Uncertainty Problems in Image Change Detection
| Autor: | Wenyu Wang, Changshan Wu, Walter Nsengiyumva, Mryka Hall-Beyer, Weihua Fang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
accuracy analysis
010504 meteorology & atmospheric sciences Computer science Geography Planning and Development 0211 other engineering and technologies TJ807-830 02 engineering and technology Management Monitoring Policy and Law TD194-195 01 natural sciences Renewable energy sources Set (abstract data type) Statistics GE1-350 land change 021101 geological & geomatics engineering 0105 earth and related environmental sciences evaluation Environmental effects of industries and plants Renewable Energy Sustainability and the Environment image change detection Sampling (statistics) Variance (accounting) Thresholding Stratified sampling Environmental sciences Change detection |
| Zdroj: | Sustainability Volume 12 Issue 1 Sustainability, Vol 12, Iss 1, p 274 (2019) |
| ISSN: | 2071-1050 |
| DOI: | 10.3390/su12010274 |
| Popis: | Image Change Detection (ICD) methods are widely adopted to update large area land use/cover products. Uncertainty problems, however, are well known in such techniques, and a transparent assessment is necessary. In this study, a framework was proposed for evaluating binary land change utilizing remote sensing images. First, two widely adopted ICD methods were used to establish change maps. Second, binary decisions on Change (C) and Non-Change (NC) classes were reached through thresholding on change maps. Then, results were evaluated using two sampling designs: random sampling and stratified sampling. Analysis of results suggests that (1) for random sampling, with an increasing threshold on change variables, the overall accuracy increases and shows a large variance, which is highly correlated with the C omission error and (2) comparatively, for stratified sampling, in which two strata (i.e., C and NC) were set, the overall accuracy shows a smaller variance and is highly associated with the NC commission error. The significant trends in accuracy assessments indicate the trade-offs between the C and NC classification errors in a binary decision and can present superficial or perfunctory accuracy evaluation in certain circumstances that the causes of error sources and uncertainty problems in ICD are not fully understood. |
| Databáze: | OpenAIRE |
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