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An improved spatio-temporal clustering method for extracting fire footprints based on MCD64A1 in the Daxing’anling Area of north-eastern China
Research article (International Journal of Wildland Fire, 2023) · cited 15× · AI/ML
An improved spatio-temporal clustering method for extracting fire footprints based on MCD64A1 in the Daxing’anling Area of north-eastern China
Summary
An improved spatio-temporal clustering method for extracting fire footprints based on MCD64A1 in the Daxing’anling Area of north-eastern China is a scholarly article[1].
Key Facts
An improved spatio-temporal clustering method for extracting fire footprints based on MCD64A1 in the Daxing’anling Area of north-eastern China'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). An improved spatio-temporal clustering method for extracting fire footprints based on MCD64A1 in the Daxing’anling Area of north-eastern China. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-improved-spatio-temporal-clustering-method-for-extracting-fire-footprints-based-on-mcd64a1-in-the-daxinganling-area-o
MLA“An improved spatio-temporal clustering method for extracting fire footprints based on MCD64A1 in the Daxing’anling Area of north-eastern China.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-improved-spatio-temporal-clustering-method-for-extracting-fire-footprints-based-on-mcd64a1-in-the-daxinganling-area-o.
BibTeX@misc{4ortxyz_an-improved-spatio-temporal-clustering-method-for-extracting-fire-footprints-based-on-mcd64a1-in-the-daxinganling-area-o_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An improved spatio-temporal clustering method for extracting fire footprints based on MCD64A1 in the Daxing’anling Area of north-eastern China}}, year = {2026}, url = {https://4ort.xyz/entity/an-improved-spatio-temporal-clustering-method-for-extracting-fire-footprints-based-on-mcd64a1-in-the-daxinganling-area-o}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): An improved spatio-temporal clustering method for extracting fire footprints based on MCD64A1 in the Daxing’anling Area of north-eastern China — https://4ort.xyz/entity/an-improved-spatio-temporal-clustering-method-for-extracting-fire-footprints-based-on-mcd64a1-in-the-daxinganling-area-o (retrieved 2026-05-24)
