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A machine learning model for estimating the temperature of small rivers using satellite-based spatial data
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2024
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Source: Remote Sensing of Environment, 311, 114271
[PDF-4.96 MB]
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Journal Title:Remote Sensing of Environment
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Description:The influence of anthropogenic activity and land cover alteration on stream temperatures has major ecological implications, such as limiting fish survival. While these ecological impacts have been extensively studied at varying spatial scales for major rivers, our understanding of the range and complexity of this relationship across climates and geographies for smaller rivers (less than ~60 m wide) remains limited. This is in part because although such rivers comprise a vast majority (~97%) of total stream length, most smaller rivers lack routine temperature observations despite extensive gage networks. While existing gage networks in many regions are sufficient to support satellite remote sensing-based modeling of small stream temperatures, most large regions including the contiguous United States do not have modeled data products at high spatial and temporal resolution for small rivers.
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Source:Remote Sensing of Environment, 311, 114271
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DOI:
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ISSN:0034-4257
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Rights Information:CC BY
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Compliance:Submitted
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