Comparison of upscaling cropland and non-cropland map using uncertainty weighted majority rule-based and the majority rule-based aggregation methods |
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| Authors: | Peijun Sun Jinshui Zhang |
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| Institution: | 1. State Key Laboratory of Remote Sensing Science, Faculty of Geographical Sciences, Beijing Normal University, Beijing, China;2. Institute of Remote Sensing and Engineering, Faculty of Geographical Sciences, Beijing Normal University, Beijing, China;3. Department of Natural Resources and the Environment, University of New Hampshire, Durham, NH, USA;4. Institute of Remote Sensing and Engineering, Faculty of Geographical Sciences, Beijing Normal University, Beijing, China;5. State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Sciences, Beijing Normal University, Beijing, China |
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| Abstract: | Aggregation method is seriously impacted by the landscape characteristics, which has been emphasized due to proportional errors. This research proposed an uncertainty weighted majority rule-based aggregation method (UWMRB) to upscale the cropland/non-cropland map. The Cropland Data Layer for 2016 at 30m resolution, with its corresponding confidence level data, were collected to conduct the experiment using UWMRB and majority rule-based aggregation method. Proportional errors of crop/non-crop were used to assess the accuracy of the two methods. Ordinal logistic regression was used to obtain the probability of an error occurring to predict the uncertainty of both methods. The results show that UWMRB can achieve the lower proportional errors with lower uncertainty. Also, it can reduce the influence of complexity and fragmentation of landscape on aggregation performance. Additionally, the examination of UWMRB provides an important view of application of uncertainty information for upscaling land cover maps in an efficient way. |
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| Keywords: | Upscale aggregation uncertainty weighted majority rule cropland map |
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