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Spatial Random Forest (S-RF): A random forest approach for spatially interpolating missing land-cover data with multiple classes
Research article (International Journal of Remote Sensing, 2021) · cited 10× · AI/ML
Spatial Random Forest (S-RF): A random forest approach for spatially interpolating missing land-cover data with multiple classes
Summary
Spatial Random Forest (S-RF): A random forest approach for spatially interpolating missing land-cover data with multiple classes is a scholarly article[1].
Key Facts
Spatial Random Forest (S-RF): A random forest approach for spatially interpolating missing land-cover data with multiple classes's 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). Spatial Random Forest (S-RF): A random forest approach for spatially interpolating missing land-cover data with multiple classes. Retrieved May 24, 2026, from https://4ort.xyz/entity/spatial-random-forest-s-rf-a-random-forest-approach-for-spatially-interpolating-missing-land-cover-data-with-multiple-cl
MLA“Spatial Random Forest (S-RF): A random forest approach for spatially interpolating missing land-cover data with multiple classes.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/spatial-random-forest-s-rf-a-random-forest-approach-for-spatially-interpolating-missing-land-cover-data-with-multiple-cl.
BibTeX@misc{4ortxyz_spatial-random-forest-s-rf-a-random-forest-approach-for-spatially-interpolating-missing-land-cover-data-with-multiple-cl_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Spatial Random Forest (S-RF): A random forest approach for spatially interpolating missing land-cover data with multiple classes}}, year = {2026}, url = {https://4ort.xyz/entity/spatial-random-forest-s-rf-a-random-forest-approach-for-spatially-interpolating-missing-land-cover-data-with-multiple-cl}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Spatial Random Forest (S-RF): A random forest approach for spatially interpolating missing land-cover data with multiple classes — https://4ort.xyz/entity/spatial-random-forest-s-rf-a-random-forest-approach-for-spatially-interpolating-missing-land-cover-data-with-multiple-cl (retrieved 2026-05-24)
