Integration of satellite gravimetry, multispectral imagery and digital elevation model for investigating crustal deformation in the Niger Delta Basin

Epuh, E. E.; Moshood, Ahmed I.; Okolie, Chukwuma J.; Daramola, Olagoke E.; Akinnusi, Samuel A.; Arungwa, Ikenna D.; Orji, Michael J.; Olanrewaju, Hamed O.; Fatoyinbo, Ahmed A

doi:10.1016/j.geogeo.2022.100067

Cited by 5 publications

(2 citation statements)

References 58 publications

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“…This assumption, however, requires effective methods of image processing for analysis of a time series rapidly and accurately. While many existing GIS software involve a variety of manual operations for processing each image (Epuh et al, 2022;Spiekermann et al, 2015;Tappan and McGahuey, 2007), the success in classification of the satellite images requires the development of more advanced approaches. The tasks of satellite image processing require machine-based programming algorithms for accurate classification and mapping.…”

Section: Introductionmentioning

confidence: 99%

Time Series Analysis of Landsat Images for Monitoring Flooded Areas in the Inner Niger Delta, Mali

Lemenkova,

Debeir

2023

Artificial Satellites

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This paper presents an R-based approach to mapping dynamics of the flooded areas in the Inner Niger Delta (IND), Mali, using time series analysis of Landsat 8–9 satellite images. As the largest inland wetland in West Africa, the habitats of IND offers high potential for biodiversity of the flood-dependent eco systems. IND is one of the most productive areas in West Africa. Mapping flooded areas based on satellite images enables to provide strategies for land management and rice planting and modelling vegetation types of IND. Our approach is based on using libraries of R programming language for processing six Landsat images, and each image was taken on November from 2013 to 2022. By capturing spatial and temporal structures of the satellite images on 2013, 2015, 2018, 2020, 2021 and 2022, the remote sensing data are combined to yield estimates of landscape dynamics that is temporally coherent, while helping to analyse fluctuations of spatial extent in fluvial wetlands caused by the hydrological processes of seasonal flooding. Further, by allowing packages of R to support image processing, an approach to mapping vegetation by NDVI, SAVI and EVI indices and visualising changes in distribution of different land cover classes over time is realised. In this context, processing Earth observation data by advanced scripting tools of R language provides new insights into complex interlace of climate-hydrological processes and vegetation responses. Our study contributes to the sustainable management of natural resources and improving knowledge on the functioning of IND ecosystems in Mali, West Africa.

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Section: Introductionmentioning

confidence: 99%

Time Series Analysis of Landsat Images for Monitoring Flooded Areas in the Inner Niger Delta, Mali

Lemenkova,

Debeir

2023

Artificial Satellites

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“…En la actualidad, gracias al desarrollo de los Sistemas de Información Geográfica y la evolución de los sensores satelitales que hicieron posible la creación de Modelos Digitales de Superficie (MDS) precisos y de alta resolución, estas dificultades están siendo superadas y los métodos tradicionales de digitalización de las redes de drenaje han sido reemplazados por metodologías más avanzadas (López-Vicente et al, 2014;Nikolakopoulos et al, 2015;Kok et al, 2018;Shavers & Stanislawski, 2020). La disponibilidad de nuevas tecnologías para la medición de la elevación de la superficie terrestre ha abordado la ausencia de datos de alta resolución, lo que ha llevado a un aumento de la utilización de este tipo de herramientas en la realización de estudios de modelado hidrológico, hidráulico y geomorfológico (Manfreda et al, 2011;Samela et al, 2016;Niyazi et al, 2019;Epuh et al, 2022;Kale et al, 2022;Roy et al, 2022).…”

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Determinación de inicios de cauces a partir de Modelos Digitales de Superficie. Cuenca alta del arroyo La Ventana (Buenos Aires, Argentina)

González¹,

Gil²,

Gentili³

2023

GeoFocus

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When defining the hydrographic network of a basin, it is important to precisely locate the beginnings of the channels, since this position influences different aspects of the dynamics of a basin. Currently, the evolution of Geographic Information Systems (GIS) and the existence of Digital Surface Models (DSM) make it possible to extract drainage networks automatically, however, on many Determinación de inicios de cauces a partir de Modelos Digitales de Superficie. Cuenca alta del arroyo La Ventana (Buenos Aires, Argentina) www.geofocus.org 102 occasions, these results require verification in field or in different sources of information to validate and achieve greater precision. Therefore, the objective of this work is to determine and evaluate the optimum location threshold of the channels heads location of upper basin of La Ventana stream (Buenos Aires, Argentina) through the use of a DSM. To evaluate the suitability of the automatic models obtained, the results were compared with high-resolution satellite images and field control. In turn, morphometric indices were used to determine the variations in the hydrological response of each model. The main results indicate variations both in the length and in the number of sections according to the threshold that affect the results of each index. Is highlighted the importance of choosing an optimal threshold to obtain the drainage network model that is most consistent with reality from which valid and specific data can be extracted.

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Corrigendum to “Integration of satellite gravimetry, multispectral imagery and digital elevation model for investigating crustal deformation in the Niger Delta Basin” [Geosystems and Geoenvironment, Volume 1, Issue 3, August 2022, 100067]

Epuh

Moshood

Okolie

et al. 2022

Geosystems and Geoenvironment

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Integration of satellite gravimetry, multispectral imagery and digital elevation model for investigating crustal deformation in the Niger Delta Basin

Cited by 5 publications

References 58 publications

Time Series Analysis of Landsat Images for Monitoring Flooded Areas in the Inner Niger Delta, Mali

Time Series Analysis of Landsat Images for Monitoring Flooded Areas in the Inner Niger Delta, Mali

Determinación de inicios de cauces a partir de Modelos Digitales de Superficie. Cuenca alta del arroyo La Ventana (Buenos Aires, Argentina)

Corrigendum to “Integration of satellite gravimetry, multispectral imagery and digital elevation model for investigating crustal deformation in the Niger Delta Basin” [Geosystems and Geoenvironment, Volume 1, Issue 3, August 2022, 100067]

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