首页|Max-Planck-Institute Researchers Publish Findings in Machine Learning (Assessing climate risks from satellite imagery with machine learning: A case study of flo od risks in Jakarta)
Max-Planck-Institute Researchers Publish Findings in Machine Learning (Assessing climate risks from satellite imagery with machine learning: A case study of flo od risks in Jakarta)
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Investigators discuss new findings in artificial intelligence. According to news originating from Bochum, Germany, by NewsRx correspondents, research stated, "Consistent and timely assessment of cli mate risks is crucial for planning disaster mitigation and adaptation to climate change at the local community level." Funders for this research include Institute For Basic Science. The news correspondents obtained a quote from the research from Max-Planck-Insti tute: "This article presents an automatized method for monitoring climate risks with machine learning on satellite imagery, specially targeting riverine and coa stal floods. Our research demonstrates that disaster-related risk measurement be comes more comprehensive and multi-faceted by including the following components : hazards, exposure, and vulnerability. Our model first maps hazard-related risk s with geo-spatial data, then extends the model to incorporate exposure and vuln erability. In doing so, we adopt a clustering-based supervised algorithm to sort satellite images to produce the climate risk scores at a grid-level. The develo ped model was tested over multiple ground-truth datasets on flood risks in the r egion of Jakarta, Indonesia. Results confirm that our model can assess climate r isks in a granular scale and further capture potential risks in the marginalized areas (e.g., slums) that were previously hard to predict."
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