Positional accuracy assessment of historical Google Earth imagery in Lagos State, Nigeria

Nwilo, Peter C.; Okolie, Chukwuma J.; Onyegbula, Johanson C.; Arungwa, Ikenna D.; Ayoade, Owolabi Q.; Daramola, Olagoke E.; Orji, Michael J.; Maduako, Ikechukwu D.; Uyo, Imeime I.

doi:10.1007/s12518-022-00449-9

Cited by 11 publications

(8 citation statements)

References 50 publications

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“…The analysis was conducted to ensure that spatial information regarding coastline changes that cause accretion and erosion in Subang Regency can be disseminated to the general public. The OA (overall accuracy), kappa coefficient, producer accuracy (PA), and user accuracy (UA) values, which are often seen as standards, are above 85% to be acceptable and are said to be at a comparable level of accuracy [37,38,39,40]. The analysis results interpret that the data on the dynamics of changes in the Subang Regency coastline has relatively high accuracy values, as shown in Figure 6.…”

Section: Accuracy Classification Of Coastal Areasmentioning

confidence: 81%

“…The highest accuracy values were obtained in 2023 and 2010 for each metric type (OA, kappa, PA, and UA), while the lowest value occurred in 2000. 2000 and 2008 were recorded as the worst years for horizontal accuracy, and Google made many improvements and developments to satellite imagery until 2018 [40]. The highest OA value is 1.00, and the lowest is 0.93.…”

Section: Accuracy Classification Of Coastal Areasmentioning

confidence: 99%

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Monitoring of coastal dynamics at Subang Regency using Landsat Collection Data and Cloud Computing Based

A Madinu,

Jouhary,

Ulfa

et al. 2024

BIO Web Conf.

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This study aims to better understand the coastal dynamics along the 6.89 km of Subang shoreline using Landsat data and GIS methods with cloud computing-based analysis. The data is processed using remote sensing techniques, image classification, and change detection algorithms. Furthermore, this research harnesses cloud computing to efficiently manipulate big data, enabling rapid and measurable analysis of coastline changes. Cloud computing-based platforms facilitate data storage, processing, and dissemination, enhancing accessibility for researchers and stakeholders. This study indicates that the area has experienced significant changes from 1990 to 2023, with the total length of the coastlines that have changed (positive stands for accretion and negative for erosion) being 8.21 km (-16,86 %) for 1990 to 2000, 6.52 km (16.21%) for 2000 to 2010, 8.14 km (6,66%) for 2010 to 2020, and 8.81 km (-19,16%) for 2020 to 2023. The results provide valuable information about erosion, accretion, and coastal morphological changes. The findings can help make informed decisions for sustainable coastal management. The methodology presented in this article demonstrates a solid approach to coastline monitoring that can be replicated in other areas for more efficient and effective coastal management and environmental preservation.

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Section: Accuracy Classification Of Coastal Areasmentioning

confidence: 81%

Section: Accuracy Classification Of Coastal Areasmentioning

confidence: 99%

Monitoring of coastal dynamics at Subang Regency using Landsat Collection Data and Cloud Computing Based

A Madinu,

Jouhary,

Ulfa

et al. 2024

BIO Web Conf.

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“…In the present research, we observed that the food preferences of the adolescent girls in the Gamawa LGA in the Bauchi North senatorial district were limited and influenced by physical access to food, particularly the types of agricultural produce thriving in their communities. The area of Gamawa has been shown to be prone to desertification, with remarkable losses of vegetation and elevation in land surface temperatures; thus, primarily drought-resistant crop varieties thrive in this arid region [ 116 , 117 , 118 ]. To improve access to healthy foods in desert-prone areas, research efforts need to be directed towards identifying and promoting the cultivation and utilization of climate-resilient, nutrient-dense foods (soybean, cowpea, and Bambara nuts), micronutrient-rich vegetables (Moringa leaves), and other crops that can thrive in impoverished soils [ 89 , 118 ].…”

Section: Discussionmentioning

confidence: 99%

Why Acute Undernutrition? A Qualitative Exploration of Food Preferences, Perceptions and Factors Underlying Diet in Adolescent Girls in Rural Communities in Nigeria

Sosanya,

Freeland-Graves,

Gbemileke

et al. 2024

Nutrients

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Background: Adolescent girls are nutritionally vulnerable due to their rapid growth and increased nutrient requirements. Nigeria has the sixth-largest population in the world. This study qualitatively explored the food preferences, perceptions of nutritive value and factors underlying food consumption of adolescent girls in rural communities in Nigeria. Methods: The data were collected via the free listing of foods and focus group sessions conducted in the Hausa language with 48 unmarried adolescent girls. The discussions were audio-recorded, transcribed, translated into English, and analyzed using a deductive thematic framework. Results: The mean age of the respondents was 13.0 ± 2.7, and almost half (48%) had a primary school education. A total of 19 and 23 foods were identified as preferred, and perceived as nourishing, respectively. The top 10 foods present on both free lists overlapped considerably in terms of cognitive salience. The focus group themes included nutrition knowledge, food preferences, autonomy, household food allocation, courtship practices, and agricultural landscapes and economic access. The participants had minimal knowledge of nutrients and food groups, and their preferred foods were limited in diversity. The key factors in food preferences were desirable health effects, sensory attributes, and the contribution of foods to a desirable body image for marriage. Household food choices depended on parents. Thus, a desire for independence was an incentive for early marriage, mostly at 13 to 17 years. Gender inequities in household food distribution (quantity) and animal protein intake were reported. The participants believed that boys need more food for strength to impregnate girls. As part of a courtship practice, the girls received gifts of animal source foods from potential suitors. The food options were limited by financial challenges and low agricultural diversity. Conclusion: To interrupt the cycle of inadequate food consumption and undernutrition in these adolescent girls, policy makers need to promote nutrition education and address the underlying determinants of inequitable access to nutritious foods.

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“…Google Earth's “Historical Imagery” enables users to view images and observe changes over a region at different epochs [4] . Usually, the criteria for selecting a particular year include the degree of cloud cover and image clarity.…”

Section: Data Descriptionmentioning

confidence: 99%

“…Although there is little documentation about the metadata of Google Earth images [5] , they have found wide uses in applications such as land use change detection, modelling of earth surface processes, habitat availability, health and surveillance systems, agriculture, landscape and other applications etc. [3] , [4] , [5] . The 2005 GE Historical Imagery dataset consists of 42 images extracted from Google Earth Pro using Elshayal Smart GIS software (folder dataset “GE Historical Image data\Raw” https://data.mendeley.com/datasets/63n37x7c92 ).…”

Section: Data Descriptionmentioning

confidence: 99%

Dataset of urban development analysis in a section of Kuje Area Council, Abuja, Nigeria

et al. 2023

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Positional accuracy assessment of historical Google Earth imagery in Lagos State, Nigeria

Cited by 11 publications

References 50 publications

Monitoring of coastal dynamics at Subang Regency using Landsat Collection Data and Cloud Computing Based

Monitoring of coastal dynamics at Subang Regency using Landsat Collection Data and Cloud Computing Based

Why Acute Undernutrition? A Qualitative Exploration of Food Preferences, Perceptions and Factors Underlying Diet in Adolescent Girls in Rural Communities in Nigeria

Dataset of urban development analysis in a section of Kuje Area Council, Abuja, Nigeria

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