Home ›
Entities
› academia
› Correction of global digital elevation models in forested areas using an artificial neural network-based method with the consideration of spatial autocorrelation
Correction of global digital elevation models in forested areas using an artificial neural network-based method with the consideration of spatial autocorrelation
Research article (International Journal of Digital Earth, 2023) · cited 25× · AI/ML
Correction of global digital elevation models in forested areas using an artificial neural network-based method with the consideration of spatial autocorrelation
Summary
Correction of global digital elevation models in forested areas using an artificial neural network-based method with the consideration of spatial autocorrelation is a scholarly article[1].
Key Facts
Correction of global digital elevation models in forested areas using an artificial neural network-based method with the consideration of spatial autocorrelation's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
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). Correction of global digital elevation models in forested areas using an artificial neural network-based method with the consideration of spatial autocorrelation. Retrieved May 24, 2026, from https://4ort.xyz/entity/correction-of-global-digital-elevation-models-in-forested-areas-using-an-artificial-neural-network-based-method-with-the
MLA“Correction of global digital elevation models in forested areas using an artificial neural network-based method with the consideration of spatial autocorrelation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/correction-of-global-digital-elevation-models-in-forested-areas-using-an-artificial-neural-network-based-method-with-the.
BibTeX@misc{4ortxyz_correction-of-global-digital-elevation-models-in-forested-areas-using-an-artificial-neural-network-based-method-with-the_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Correction of global digital elevation models in forested areas using an artificial neural network-based method with the consideration of spatial autocorrelation}}, year = {2026}, url = {https://4ort.xyz/entity/correction-of-global-digital-elevation-models-in-forested-areas-using-an-artificial-neural-network-based-method-with-the}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Correction of global digital elevation models in forested areas using an artificial neural network-based method with the consideration of spatial autocorrelation — https://4ort.xyz/entity/correction-of-global-digital-elevation-models-in-forested-areas-using-an-artificial-neural-network-based-method-with-the (retrieved 2026-05-24)
