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A comprehensive evaluation of disturbance agent classification approaches: Strengths of ensemble classification, multiple indices, spatio-temporal variables, and direct prediction
Research article (ISPRS Journal of Photogrammetry and Remote Sensing, 2019) · cited 50× · AI/ML
A comprehensive evaluation of disturbance agent classification approaches: Strengths of ensemble classification, multiple indices, spatio-temporal variables, and direct prediction
Summary
A comprehensive evaluation of disturbance agent classification approaches: Strengths of ensemble classification, multiple indices, spatio-temporal variables, and direct prediction is a scholarly article[1].
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A comprehensive evaluation of disturbance agent classification approaches: Strengths of ensemble classification, multiple indices, spatio-temporal variables, and direct prediction's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). A comprehensive evaluation of disturbance agent classification approaches: Strengths of ensemble classification, multiple indices, spatio-temporal variables, and direct prediction. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-comprehensive-evaluation-of-disturbance-agent-classification-approaches-strengths-of-ensemble-classification-multiple-
MLA“A comprehensive evaluation of disturbance agent classification approaches: Strengths of ensemble classification, multiple indices, spatio-temporal variables, and direct prediction.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-comprehensive-evaluation-of-disturbance-agent-classification-approaches-strengths-of-ensemble-classification-multiple-.
BibTeX@misc{4ortxyz_a-comprehensive-evaluation-of-disturbance-agent-classification-approaches-strengths-of-ensemble-classification-multiple-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A comprehensive evaluation of disturbance agent classification approaches: Strengths of ensemble classification, multiple indices, spatio-temporal variables, and direct prediction}}, year = {2026}, url = {https://4ort.xyz/entity/a-comprehensive-evaluation-of-disturbance-agent-classification-approaches-strengths-of-ensemble-classification-multiple-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A comprehensive evaluation of disturbance agent classification approaches: Strengths of ensemble classification, multiple indices, spatio-temporal variables, and direct prediction — https://4ort.xyz/entity/a-comprehensive-evaluation-of-disturbance-agent-classification-approaches-strengths-of-ensemble-classification-multiple- (retrieved 2026-05-24)
