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基于MODIS-EVI及物候差异免阈值提取黄淮海平原冬小麦面积

张莎 张佳华 白雲 姚凤梅

农业工程学报2018,Vol.34Issue(11):150-158,9.
农业工程学报2018,Vol.34Issue(11):150-158,9.DOI:10.11975/j.issn.1002-6819.2018.11.019

基于MODIS-EVI及物候差异免阈值提取黄淮海平原冬小麦面积

Extracting winter wheat area in Huanghuaihai Plain using MODIS-EVI data and phenology difference avoiding threshold

张莎 1张佳华 2白雲 1姚凤梅2

作者信息

  • 1. 中国科学院遥感与数字地球研究所数字地球重点实验室,北京 100094
  • 2. 中国科学院大学地球与行星科学学院,北京 100049
  • 折叠

摘要

Abstract

Huanghuaihai (HHH) Plain is the main cultivating area of winter wheat in China. Accurately detecting the winter wheat area in HHH Plain is of great importance and significance for grain yield estimation and national food security. Vegetation indices (VIs), such as normalized difference vegetation index (NDVI) or enhanced vegetation index (EVI), have been generally used to characterize the winter wheat cultivation area during some key growing stages. However, such method requires thresholds for VIs, which vary spatially due to the differences of local climates and phenology. In other words, if the study area covers wide range of climate gradients which cause significant phenology differences for winter wheat, one invariant threshold value is not suitable for the whole study area. Previous studies usually set different threshold values manually for different regions or provinces to solve this problem. Thus, there is no doubt that the usual solution increases the workload and introduces more uncertainties. For addressing the above issues, a new method was developed and tested in this study for extracting the winter wheat area over HHH Plain of China. The new method used a vegetation index decrease slope threshold to replace the vegetation index threshold at a specified growing stage, and added the peak number during winter wheat growing season as another decision condition. It avoided the issues of setting different threshold values and achieved good accuracy. First, the relationships between the sowing and maturity day of year (DOY) and climate factors were established by stepwise method. In this step, the ERA-Interim reanalysis data (air temperature, precipitation and solar radiation) and observed sowing and maturity date of winter wheat at 140 agro-meteorological sites were used. Among these sites, 70% of them (98 sites) randomly distributed were selected to build the relationships, and the other 30% (42 sites) were used to validate the established relationships. The ERA-Interim reanalysis data were used rather than the observed climate variables at meteorological sites due to the departure of the location of meteorological site from each other. The R2 values of simulated DOY versus observed DOY at agro-meteorological sites were 0.69 and 0.67 for winter wheat sowing and maturity stage, respectively, and the root mean square error (RMSE) values were 6.12 and 4.88 d, which indicated good reliability of the established relationships between sowing and maturity DOY of winter wheat and climate factors. Based on the established relationships, the gridded sowing and maturity DOY of wheat winter for the entire study area were calculated with ERA meteorological variables. Second, the MODIS EVI data (250 m) before and after maturity were used to calculate a decease slope for each pixel, and MODIS EVI data filtered by Savitzky-Golay (S-G) method were used to calculate the peak frequency of EVI curve between sowing and maturity stage of winter wheat for each pixel. Pixels with a decease slope less than -0.02 and peak frequency equal to 2 were identified as winter wheat. Before these calculations, the sowing and maturity DOY were obtained by resampling to the same resolution with MODIS EVI data. It was unnecessary to set different thresholds for different provinces or regions. Finally, the winter wheat area was obtained after being masked by the 250 m resolution dry land extracted and resampled from land use and land cover data with 1 km resolution. The statistical data were collected from yearbooks and used to validate the statistical area at city and county levels, respectively. Validation results showed that the R2 (RMSE) values were 0.91 (60.08×103 hm2) and 0.80 (8.97×103 hm2) at city and county levels, respectively. The spatial distribution of winter wheat was also agreed well with the results of previous researchers. These demonstrated that the developed method produced a satisfactory accuracy and the result was reliable. The new approach considers the phenology difference and avoids the threshold set, and thus shows a good universal property to extract winter wheat area quickly over a large region.

关键词

遥感/农作物/提取/黄淮海平原/物候差异/冬小麦种植面积提取/普适性/MODISEVI

Key words

remote sensing/crops/extraction/Huanghuaihai Plain/phenology difference/extracting winter wheat area/universality/MODIS EVI

分类

农业科技

引用本文复制引用

张莎,张佳华,白雲,姚凤梅..基于MODIS-EVI及物候差异免阈值提取黄淮海平原冬小麦面积[J].农业工程学报,2018,34(11):150-158,9.

基金项目

国家重点研发计划(2016YFD0300101) (2016YFD0300101)

中科院先导专项A类(XDA19030402) (XDA19030402)

国家自然科学基金(31571565,31671585) (31571565,31671585)

山东自然科学基金重大基础研究项目(ZR2017ZB0422) (ZR2017ZB0422)

农业工程学报

OA北大核心CSCDCSTPCD

1002-6819

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