Geo-computation techniques for identifying spatio-temporal patterns of reported oil spills along crude oil pipeline networks
The Niger Delta region of Nigeria is a major oil-producing area which experiences frequent oil spills that severely impacts the local environment and communities. Effective environmental monitoring and management remain inadequate in this area due to negligence, slow response times following oil spi...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2024.2448218 |
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| Summary: | The Niger Delta region of Nigeria is a major oil-producing area which experiences frequent oil spills that severely impacts the local environment and communities. Effective environmental monitoring and management remain inadequate in this area due to negligence, slow response times following oil spills, and difficulties regarding access and safety. This study investigates the spatiotemporal patterns of oil spills along the pipeline network from 2013 to 2021 using geo-computation techniques. Utilising the spNetwork package in R, Network Kernel Density Estimates (NKDE) and its temporal extension, Temporal Network Kernel Density Estimates (TNKDE) were carried out. Pipeline data were transformed into 500-metre lixels (linear pixels) to compute network distances and generate density estimates. NKDE identified oil spill hotspots, while TNKDE illustrated the temporal transitions of spills. These methods surpass traditional approaches (e.g. KDE, cluster analysis, point pattern analysis) by incorporating network constraints and uncovering critical spatial–temporal patterns. The findings offer valuable insights for targeted interventions to reduce future spills and mitigate past impacts. |
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| ISSN: | 1753-8947 1753-8955 |