Abstract
The possibility of improving classification accuracies using different training strategies and data transformations within the framework of a supervised maximum likelihood classification scheme was explored in this study. The effect of spatial resolution of data on the accuracy of classification was also studied Single-pixel training strategy resulted in improved classification accuracy over the block-training method. Data transformations gave no significant improvements in accuracy over untransformed data. There was a reduction in classification accuracy as resolution of data improved from 72 m (LISS I) to 36 m (LISS II) while other sensor characteristics remained same.
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Medhavy, T.T., Sharma, T., Dubey, R.P. et al. Crop classification accuracy as influenced by training strategy, data transformation and spatial resolution of data. J Indian Soc Remote Sens 21, 21–28 (1993). https://doi.org/10.1007/BF03020114
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DOI: https://doi.org/10.1007/BF03020114