Crown-level tree species classification from AISA hyperspectral imagery using an innovative pixel-weighting approach

Research article (International Journal of Applied Earth Observation and Geoinformation, 2017) · cited 16× · AI/ML
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Crown-level tree species classification from AISA hyperspectral imagery using an innovative pixel-weighting approach

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Crown-level tree species classification from AISA hyperspectral imagery using an innovative pixel-weighting approach is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Crown-level tree species classification from AISA hyperspectral imagery using an innovative pixel-weighting approach. Retrieved May 24, 2026, from https://4ort.xyz/entity/crown-level-tree-species-classification-from-aisa-hyperspectral-imagery-using-an-innovative-pixel-weighting-approach
MLA “Crown-level tree species classification from AISA hyperspectral imagery using an innovative pixel-weighting approach.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/crown-level-tree-species-classification-from-aisa-hyperspectral-imagery-using-an-innovative-pixel-weighting-approach.
BibTeX @misc{4ortxyz_crown-level-tree-species-classification-from-aisa-hyperspectral-imagery-using-an-innovative-pixel-weighting-approach_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Crown-level tree species classification from AISA hyperspectral imagery using an innovative pixel-weighting approach}}, year = {2026}, url = {https://4ort.xyz/entity/crown-level-tree-species-classification-from-aisa-hyperspectral-imagery-using-an-innovative-pixel-weighting-approach}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Crown-level tree species classification from AISA hyperspectral imagery using an innovative pixel-weighting approach — https://4ort.xyz/entity/crown-level-tree-species-classification-from-aisa-hyperspectral-imagery-using-an-innovative-pixel-weighting-approach (retrieved 2026-05-24)

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