Journal of Remote Sensing Technology
Journal of Remote Sensing Technology(JRST)
Frequency: Annually
Towards more robust land cover classification – fusing low spatial resolution, multi-temporal imagery with high spatial resolution data
The development of rapid and accurate land cover maps for crop acreage estimation of disaster-affected regions in the case of an accidental nuclear fallout, e.g., after the earthquake/tsunami in Japan (2011), is often required to facilitate response efforts. An approach is presented that can generate land cover maps, based on an a posteriori probability-based fusion approach, to augment classification results. Data include established indices and time series features from a Moderate Resolution Imaging Spectrometer (MODIS) and a single RapidEye scene over the Nine Mile Point Nuclear Power Station in Oswego (New York, USA). The overall accuracies are estimated using the USDA-Cropland Data Products for New York State, and approximate accuracy reported is 82%. Advantages include correction for cloud cover and point-in-time dependency by inclusion of multi-temporal data. This approach could prove useful to disaster response decision makers, who require rapid and accurate geospatial information products.
Keywords:Image Fusion; Time Series; Image Classification; Multi-resolution; Land Cover Mapping
Author: Shagan Sah,Jan van Aardt,Peter Bajorski


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