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Let your maps be fuzzy!—Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation
Research article (Remote Sensing in Ecology and Conservation, 2020) · cited 48× · AI/ML
Let your maps be fuzzy!—Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation
Summary
Let your maps be fuzzy!—Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation is a scholarly article[1].
Key Facts
Let your maps be fuzzy!—Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation's Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation — instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Let your maps be fuzzy!—Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation. Retrieved May 24, 2026, from https://4ort.xyz/entity/let-your-maps-be-fuzzy-class-probabilities-and-floristic-gradients-as-alternatives-to-crisp-mapping-for-remote-sensing-o
MLA“Let your maps be fuzzy!—Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/let-your-maps-be-fuzzy-class-probabilities-and-floristic-gradients-as-alternatives-to-crisp-mapping-for-remote-sensing-o.
BibTeX@misc{4ortxyz_let-your-maps-be-fuzzy-class-probabilities-and-floristic-gradients-as-alternatives-to-crisp-mapping-for-remote-sensing-o_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Let your maps be fuzzy!—Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation}}, year = {2026}, url = {https://4ort.xyz/entity/let-your-maps-be-fuzzy-class-probabilities-and-floristic-gradients-as-alternatives-to-crisp-mapping-for-remote-sensing-o}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Let your maps be fuzzy!—Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation — https://4ort.xyz/entity/let-your-maps-be-fuzzy-class-probabilities-and-floristic-gradients-as-alternatives-to-crisp-mapping-for-remote-sensing-o (retrieved 2026-05-24)
