Home ›
Entities
› academia
› Integrating multiple texture methods and NDVI to the Random Forest classification algorithm to detect tea and hazelnut plantation areas in northeast Turkey
Integrating multiple texture methods and NDVI to the Random Forest classification algorithm to detect tea and hazelnut plantation areas in northeast Turkey
Research article (International Journal of Remote Sensing, 2015) · cited 123× · AI/ML
Integrating multiple texture methods and NDVI to the Random Forest classification algorithm to detect tea and hazelnut plantation areas in northeast Turkey
Summary
Integrating multiple texture methods and NDVI to the Random Forest classification algorithm to detect tea and hazelnut plantation areas in northeast Turkey is a scholarly article[1].
Key Facts
Integrating multiple texture methods and NDVI to the Random Forest classification algorithm to detect tea and hazelnut plantation areas in northeast Turkey'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). Integrating multiple texture methods and NDVI to the Random Forest classification algorithm to detect tea and hazelnut plantation areas in northeast Turkey. Retrieved May 24, 2026, from https://4ort.xyz/entity/integrating-multiple-texture-methods-and-ndvi-to-the-random-forest-classification-algorithm-to-detect-tea-and-hazelnut-p
MLA“Integrating multiple texture methods and NDVI to the Random Forest classification algorithm to detect tea and hazelnut plantation areas in northeast Turkey.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/integrating-multiple-texture-methods-and-ndvi-to-the-random-forest-classification-algorithm-to-detect-tea-and-hazelnut-p.
BibTeX@misc{4ortxyz_integrating-multiple-texture-methods-and-ndvi-to-the-random-forest-classification-algorithm-to-detect-tea-and-hazelnut-p_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Integrating multiple texture methods and NDVI to the Random Forest classification algorithm to detect tea and hazelnut plantation areas in northeast Turkey}}, year = {2026}, url = {https://4ort.xyz/entity/integrating-multiple-texture-methods-and-ndvi-to-the-random-forest-classification-algorithm-to-detect-tea-and-hazelnut-p}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Integrating multiple texture methods and NDVI to the Random Forest classification algorithm to detect tea and hazelnut plantation areas in northeast Turkey — https://4ort.xyz/entity/integrating-multiple-texture-methods-and-ndvi-to-the-random-forest-classification-algorithm-to-detect-tea-and-hazelnut-p (retrieved 2026-05-24)
