International Journal of Environment and Geoinformatics最新文献_第6页

Estimation of Urban Area Change in Eskişehir Province Using Remote Sensing Data and Machine Learning Algorithms 基于遥感数据和机器学习算法估算eski<e:1>省城市面积变化

International Journal of Environment and Geoinformatics Pub Date : 2023-03-15 DOI: 10.30897/ijegeo.1162153

Dilek Küçük Matcı

引用次数: 0

Estimation of Greenhouse Gas Emission and Global Warming Potential of Livestock Sector; Lake District, Türkiye 畜牧业温室气体排放与全球变暖潜势的估算湖区，<s:1> rkiye

International Journal of Environment and Geoinformatics Pub Date : 2023-03-12 DOI: 10.30897/ijegeo.1194702

K. Kumaş, A. Akyüz

{"title":"Estimation of Greenhouse Gas Emission and Global Warming Potential of Livestock Sector; Lake District, Türkiye","authors":"K. Kumaş, A. Akyüz","doi":"10.30897/ijegeo.1194702","DOIUrl":"https://doi.org/10.30897/ijegeo.1194702","url":null,"abstract":"The calling on livestock is increasing fast because of the population and economic broadening. In recent years, the contribution of the livestock sector to greenhouse gas emissions and climate change has been a concern. This sector accounts for the second largest share of anthropogenic greenhouse gas emissions after the energy sector. The storage of animal manure is very important in this respect. Because gases such as nitrous oxide and methane, which are important greenhouse gases, are formed during storage. Therefore, it is very important to focus on this area to make manure management systems sustainable. In this study, greenhouse gas emissions that may occur in the provinces located in the region called Turkey's Lakes Region were estimated using the data on the number of different species of animals published in 2016-2020. Evolution by years has been evaluated on a provincial basis. The global warming potential created by greenhouse gas emissions has been determined. As an animal species in the study; dairy and beef cattle, buffalo, sheep, goat, donkey-mule, meat and laying chicken, turkey, duck, and goose were used. 1567000 tons of CH4 emission has occurred due to the total enteric fermentation of animal origin. The amount of CH4 calculated based on manure management is 22450 tons. The CO2 equivalent amount of CH4 emission due to manure management and enteric fermentation was calculated as 33380500 tons. The total amount of direct and indirect N2O emissions from manure management in 2016-2020 is 12566.10 tons. CO2 emission originating from N2O emission was obtained as 555743.46 tons.","PeriodicalId":176110,"journal":{"name":"International Journal of Environment and Geoinformatics","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124025256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Determination of Urban Areas Using Google Earth Engine and Spectral Indices; Esenyurt Case Study 利用Google Earth引擎和光谱指数确定城市面积Esenyurt案例研究

International Journal of Environment and Geoinformatics Pub Date : 2023-03-05 DOI: 10.30897/ijegeo.1214001

Zelal Kaya, A. Dervisoglu

{"title":"Determination of Urban Areas Using Google Earth Engine and Spectral Indices; Esenyurt Case Study","authors":"Zelal Kaya, A. Dervisoglu","doi":"10.30897/ijegeo.1214001","DOIUrl":"https://doi.org/10.30897/ijegeo.1214001","url":null,"abstract":"Identifying impervious surfaces for monitoring urban expansion is important for the sustainable management of land resources and the protection of the environment. Remote sensing provides an important data source for urban land use/land cover mapping, and these data can be analyzed with various techniques for different purposes. If the aim is to extract information easily and rapidly, using spectral indices is the most appropriate solution, and there are many indices created for this purpose. The study carried out on the Google Earth Engine (GEE) platform, Esenyurt, the most populous district of Istanbul, was investigated using Sentinel 2 MSI image, with eight urban spectral indices and three vegetation indices. In addition, classification was made, and the results were evaluated. As a result of the urban index applications, it has been seen that the roofs are more or less mixed with the bare soil areas, and Normalized Difference Tillage Index (NDTI)gives the best results. Accuracy assessment is performed for index results and classification using the same points, and due to the urban area density in the application area, it is determined as 0.95% and 0.95% for NDTI and Normalized Difference Vegetation Index (NDVI), and 97% for classification, respectively. In GEE, a high (-0.79) negative correlation is observed between May mean values and 2007-2022 population data when the NDVI time series was applied to the entire area within the district borders using Landsat 5 and Landsat 8 images between 1990-2022. The rapidly increasing population in the district leads to rapid urbanization, and green areas are disappearing at the same rate.","PeriodicalId":176110,"journal":{"name":"International Journal of Environment and Geoinformatics","volume":"61 22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125782744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Anthropogenically-Induced Ecological Risks in Lake Gala, Thrace, NW Turkey 土耳其西北部色雷斯加拉湖的人为生态风险

