Mapping land-cover modifications over large areas: A comparison of machine learning algorithms
| Autor: | Curtis E. Woodcock, Janet Franklin, John Rogan, Dar A. Roberts, Jennifer A. Miller, Doug Stow |
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| Rok vydání: | 2008 |
| Předmět: |
Data processing
010504 meteorology & atmospheric sciences Artificial neural network Remote sensing application business.industry Computer science Decision tree learning 0211 other engineering and technologies Soil Science Geology Context (language use) 02 engineering and technology Land cover Machine learning computer.software_genre 01 natural sciences Automation Data set Artificial intelligence Computers in Earth Sciences business computer Algorithm 021101 geological & geomatics engineering 0105 earth and related environmental sciences |
| Zdroj: | Remote Sensing of Environment. 112:2272-2283 |
| ISSN: | 0034-4257 |
| Popis: | Large area land-cover monitoring scenarios, involving large volumes of data, are becoming more prevalent in remote sensing applications. Thus, there is a pressing need for increased automation in the change mapping process. The objective of this research is to compare the performance of three machine learning algorithms (MLAs); two classification tree software routines (S-plus and C4.5) and an artificial neural network (ARTMAP), in the context of mapping land-cover modifications in northern and southern California study sites between 1990/91 and 1996. Comparisons were based on several criteria: overall accuracy, sensitivity to data set size and variation, and noise. ARTMAP produced the most accurate maps overall (∼ 84%), for two study areas — in southern and northern California, and was most resistant to training data deficiencies. The change map generated using ARTMAP has similar accuracies to a human-interpreted map produced by the U.S. Forest Service in the southern study area. ARTMAP appears to be robust and accurate for automated, large area change monitoring as it performed equally well across the diverse study areas with minimal human intervention in the classification process. |
| Databáze: | OpenAIRE |
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