Optimal Scale Screening of Paddy Rice in Remote Sensing Imagery Based on High Pass Filter Fusion

doi:10.3969/j.issn.1000-6362.2018.05.006

Abstract

Abstract: In order to confirm optimal scale of paddy rice extraction in Jiangsu, the experiment was first set up four fusion images with different scales using HPF algorithm, based on HJ1A/CCD2 image (30m×30m) and GF1/WFV4 near-infrared image (16m×16m). To screen optimal scale, it was then conducted the four images on quantitative index assessment and vegetation index inversion assessment. At last, the superiority of optimal scale in fusion images was verified with testing data from extraction of paddy rice area with decision tree method composed of multi-spectral indexes and inversion of paddy rice LAI with PROSAIL model. The results showed that: (1)it was 20m×20m and 15m×15m that both had spectral inheritance and spectral optimization to meet the use requirements, based on quantitative index assessment and vegetation index inversion assessment. Optimal scale was chose 15m×15m because of scale advantage. (2)Compared with original image scales, 15m×15m was verified higher spatial resolution, best area extraction, and improved LAI inversion, which area accuracy 93.33%, quadrat accuracy 94.71%, RMSE 0.25 ha, and LAI inversion accuracy 94.69%, RMSE 0.893. In conclusion, the optimal scale which could inverse paddy rice in research area was 15m×15m.

Key words: Image quality evaluation, Paddy rice area, Quadrat accuracy, PROSAIL model, LAI

ZHANG Xiao-yi，JING Yuan-shu,LI Wei-guo. Optimal Scale Screening of Paddy Rice in Remote Sensing Imagery Based on High Pass Filter Fusion[J]. Chinese Journal of Agrometeorology, 2018, 39(05): 344-353.

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