Closing the Observation–Inference Gap in Southeast Asian Coastal Ecosystem Monitoring
Keywords:
remote sensing, ecological inference, coastal ecosystems, evidence integration, Southeast Asia.Abstract
This study develops a quantitative evidence architecture for interpreting remote-sensing and ecological data in Southeast Asian coastal ecosystems. A fixed corpus of 30 DOI-indexed studies published between 2007 and 2024 was coded by ecosystem, evidence mode, spatial scale, and primary ecological target, then analyzed using descriptive statistics, contingency analysis, and a 20,000-permutation test. The corpus was dominated by mangrove (40.0%) and coral (33.3%) research, while seagrass represented only 10.0%; 70.0% of studies were published from 2018 onward. Evidence mode differed substantially among ecosystems (chi-square = 24.62; permutation p = 0.016; Cramer's V = 0.523), with coral studies dominated by multi-source quantitative designs and seagrass studies concentrated in synthesis and mapping. Numeric benchmarks showed that high map accuracy or broad spatial coverage did not remove uncertainty in below-ground carbon, functional recovery, or biological response to thermal stress. The study introduces an Observation–Inference Gap framework in which stronger ecological and management claims require proportionally stronger field calibration, temporal continuity, cross-sensor validation, and uncertainty propagation. The framework provides a practical basis for interoperable coastal monitoring without treating all spatial products as equivalent ecological evidence.
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Copyright (c) 2026 Emha Dzia’ul Haq, Yassine HADDIOUI (Author)
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