Comparison of different interpolation techniques in determining of agricultural soil index on land consolidation projects

Uyan, Mevlüt

doi:10.26833/ijeg.422570

Cited by 13 publications

(3 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, this method is used to define constantly changing data belonging to the same field. Shaperd's is the most widely used and well-known IDW method [57,58]. Shaperd's Equation 7 is as follows: 𝑓(𝑥, 𝑦) = ∑ 𝑤 𝑖 𝑓 𝑖 𝑛 𝑖 (7) In this formula, n is the number of scattered points on the surface, fi is the function that defines the sampling points, and wi is the weights.…”

Section: Inverse Distance Weighted Interpolation Methods (Idw)mentioning

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

View full text Add to dashboard Cite

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.

show abstract

Section: Inverse Distance Weighted Interpolation Methods (Idw)mentioning

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

View full text Add to dashboard Cite

show abstract

“…Geographic information systems (GIS) are important for decision-makers to better interpret and visualize events and data [26][27][28][29][30]. It is also said that GIS is an important technology for air pollution [31][32][33] and natural disaster studies [34][35][36].…”

Section: Inverse Distance Weighted (Idw)mentioning

confidence: 99%

Seasonal analysis and mapping of air pollution (PM10 and SO2) during Covid-19 lockdown in Kocaeli (Türkiye)

KOTAN

Erener

2023

International Journal of Engineering and Geosciences

View full text Add to dashboard Cite

The Covid-19 epidemic has adversely affected the world in terms of health, education, economic, tourism, social and psychological. During to the epidemic, different measures were taken to prevent the epidemic, such as travel bans, curfews, stopping in production. These measures have reduced and improved air pollution. Within the scope of this study, the change in air pollution in Kocaeli between 2019 and 2021 was examined monthly. PM10 and SO2 maps were created with inverse distance weighted (IDW) technique using geographic information systems technology (GIS). The year 2020, when Covid-19 measures were taken, was compared with 2019 and 2021. Change maps were created by taking the difference between 2020-2019 and 2021-2020 with GIS technology. As a result of the research, it was determined that the level of air pollution decreased in 2020. On the contrary, in 2021, an increase in air pollution levels was observed. In the study, a decrease was observed in PM10 concentration during the Covid-19 lockdowns, however a decrease was not observed for SO2.

show abstract

“…Increasing population [2], air pollution, and reduction of cultivated lands have serious impacts on cereal crops [3] and food security has become a serious problem worldwide. Especially, for agriculture depended on economies like Turkey [4], yields prediction is vital for determining a sustainable supply-demand statistic [5]. In addition, considering in a timely manner predicting yields a few months earlier before harvest provides great advantages for securing national demand, organizing food transport [6,7], forecasting agricultural imports and exports, regulating grain markets, and managing plantations [8,9].…”

Section: Introductionmentioning

confidence: 99%

A linear approach for wheat yield prediction by using different spectral vegetation indices

Kaya

Polat

2023

International Journal of Engineering and Geosciences

View full text Add to dashboard Cite

Yield prediction before harvest is one of the important issues in terms of managing agricultural policies and making the right decisions for the future. Using remote sensing techniques in yield estimation studies is one of the important steps for many countries to reach their 21st-century agricultural targets. The aim of this study is to develop a wheat yield model using Landsat-8 and Sentinel-2 satellite data. In this study, the development stages of winter wheat were examined with the help of satellite images obtained between the years 2015-2018 of a selected region in Sanliurfa, Turkey, and it was aimed to predict the yields for other years by establishing a yield estimation model. The yield estimation model was established with the help of Normalized Difference Vegetation Index (NDVI), Soil-adjusted Vegetation Index (SAVI), Green Normalized Difference Vegetation Index (GNDVI) and Modified Soil-adjusted Vegetation Index (MSAVI) obtained from remote sensing satellite images. Linear regression analysis was established between calculated NDVI, SAVI, GNDVI, MSAVI indices, and actual yield values on the pre-flowering, flowering stage, and postflowering stage. As a result of the study, the highest correlation coefficient was found in the flowering stage between the vegetation indices values and the actual yield values. The values of NDVI, SAVI, GNDVI, and MSAVI and correlation coefficients are obtained in the flowering stage were 0.82, 0.80, 0.86, and 0.87, respectively. With the established model, yield values in 2019 were tried to be estimated for three different fields. The highest correlations were seen in the flowering stage for MSAVI and GNDVI, pre-flowering stage for NDVI and post-flowering stage for SAVI. This clearly shows that the satellite images can be used in yield estimation studies with a remarkable correlation between vegetation indices and actual yield values.

show abstract

Comparison of different interpolation techniques in determining of agricultural soil index on land consolidation projects

Cited by 13 publications

References 27 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

Seasonal analysis and mapping of air pollution (PM10 and SO2) during Covid-19 lockdown in Kocaeli (Türkiye)

A linear approach for wheat yield prediction by using different spectral vegetation indices

Contact Info

Product

Resources

About