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Deep Learning in Forest Tree Species Classification Using Sentinel-2 on Google Earth Engine: A Case Study of Qingyuan County
Research article (Sustainability, 2023) · cited 27× · AI/ML
Deep Learning in Forest Tree Species Classification Using Sentinel-2 on Google Earth Engine: A Case Study of Qingyuan County
Summary
Deep Learning in Forest Tree Species Classification Using Sentinel-2 on Google Earth Engine: A Case Study of Qingyuan County is a scholarly article[1].
Key Facts
Deep Learning in Forest Tree Species Classification Using Sentinel-2 on Google Earth Engine: A Case Study of Qingyuan County'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). Deep Learning in Forest Tree Species Classification Using Sentinel-2 on Google Earth Engine: A Case Study of Qingyuan County. Retrieved May 24, 2026, from https://4ort.xyz/entity/deep-learning-in-forest-tree-species-classification-using-sentinel-2-on-google-earth-engine-a-case-study-of-qingyuan-cou
MLA“Deep Learning in Forest Tree Species Classification Using Sentinel-2 on Google Earth Engine: A Case Study of Qingyuan County.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deep-learning-in-forest-tree-species-classification-using-sentinel-2-on-google-earth-engine-a-case-study-of-qingyuan-cou.
BibTeX@misc{4ortxyz_deep-learning-in-forest-tree-species-classification-using-sentinel-2-on-google-earth-engine-a-case-study-of-qingyuan-cou_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deep Learning in Forest Tree Species Classification Using Sentinel-2 on Google Earth Engine: A Case Study of Qingyuan County}}, year = {2026}, url = {https://4ort.xyz/entity/deep-learning-in-forest-tree-species-classification-using-sentinel-2-on-google-earth-engine-a-case-study-of-qingyuan-cou}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Deep Learning in Forest Tree Species Classification Using Sentinel-2 on Google Earth Engine: A Case Study of Qingyuan County — https://4ort.xyz/entity/deep-learning-in-forest-tree-species-classification-using-sentinel-2-on-google-earth-engine-a-case-study-of-qingyuan-cou (retrieved 2026-05-24)
