Assessing Climate Change Vulnerability in Coastal Ecosystems Using Remote Sensing

Coastal ecosystems are among the most economically active and ecologically important in the world, biodiversity, climate control, shoreline protection, and millions of livelihoods of people on the planet. Nevertheless, the complex effects of climate change, such as rise in sea level, frequency and intensity of extreme weather events and ocean warming, salinity intrusion, coastal erosion as well as habitat degradation are increasingly threatening these ecosystems. The vulnerability of the coastal ecosystems is thus becoming a key scientific and policy issue. Conventional methods of vulnerability measurement, relying on the efforts of field survey and local observation, are usually constrained in their spatial domain, temporal coverage, availability, and monetary aspect. In this regard, remote sensing technology offers a viable, scaled, and scientifically sound substitute to the tracking and assessment of effects of climate change on coastal infrastructure. This paper discusses how multi-source remote sensing data can be used to determine the vulnerability to climate change in coastal ecosystems using a combined spatial and temporal analysis system. Optical, radar and elevation based satellite data is used to follow indicators of critical vulnerability such as shoreline processes, vegetation condition, land cover changes and inundation. This research establishes both progressive environmental changes and instances of sudden disturbance by the use of the long-term satellite archives to enable a holistic view of the ecosystem exposure and sensitivity. The methods of measuring ecosystem responses to climatic stressors include advanced image processing techniques, spectral indices, change detection techniques, and geographic information system (GIS)-based modeling. The paper also establishes a complex vulnerability model that is founded on the generally agreeable dimensions of exposure and sensitivity, and adaptive capacity. These elements are spatially modeled to find regions of high risk in coastal setting which can be applied in conservation planning, disaster risk reduction and climate adaptation measures. The results show that remote sensing does not only increase the accuracy and efficiency of vulnerability assessment, but also contributes to sound-based policymaking by providing timely and objective data on large and often inaccessible coastal areas. Conclusively, the study highlights how remote sensing is of crucial importance in enhancing climate resilience and sustainable governance of coastal ecosystems in a world that is rapidly changing in terms of environmental change.

• Publication year

  2026

• Venue

  Journal for Research in Applied Sciences and Biotechnology

• Publication date

  2026-02-09

• Fields of study

  Not labeled

• Identifiers
  DOI 10.55544/jrasb.5.1.7
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Building adaptive capacity to climate change in tropical coastal communities

  2018cited by this paper
• Continuous change detection and classification of land cover using all available Landsat data

  2014cited by this paper
• Sea-level rise and coastal change: the past as a guide to the future

  2012cited by this paper
• Status and distribution of mangrove forests of the world using earth observation satellite data

  2011cited by this paper
• Mangroves among the most carbon-rich forests in the tropics

  2011cited by this paper
• The value of estuarine and coastal ecosystem services

  2011cited by this paper
• Remote Sensing of Mangrove Ecosystems: A Review

  2011cited by this paper
• Multi-sensor data fusion for estimating forest species composition and abundance in northern Minnesota

  2011cited by this paper
• Sea-Level Rise and Its Impact on Coastal Zones

  2010cited by this paper
• Sinking deltas due to human activities

  2009cited by this paper
• Mangrove forests: Resilience, protection from tsunamis, and responses to global climate change

  2008cited by this paper
• A Semi-Empirical Approach to Projecting Future Sea-Level Rise

  2007cited by this paper
• Review ArticleDigital change detection methods in ecosystem monitoring: a review

  2004cited by this paper
• A framework for vulnerability analysis in sustainability science

  2003cited by this paper

• No citing papers are available for this paper.