Mangrove vulnerability modelling in parts of Western Niger Delta, Nigeria using satellite images, GIS techniques and Spatial Multi-Criteria Analysis (SMCA)

Environ Monit Assess. 2011 Jul;178(1-4):39-51. doi: 10.1007/s10661-010-1669-z. Epub 2010 Sep 21.

Abstract

Mangroves are known for their global environmental and socioeconomic value. Despite their importance, mangrove like other ecosystems is now being threatened by natural and human-induced processes that damage them at alarming rates, thereby diminishing the limited number of existing mangrove vegetation. The development of a spatial vulnerability assessment model that takes into consideration environmental and socioeconomic criteria, in spatial and non-spatial formats has been attempted in this study. According to the model, 11 different input parameters are required in modelling mangrove vulnerability. These parameters and their effects on mangrove vulnerability were selected and weighted by experts in the related fields. Criteria identification and selection were mainly based on effects of environmental and socioeconomic changes associated with mangrove survival. The results obtained revealed the dominance of socioeconomic criteria such as population pressure and deforestation, with high vulnerability index of 0.75. The environmental criteria was broadly dispersed in the study area and represents vulnerability indices ranging from 0.00-0.75. This category reflects the greater influence of pollutant input from oil wells and pipelines and minimal contribution from climatic factors. This project has integrated spatial management framework for mangrove vulnerability assessment that utilises information technology in conjunction with expert knowledge and multi-criteria analysis to aid planners and policy/ decision makers in the protection of this very fragile ecosystem.

MeSH terms

  • Avicennia*
  • Ecosystem
  • Environmental Monitoring / instrumentation
  • Environmental Monitoring / methods*
  • Environmental Pollutants / analysis
  • Environmental Pollution / statistics & numerical data
  • Geographic Information Systems
  • Introduced Species
  • Nigeria
  • Population Growth
  • Remote Sensing Technology
  • Rhizophoraceae*
  • Risk Assessment
  • Rivers / chemistry
  • Seawater / chemistry
  • Socioeconomic Factors
  • Spacecraft*

Substances

  • Environmental Pollutants