International Journal of Environment and Geoinformatics Pub Date : 2023-03-05 DOI: 10.30897/ijegeo.1181757

Erdal Öztura

引用次数: 1

Application of Remote Sensing and Geographical Information System (GIS) in Flood Vulnerability Mapping: A Scenario of Akure South, Nigeria 遥感与地理信息系统(GIS)在洪水易损性制图中的应用——以尼日利亚阿库雷南部为例

International Journal of Environment and Geoinformatics Pub Date : 2023-03-05 DOI: 10.30897/ijegeo.1073697

Ibrahim Olatunji Raufu, Ibrahim Mukai̇la, Kafayat Olani̇yan, Zachariah Awodele

{"title":"Application of Remote Sensing and Geographical Information System (GIS) in Flood Vulnerability Mapping: A Scenario of Akure South, Nigeria","authors":"Ibrahim Olatunji Raufu, Ibrahim Mukai̇la, Kafayat Olani̇yan, Zachariah Awodele","doi":"10.30897/ijegeo.1073697","DOIUrl":"https://doi.org/10.30897/ijegeo.1073697","url":null,"abstract":"In flooding, dry land capable of residential, agricultural, and other economic activities is submerged by overflowing water. This causes loss of lives, properties, and destruction of infrastructure. This study applies remote sensing and GIS techniques to produce a flood vulnerability map of the Akure South metropolis. For this study, satellite image data (Landsat 8), location map of Akure South metropolis, SRTM DEM, rainfall data, soil data, and GPS coordinates; acquired during the field survey were integrated to map areas vulnerable to flooding. Using Pairwise Comparison, the various weights of factors constituting flood in the area were acquired. A weighted linear combination and analytical hierarchical process were used to produce the flood hazard and flood vulnerability map. ArcGIS Pro 2.7.3 software was used in spatial and attribute data acquisition, processing, and information presentation. The flood vulnerability results indicated that the very high vulnerability zone occupied 13.9% of the study area, while high vulnerability zone occupied 25.5%. Moderate vulnerability zone occupied 36.8% while low vulnerability zone occupied 23.8% of the study area. The study shows that, remote sensing and GIS can be effectively implemented to analyse and provide results on flood vulnerability required for prompt and effective decision-making on floods.","PeriodicalId":176110,"journal":{"name":"International Journal of Environment and Geoinformatics","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133875952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluation of the Accuracy of Open-Source DEMs using GPS Data 基于GPS数据的开源dem精度评价

International Journal of Environment and Geoinformatics Pub Date : 2023-03-05 DOI: 10.30897/ijegeo.1119695

