基于高通滤波算法的水稻遥感影像适宜尺度筛选

doi:10.3969/j.issn.1000-6362.2018.05.006

摘要/Abstract

摘要： 为确定江苏地区水稻田块信息提取的适宜尺度，选取拔节期30m×30m空间分辨率HJ1A/CCD2影像和16m×16m空间分辨率GF1/WFV4近红外波段影像，采用高通滤波（HPF）算法构建4种空间尺度融合影像。利用定量指标评价和植被指数反演评价分析4种融合影像筛选适宜尺度，最后通过多类光谱指标构建决策树提取水稻面积与PROSAIL冠层光谱模型反演叶面积指数（LAI），验证融合影像适宜尺度相较原始影像尺度的优越性。结果表明：（1）综合定量指标评价和植被指数反演评价，20m×20m尺度和15m×15m尺度均可保证光谱继承性，反演水稻田块信息，而结合尺度优势，适宜尺度筛选为15m×15m；（2）与原始影像尺度相比，15m×15m尺度空间分辨率提高，同时水稻面积提取精度增大，面积精度93.33%，样方精度94.71%，标准误差0.25hm2，且能理想反演LAI，精度达94.69%，标准误差0.893。结论表明，研究区水稻田块信息反演的适宜尺度为15m×15m。

关键词: 影像质量评价, 水稻面积, 样方精度, PROSAIL冠层光谱模型, LAI

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

张晓忆，景元书，李卫国. 基于高通滤波算法的水稻遥感影像适宜尺度筛选[J]. 中国农业气象, 2018, 39(05): 344-353.

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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