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The map was further refined by taking into account hydrogeologic data collected during mining activities.
The flood map was further visualized with other variables in terms of the properties of coal and coal reservoir and its geological conditions.
The classified map was further segmented into polygons based on a region growing algorithm, yielding multi-scale maps of soil-landscape relations that were compared with maps of soil landforms identified from aerial photographs, satellite images and field observation.
Second, based on the Global Digital Elevation Model data from the ASTER satellite, the land-use/cover map was further re-classified for elevation demarcation into waterless, run-up and flooded areas.
The normalized difference map was further transformed into a rank map (sub-index), to remove the negative values, using the following polynomial function: r =, left( {0.5, *, C^{2} } right), +, left( {4.5, *, C} right), +, 5 (2)where C stands for the contamination index value for each grid cell in the normalized difference map and r stands for the corresponding rank value.
The resolution of this map was further improved by adding COSII and AFLP markers [ 29, 30].
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Saliency map is further smoothened by Gaussian filter β(f).
The transmission map is further refined, and the haze-free image is finally reconstructed as Eq. (3).
The line-scan analysis of EDX map is further conducted to investigate the distribution of components in the solar cell, as shown in Fig. S3.
The 4363 SNPs that were localised on the integrated map were further used for investigating polymorphism variation across the linkage groups.
The output of the corrected lineaments from high resolution Google Earth image and topographical maps was further processed for hydrogeological analysis whereby non-hydrogeologic significant lineaments lying on DEM highs were removed.
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