Akif EL MHAMDI, M. Aarab, Abdelkhalek EL FARİATİ

{"title":"Evaluation of the Accuracy of Open-Source DEMs using GPS Data","authors":"Akif EL MHAMDI, M. Aarab, Abdelkhalek EL FARİATİ","doi":"10.30897/ijegeo.1119695","DOIUrl":"https://doi.org/10.30897/ijegeo.1119695","url":null,"abstract":"The DEM is often required for flooding or drainage modeling, land use studies, and geological or other applications. A variety of DEMs, such as the Advanced Space Thermal Emission Radiometer (ASTER GDEM) and the Radar Topography Mission (SRTM) are currently available to the public free of charge. However, these DEMs remain a representation of reality, which requires, before any application, their evaluation using high-precision reference data. The objective of this study is to assess the quality of the two DEMs, ASTER GDEM and SRTM, in Morocco. The methodology adopted for this validation is based on two approaches: internal validation and external validation. The first validation consists of a comparison of the versions of each product with each other. This processing showed that version 2 and version 3 (1 arcsecond) are the best versions of ASTER and SRTM respectively. For the second validation, the vertical precision of DEMs is evaluated by 3551 GPS control points. The overall vertical accuracy attests to a ″ RMSE ″ mean square error of 8.17 and 10.15 respectively for ASTER and SRTM, compared to the GPS elevation points. These ″ RMSE ″ values are the lowest compared to the other versions of these two products, which confirms the quality of version 2 of ASTER GDEM and that of version 3 (1 arcsecond) of SRTM. An in-depth analysis of SRTM version 3 data (1 arcsecond) and ASTER GDEM v2, shows the presence of outliers associated with the slope, which shows the degradation of the performance of these DEMs with the increase of the slope.","PeriodicalId":176110,"journal":{"name":"International Journal of Environment and Geoinformatics","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123006401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An Assessment of YOLO Architectures for Oil Tank Detection from SPOT Imagery 基于SPOT图像的油罐检测YOLO体系评估

International Journal of Environment and Geoinformatics Pub Date : 2023-03-05 DOI: 10.30897/ijegeo.1196817

Tolga Bakirman

{"title":"An Assessment of YOLO Architectures for Oil Tank Detection from SPOT Imagery","authors":"Tolga Bakirman","doi":"10.30897/ijegeo.1196817","DOIUrl":"https://doi.org/10.30897/ijegeo.1196817","url":null,"abstract":"Since it can be used to manage and estimate oil reserves, the inventory of oil tanks is essential for both the economy and the military applications. Considering oil tanks contain valuable materials required for transportation and industrial production, they are a significant type of target. Oil tank detection techniques have several uses, including monitoring disasters, preventing oil leaks, designing cities, and assessing damage. Huge amount of satellite imagery has recently been available and it is used in both the military and civil applications. The new spaceborne sensors' higher resolution enables the detection of targeted objects. Therefore, remote sensing instruments provide ideal tools for oil tank detection task. Conventional approaches for oil tank detection from high resolution remote sensing imagery generally relies on geometric shape, structure, contract differences and color information of the boundary or hand-crafted features. However, these methods come along with vulnerabilities and hence it can be challenging to obtain accurate detection in the presence of a number of disturbance elements, particularly a wide range of colours, size variations, and the shadows that view angle and illumination create. Therefore, deep learning-based methods can provide a big advantage for solution of this task. In this regard, this study employs four YOLO models namely YOLOv5, YOLOX, YOLOv6 and YOLOv7 for oil tank detection from high-resolution optical imagery. Our results show that YOLOv7 and YOLOv5 architectures provide more accurate detections with mean average precision values of 68.11% and 69.69%, respectively. The experiments and visual inspections reveal efficiency, generalization and transferability of these models.","PeriodicalId":176110,"journal":{"name":"International Journal of Environment and Geoinformatics","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132931816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

The Effects of Urbanization and Vegetation Cover on Urban Heat Island: A Case Study in Osmaniye Province 城市化和植被覆盖对城市热岛的影响——以奥斯曼省为例

International Journal of Environment and Geoinformatics Pub Date : 2023-03-05 DOI: 10.30897/ijegeo.1144167

