Winter Wheat Mixed Pixel Decomposition Based on NDVI Time-order Characters and Area Estimation

doi:10.11924/j.issn.1000-6850.casb19030086

Abstract

Abstract: Crop extraction based on MODIS data is easily affected by the mixed pixels. In order to reduce the omission and commission errors caused by mixed pixels, this paper proposed a linear mixed pixel decomposition model and establish a quantitative relation between winter wheat proportion and crest-trough differences of MODIS/NDVI time series images. This model was established based on MODIS and GF data of Baoding city of 2017, and verified based on MODIS and GF data of Baoding city of 2014. Results showed that the mean value of pixel purity index (PPI) accuracy was 0.485. The estimated value of winter wheat area of Baoding city in 2014 was 400.5 thousand hm2 based on mixed pixel decomposition model and the “actual value” of winter wheat area of Baoding city in 2014 was 373.9 thousand hm2 based on GF data, the absolute error was 26.6 thousand hm2 and the relative error rate was 7.11%. The applicability of this model was evaluated in 8 prefecture-level cities where winter wheat was widely cultivated in Hebei province. The result showed that the average error rate of different cities in Hebei province was 3.69%. The winter wheat estimation error based on the proposed model is relatively low, with relatively high data reliability. Besides, impact of terrain on the model is relatively low, and the model is widely applicable.

CLC Number:

