Wetland change prediction of Ogun-River Basin, Nigeria: Application of cellular automata Markov and remote sensing techniques

Tobore, Anthony; Bamidele, Samuel

doi:10.1016/j.wsee.2022.11.001

Cited by 7 publications

(3 citation statements)

References 72 publications

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“…The results of the classified images are also confirmed by the existing studies on changes in mangrove habitats in southern Nigeria reporting the environmental degradation [113,114]. For instance, [115] confirms the losses in mangroves in southern Nigeria since mid-1980s through the early 2000s due to the urbanization, dredging, and oil and gas industrial activities.…”

Section: Discussionsupporting

confidence: 77%

Computing Vegetation Indices from the Satellite Images Using GRASS GIS Scripts for Monitoring Mangrove Forests in the Coastal Landscapes of Niger Delta, Nigeria

Lemenkova

Debeir

2023

JMSE

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This paper addresses the issue of the satellite image processing using GRASS GIS in the mangrove forests of the Niger River Delta, southern Nigeria. The estuary of the Niger River Delta in the Gulf of Guinea is an essential hotspot of biodiversity on the western coast of Africa. At the same time, climate issues and anthropogenic factors affect vulnerable coastal ecosystems and result in the rapid decline of mangrove habitats. This motivates monitoring of the vegetation patterns using advanced cartographic methods and data analysis. As a response to this need, this study aimed to calculate and map several vegetation indices (VI) using scripts as advanced programming methods integrated in geospatial studies. The data include four Landsat 8-9 OLI/TIRS images covering the western segment of the Niger River Delta in the Bight of Benin for 2013, 2015, 2021, and 2022. The techniques included the ’i.vi’, ’i.landsat.toar’ and other modules of the GRASS GIS. Based on the GRASS GIS ’i.vi’ module, ten VI were computed and mapped for the western segment of the Niger River Delta estuary: Atmospherically Resistant Vegetation Index (ARVI), Green Atmospherically Resistant Vegetation Index (GARI), Green Vegetation Index (GVI), Difference Vegetation Index (DVI), Perpendicular Vegetation Index (PVI), Global Environmental Monitoring Index (GEMI), Normalized Difference Water Index (NDWI), Second Modified Soil Adjusted Vegetation Index (MSAVI2), Infrared Percentage Vegetation Index (IPVI), and Enhanced Vegetation Index (EVI). The results showed variations in the vegetation patterns in mangrove habitats situated in the Niger River Delta over the last decade as well as the increase in urban areas (Onitsha, Sapele, Warri and Benin City) and settlements in the Delta State due to urbanization. The advanced techniques of the GRASS GIS of satellite image processing and analysis enabled us to identify and visualize changes in vegetation patterns. The technical excellence of the GRASS GIS in image processing and analysis was demonstrated in the scripts used in this study.

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Section: Discussionsupporting

confidence: 77%

Computing Vegetation Indices from the Satellite Images Using GRASS GIS Scripts for Monitoring Mangrove Forests in the Coastal Landscapes of Niger Delta, Nigeria

Lemenkova

Debeir

2023

JMSE

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“…Currently, efforts to abate heavy metals contamination in wetland soils requires urgent attention in developing countries, such as Nigeria, where "wetlands in close vicinities to 2 Air, Soil and Water Research waste effluents or industrial areas are sometimes referred to as wastelands" (A. Tobore & Bamidele, 2022). Extant research, in agriculture, and the environment indicates that a technique harmonizing soil standard specification, Igeo, and PI, combined with RS environmental covariates such as, EVI, NDVI, and MNDWI, are regarded as essential and accurate techniques utilized to assess heavy metal contamination in the environment, especially, in developed countries (Song et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…Consequently, with the increasing economic growth, “Ibese” Ogun state, Nigeria, has been witnessing a dramatic expansion in industrialization and urbanization and also described as Agrarian region vulnerable to climate change (Akindele et al, 2020). Currently, efforts to abate heavy metals contamination in wetland soils requires urgent attention in developing countries, such as Nigeria, where “wetlands in close vicinities to waste effluents or industrial areas are sometimes referred to as wastelands” (A. Tobore & Bamidele, 2022).…”

Section: Introductionmentioning

confidence: 99%

Assessment of Heavy Metal Contamination in Wetlands Soils Around an Industrial Area Using Combined GIS-Based Pollution Indices and Remote Sensing Techniques

Anthony

2023

Air, Soil and Water Research

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Understanding variations of heavy metals and their anthropogenic influence on wetland soils are very imperative and crucial for environmental planning and sustainability. To assess heavy metal contamination in Ibese wetland soils, Nigeria, 30 soil surface (0–20 cm) samples clustered around industrial effluents, were collected and analyzed with atomic absorption spectrophotometer for copper (Cu), zinc (Zn) and cadmium (Cd). Herein, the geo-accumulation (Igeo), and pollution index (PI), coupled with environmental (RS) remote sensing vegetation and water indices were employed as predictor models to assess heavy metals contamination of the area. The vegetation and water indices highlighted an intense decreasing vegetation trend and loss of waterbodies of the area, respectively. The results of the Igeo metals revealed that the wetland soils pollution ranged from uncontaminated to moderately contaminated, except Cd which ranged from moderately to heavy pollution. The PI shows a moderate significant pollution by Cu and Zn, except Cd which recorded considerable contamination. A very significant correlation was found between the metals and the spatial distribution pattern revealed that the contamination is related to the influence of uncontrolled human activities on soil properties like soil pH and organic carbon. The study suggested that adequate attention be directed to alert policymakers and stakeholders toward lessening the anthropogenic sources in the area for future control measures.

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Spatial analysis of land cover changes for detecting environmental degradation and promoting sustainability

Anthony,

Shohan,

Oludare

et al. 2024

Kuwait Journal of Science

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Wetland change prediction of Ogun-River Basin, Nigeria: Application of cellular automata Markov and remote sensing techniques

Cited by 7 publications

References 72 publications

Computing Vegetation Indices from the Satellite Images Using GRASS GIS Scripts for Monitoring Mangrove Forests in the Coastal Landscapes of Niger Delta, Nigeria

Computing Vegetation Indices from the Satellite Images Using GRASS GIS Scripts for Monitoring Mangrove Forests in the Coastal Landscapes of Niger Delta, Nigeria

Assessment of Heavy Metal Contamination in Wetlands Soils Around an Industrial Area Using Combined GIS-Based Pollution Indices and Remote Sensing Techniques

Spatial analysis of land cover changes for detecting environmental degradation and promoting sustainability

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