Deniz Çolakkadioğlu

{"title":"The Effects of Urbanization and Vegetation Cover on Urban Heat Island: A Case Study in Osmaniye Province","authors":"Deniz Çolakkadioğlu","doi":"10.30897/ijegeo.1144167","DOIUrl":"https://doi.org/10.30897/ijegeo.1144167","url":null,"abstract":"This study analyzed the changes in the urban heat island effect in the 30 years (from 1990 to 2021) in the central district of Osmaniye. In this sense, there were two primary goals. Firstly, Land use/land cover change (LULC), land surface temperature (LST), normalized difference built-up index (NDBI), and normalized difference vegetation index (NDVI) were analyzed by using remote sensing methods between 1990 and 2021. Secondly, a linear regression analysis was conducted to determine the factors associated with LST, NDVI, and NDBI. The study results revealed increases in urban surfaces and the average land surface temperature values in the past 30 years and showed a decline in the vegetation with low, medium, and high NDVI values. The regression analysis results indicated a strong negative relationship between LST and NDVI and a strong positive relationship between LST and NDBI. It was also found a robust negative relationship between NDBI and NDVI. In light of the findings, it was stated that the amount of open and green areas should be increased in order to prevent the negative effects of the urban heat island in the central district of Osmaniye. For this purpose, it has been proposed to encourage green roof systems throughout the city, to create city parks and to create a green belt system. In addition, as a result of the study, the importance of preventing forest destruction caused by over-settlement in the Amanos Mountains, which is one of the rare habitats of the world with different plant species, was emphasized. In this sense, legal sanctions should be employed to protect those areas and prevent construction.","PeriodicalId":176110,"journal":{"name":"International Journal of Environment and Geoinformatics","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127474948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Waste as A Medium for Agriculture- An Example of Sustainable Waste Management: A Case Study of Titagarh Municipal Dump Site, West Bengal 废物作为农业的媒介——可持续废物管理的一个例子:以西孟加拉邦蒂塔格尔市政垃圾场为例

International Journal of Environment and Geoinformatics Pub Date : 2023-03-05 DOI: 10.30897/ijegeo.1158999

Mallicka Banerjee, Swapan Paul

引用次数: 0

Water-body Segmentation in Heterogeneous Hydrodynamic and Morphodynamic Structured Coastal Areas by Machine Learning 基于机器学习的非均质水动力和形态动力结构海岸带水体分割

International Journal of Environment and Geoinformatics Pub Date : 2023-03-05 DOI: 10.30897/ijegeo.1119096

İrem Gümüşçü, Furkan Altas, Beril Türkekul, Hasan Alper Kaya, F. Erdem, Tolga Bakirman, B. Bayram

{"title":"Water-body Segmentation in Heterogeneous Hydrodynamic and Morphodynamic Structured Coastal Areas by Machine Learning","authors":"İrem Gümüşçü, Furkan Altas, Beril Türkekul, Hasan Alper Kaya, F. Erdem, Tolga Bakirman, B. Bayram","doi":"10.30897/ijegeo.1119096","DOIUrl":"https://doi.org/10.30897/ijegeo.1119096","url":null,"abstract":"Coastal areas constitute the most important part of the world when considered in terms of their socio-economic and natural values. Measuring and monitoring the coastal areas accurately is an important issue for coastal management. Compared to ground-based studies, remote sensing applications enriched with machine learning algorithms such as Random Forest (RF) and Support Vector Machine (SVM) provide significant benefits in terms of cost, time, and size of the study area. Within the scope of this study, Sentinel-2 images for five coastal areas located in Turkey with different morphological and hydrodynamic properties were classified as land and water-bodies using SVM and RF algorithms. Water-body segmentation results of the SVM and RF classification for the different band combinations of Sentinel-2 images have been compared. The reasons affecting the results of the accuracy analysis were examined in accordance with the geography of each area. Experimental results show that the utilized machine learning methods provide satisfactory results for combinations involving the NIR band in all study areas.","PeriodicalId":176110,"journal":{"name":"International Journal of Environment and Geoinformatics","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115366366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0