S252

References

[1] 王学,李秀彬,谈明洪,等.华北平原2001-2011年冬小麦播种面积变化遥感监测[J].农业工程学报,2015,31(8):190-199.
[2] 冯美臣,杨武德,张东彦,等.基于TM和MODIS数据的水旱地冬小麦面积提取和长势监测[J].农业工程学报,2009,25(3):103-109.
[3] 陈健,刘云慧,宇振荣.基于时序MODIS-EVI数据的冬小麦种植信息提取[J].中国农学通报,2011,27(01):446-450.
[4] 申健,常庆瑞,李粉玲,等.基于时序NDVI的关中地区冬小麦种植信息遥感提取[J].农业机械学报,2017,48(3):215-220.
[5] 姜涛,朱文泉,詹培,等.一种抗时序数据噪声的冬小麦识别方法研究[J].遥感技术与应用,2017,32(4):698-708.
[6] 张莎,张佳华,白雲,等．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．
[7] 潘耀忠,李乐,张锦水,等.基于典型物候特征的MODIS-EVI时间序列数据农作物种植面积提取方法——小区域冬小麦实验研究[J].遥感学报,2011,15(3):578-594.
[8] 李乐,张锦水,朱文泉,等.地块支持下MODIS-NDVI时间序列冬小麦种植面积测量研究[J].光谱学与光谱分析,2011,31(5):1379-1383.
[9] 刘红超,梁燕,张喜旺.多时相影像的冬小麦种植面积提取及估产[J].遥感信息,2017,32(5):87-92.
[10] 李颖,陈秀万,段红伟,等.多源多时相遥感数据在冬小麦识别中的应用研究[J].地理与地理信息科学,2010,26(4):47-49.
[11] Rahman A F, Dragoni D, Didan K, et al. Detecting large scale conversion of mangroves to aquaculture with change point and mixed-pixel analyses of high-fidelity MODIS data[J]. Remote Sensing of Environment, 2013, 130(4): 96－107.
[12] Kuusinen N, Tomppo E, Berninger F. Linear unmixing of MODIS albedo composites to infer subpixel land cover type albedos[J]. International Journal of Applied Earth Observations Geoinformation, 2013, 23(23): 324－333.
[13] 武永利,王云峰,张建新,等.应用线性混合模型遥感监测冬小麦种植面积[J].农业工程学报,2009,25(2):136-140.
[14] 王凯,赵军,朱国锋,等.基于GF-1遥感数据决策树与混合像元分解模型的冬小麦种植面积早期估算[J].遥感技术与应用,2018,33(1):158-167.
[15]王连喜,徐胜男,李琪,等.基于决策树和混合像元分解的江苏省冬小麦种植面积提取[J].农业工程学报,2016(5):182-187.
[16] Tsutsumida N, Comber A, Barrett K, et al. Sub-Pixel Classification of MODIS EVI for Annual Mappings of Impervious Surface Areas[J]. Remote Sensing, 2016, 8(2):143.
[17] Liu C, Xie D, Shi J, et al. Subpixel mapping of water cover with MODIS in Tibetan Plateau[C]// Geoscience and Remote Sensing Symposium,2009 IEEE International,igarss. IEEE, 2010:307－309.
[18] Roosta H, Saradjian M R. Sub-pixel classification of MODIS images[C]// Proceedings of the 6th WSEAS international conference on Non-linear analysis, non-linear systems and chaos. World Scientific and Engineering Academy and Society (WSEAS), 2007:103－108.
[19] Kumar U, Raja K S, Mukhopadhyay C, et al. A Neural Network Based Hybrid Mixture Model to Extract Information from Non-linear Mixed Pixels[J]. Information, 2012, 3(3):420－441.
[20] Kumar U, Mukhopadhyay C, Raja K, et al. Soft Classification Based Sub-pixel Allocation Model[C]// International Conference on Operations Research for A Growing Nation" in Conjunction with the, Convention of Operation Research Society of India. 2008.
[21] Fritz S, Massart M, Savin I, et al. The use of MODIS data to derive acreage estimations for larger fields: A case study in the south-western Rostov region of Russia[J]. International Journal of Applied Earth Observation Geoinformation, 2008, 10(4):453－466.
[22] 田珊珊,杨敏华.遥感影像混合像元分解算法对比分析[J].现代测绘,2016,39(1):11-13.
[23] 李耀辉,王金鑫,李颖.应用时间序列EVI的MERSI多光谱混合像元分解[J].遥感学报,2016,20(3):459-467.
[24]郝虑远,孙睿,谢东辉,等.基于改进N-FINDR算法的华北平原冬小麦面积提取[J].农业工程学报,2013,29(15):153-161.
[25] Liu W, Wu E Y. Comparison of non-linear mixture models: sub-pixel classification[J]. Remote Sensing of Environment, 2005, 94(2):145－154.
[26] Lu L, Huang Y, Di L, et al. A New Spatial Attraction Model for Improving Subpixel Land Cover Classification[J]. Remote Sensing, 2017, 9(4):360.
[27]王群明.基于软硬属性转换的遥感图像亚像元定位算法[J].测绘学报,2016,45(4):503.
[28] Zhao J, Wang Y, Zhang H, et al. Spatially and temporally continuous LAI datasets based on the mixed pixel decomposition method[J]. Springerplus, 2016, 5(1):516.
[29] 陈飞宇,胡友彬,施恩.海岸线亚像元定位技术研究进展[J].现代计算机(专业版),2018,3(1):53-57.
[30] Kumar S. Fuzzy-Based Sub-Pixel Classification of Satellite Imagery[J]. International Journal of Emerging Trends Technology in Computer Science, 2012, 3(1): 593－598.
[31] Ling F, Du Y, Zhang Y, et al. Burned-Area Mapping at the Subpixel Scale With MODIS Images[J]. IEEE Geoscience Remote Sensing Letters, 2015, 12(9):1963－1967.
[32] 王金星,侯敏.基于RS与GIS技术的生态环境保护规划研究——以保定市为例[J].资源与产业,2009,11(4):42-45.
[33] 刘佳,王利民,杨玲波,等.基于6S模型的GF-1卫星影像大气校正及效果[J].农业工程学报,2015,31(19):159-168.
[34] 刘佳,王利民,杨玲波,等.基于有理多项式模型区域网平差的GF-1影像几何校正[J].农业工程学报,2015,31(22):146-154.
[35] 王利民,刘佳,杨玲波,等.基于NDVI加权指数的冬小麦种植面积遥感监测[J].农业工程学报,2016,32(17):127-135.
[36] 河北省人民政府办公厅,河北省统计局.河北农村统计年鉴2015[M].中国统计出版社,2015.