.29128/geomatik.651702

Cited by 11 publications

(2 citation statements)

References 23 publications

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“…It differs from other interpolation methods because it measures the confidence level of the estimated value with variance. This method achieves more unbiased results than other interpolation techniques; investigates the accuracy of the estimation in terms of the minimum variance and the calculation of the standard deviation of the realized estimation [53][54][55].…”

Section: Kriging Interpolation Methodsmentioning

confidence: 99%

Production of fuel-based carbon footprint distribution map using spatial interpolation methods based on GIS

ÇOLAK,

MEMİŞOĞLU BAYKAL,

GENÇ

2024

International Journal of Engineering and Geosciences

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The Earth is a complex system where living and non-living elements coexist in a delicate balance. Climate change is the primary factor responsible for the degradation of this system over time. The far-reaching consequences of climate change impact various aspects of our lives, including the physical environment, urban settings, human activities, economy, technology, agriculture, food production, access to clean water, and public health, all of which are widely acknowledged. Human-induced greenhouse gas emissions in these areas significantly trigger global climate change. Hence, addressing and mitigating the environmental damage from these emissions and the interconnected climate change phenomena is imperative. This situation is where the concept of "carbon footprint" gains prominence in assessing the extent of this damage. Carbon footprint serves as an essential measure in managing and curbing climate change. This study focused on controlling and mitigating carbon emissions, one of the primary greenhouse gasses responsible for climate change, by implementing spatial interpolation techniques based on Geographic Information Systems (GIS). The investigation targeted the Beşirli neighborhood in the Ortahisar district of Trabzon province. Data concerning electricity and natural gas usage were acquired from relevant institutions to perform carbon footprint calculations. Subsequently, carbon footprint calculations were conducted utilizing the acquired data within the specified region. The resulting outputs were systematically organized, integrated into the GIS environment, and linked to their respective geographical locations. Eventually, region-specific carbon footprint distribution maps were generated using selected spatial interpolation methods. These maps enabled a spatial observation of points exhibiting variability in terms of carbon emissions, thereby highlighting the carbon footprints evident in the region. The ultimate goal of this endeavor is to propose practical measures for minimizing the adverse environmental impacts by suggesting strategies to reduce and prevent carbon footprints associated with carbon emissions in the relevant areas.

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Section: Kriging Interpolation Methodsmentioning

confidence: 99%

Production of fuel-based carbon footprint distribution map using spatial interpolation methods based on GIS

ÇOLAK,

MEMİŞOĞLU BAYKAL,

GENÇ

2024

International Journal of Engineering and Geosciences

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“…The spatial relationship of these data with the meteorological station points was then established. Although the Thornthwaite and Aydeniz algorithms were included in the developed interface model, they were not included in the results in this study because another study had previously reported on the Thornthwaite method (Colak and Memisoglu, 2021) and the map resulting from the Aydeniz method was not produced with real data and, therefore, could not be tested over the interface model. The parameters determined for the other methods were obtained in line with the inter-agency correspondence of the General Directorate of Meteorology with the relevant institutions in the form of data recorded from 13 meteorological stations over the 30-year period between 1988 and 2018.…”

Section: Methodsmentioning

confidence: 99%

Producing climate boundary maps using GIS interface model designed with Python

Baykal

Colak

2021

Progress in Physical Geography: Earth and Environment

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Climate and its effects need to be examined within a more planned and comprehensive framework to prevent the unfavorable impact of climate change. Thus, climate effects on the ecosystem can be identified by determining the geographical boundaries of different climate types. The Köppen, Trewartha, Thornthwaite, Erinc, Aydeniz, De Martonne, and De Martonne–Gottman methods are used in the classification of climates. These methods enable the regional differences of climate types to be determined and their changes over the years to be examined. A number of studies examining climate classes have produced graphic findings and maps. The absence of new approaches has resulted in climate classifications still being carried out via manual studies. However, a program for identifying and representing these methods in a convenient, fast, and automated way could facilitate the completion of analyses in a shorter time. The programming languages developed in recent years have made it easy to design interface models that can perform analyses faster and easier than prolonged manual methods. In this study, a climate boundary determination interface model, designed using the Python programming language, was developed for use in the ArcGIS 10.6 program to determine geographical climate boundaries automatically. The provinces of Artvin, Ordu, Rize, Trabzon, Giresun, Bayburt, and Samsun (Turkey) were chosen as the study area to test the interface model. The resulting interface model design is expected to: (1) address the dimensions of climate change in Intergovernmental Panel on Climate Change studies; (2) identify the climate changes in our country as an objective of the National Climate Change Strategy; and (3) determine the land-use changes caused by climate boundaries and examine the ownership dimension of the adaptation process in the declaration published by the International Geodesy Federation in 2014.

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Determining climate classifications and producing climate border maps with GIS of Muğla province on the southern Aegean Sea coast of Türkiye

Arca,

Keskin Citiroglu

2024

Theor Appl Climatol

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Climate is defined by the average of meteorological events observed over an extended period in a region, expressing the weather conditions of that area. Numerous scientists have developed various climate classifications. The fundamental purpose of these classifications is to distinguish different types of climates and thereby reveal similarities between regions. Such classifications can be based on factors like temperature and precipitation patterns. Understanding climate characteristics enables us to determine the boundaries of different climate types. This, in turn, is crucial for ensuring the sustainable use of regional resources and shaping land use plans. This study evaluates the process of creating climate boundary maps for Muğla province. Various climate classification methods, including Thornthwaite, Trewartha, Erinç, De Martonne, Köppen─Geiger, and Köppen, are comprehensively examined and compared. Our findings indicate that each method offers different approaches to defining Muğla’s climate, each with its unique advantages and limitations. For instance, while the Thornthwaite method provides detailed data, the Köppen─Geiger method offers a more generalized approach. The results suggest that combining various climate classification methods helps in more accurately and comprehensively mapping the climate boundaries of Muğla province. This study underscores the importance of integrating these diverse methods to contribute to the determination of climate boundaries and regional planning processes.

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Thornthwaite İklim Sınıflandırma Yöntemine Göre Karadeniz Bölgesi İklim Sınır Haritasının CBS İle Üretilmesi

Cited by 11 publications

References 23 publications

Production of fuel-based carbon footprint distribution map using spatial interpolation methods based on GIS

Production of fuel-based carbon footprint distribution map using spatial interpolation methods based on GIS

Producing climate boundary maps using GIS interface model designed with Python

Determining climate classifications and producing climate border maps with GIS of Muğla province on the southern Aegean Sea coast of Türkiye

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