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[1]ZHOU Junli,XUE Huazhu,DONG Guotao,et al.Comparison and Analysis of Applicability of AMSR_2 Microwave Vegetation Index in the Yellow River Basin[J].Research of Soil and Water Conservation,2018,25(05):378-384.

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Comparison and Analysis of Applicability of AMSR_2 Microwave Vegetation Index in the Yellow River Basin

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 25 Number of periods: 2018 05 Page number: 378-384 Column: Public date: 2018-09-06

Title:: Comparison and Analysis of Applicability of AMSR_2 Microwave Vegetation Index in the Yellow River Basin

Author(s):: ZHOU Junli^1,2, XUE Huazhu¹, DONG Guotao², FAN Dong¹, GUO Xinwei², YIN Huijuan²; 1. School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, Henan 454000, China;
2. Key Laboratory of Soil and Water Loss Process and Control on the Loess Plateau, Ministry of Water Resources, Yellow River Institute of Hydraulic Research, Zhengzhou 450003, China

Keywords:: AMSR_2 microwave data; vegetation index; applicability; Yellow River Basin

CLC:: TP79;Q94

DOI:: -

Abstract:: Microwave data have the advantages of all-weather, penetrating and free from the clouds, and it is more and more widely used in remote sensing research. This paper uses AMSR_2 dual polarization brightness temperature data from July 2012 to December 2016, to invert microwave polarization index MVI and microwave polarization difference index MPDI₁₈ and MPDI_36.5 of different frequencies. The difference between the microwave vegetation index and the optical vegetation index NDVI were compared, and the applicability of microwave vegetation index of the Yellow River Basin was analyzed. The result showed that the microwave penetration index MVI was negatively correlated with the optical vegetation index NDVI, microwave polarization difference index MPDI₁₈ and MPDI_36.5 were significantly positively correlated with the optical vegetation index NDVI; among them, the microwave polarization difference index MPDI_36.5 was almost identical with the monthly variation trend of the optical vegetation index NDVI, the correlation coefficient reached up to 0.999. The responses of microwave vegetation index and optical vegetation index to rainfall were approximately the same. As a whole, the microwave penetration index and microwave polarization difference index have good applicability in the Yellow River Basin.

References:: [1] 郭铌,陈添宇,陈乾.用NOAA气象卫星资料对甘肃省河东地区土地覆盖分类[J].高原气象,1995,14(4):467-475.
[2] 孙睿,朱启疆.中国陆地植被净第一性生产力及季节变化研究[J].地理学报,2000,55(1):36-45.
[3] 陈维英,肖乾广.距平植被指数在1992年特大干旱监测中的应用[J].遥感学报,1994,36(2):106-112.
[4] 郭铌.植被指数及其研究进展[J].干旱气象,2003,21(4):71-75.
[5] 陈亮,杜今阳. L波段多角度微波植被指数研究[J].遙感信息,2010,2010(1):13-16.
[6] 李爽,宋小宁,冷佩.被动微波遥感植被指数在中国的应用研究[J].干旱区资源与环境,2014,28(8):44-49.
[7] 邱玉宝,郭华东,石利娟,等.基于AMSR-E的全球陆表被动微波发射率数据集[J].遥感技术与应用,2016,31(4):809-819.
[8] Shi J, Jackson T, Tao J, et al. Microwave vegetation indexes derived from satellite microwave radiometers[C]//IEEE, Geoscience and Remote Sensing Symposium, 2007.
[9] Shi J, Jackson T, Tao J, et al. Microwave vegetation indices for short vegetation covers from satellite passive microwave sensor AMSR-E[J]. Remote Sensing of Environment, 2008,112(12):4285-4300.
[10] 陈思宇,于惠,冯琦胜,等.基于amsr-e数据的微波植被指数与modis植被指数关系研究[J].草业科学,2012,29(3):377-383.
[11] 于惠,冯琦胜,陈思宇,等.基于微波植被指数的甘南草地生物量动态监测[J].兰州大学学报:自然科学版,2011,47(4):69-74.
[12] 李爽,宋小宁,冷佩.被动微波遥感植被指数在中国的应用研究[J].干旱区资源与环境,2014,28(8):44-49.
[13] Shi J, Jiang L, Zhang L, et al. A parameterized multifrequency-polarization surface emission model[J]. Journal of Remote Sensing, 2006,43(12):2831-2841.
[14] Shi J, Chen K S, Li Q, et al. A parameterized surface reflectivity model and estimation of bare-surface soil moisture with L-band radiometer[J]. Ieee Transactions on Geoscience & Remote Sensing, 2002,40(12):2674-2686.
[15] 陈思宇,于惠,冯琦胜,等.基于amsr-e数据的微波植被指数与modis植被指数关系研究[J].草业科学,2012,29(3):377-383.
[16] 吕京国,张小咏,蒋玲梅,等.微波穿透指数MVI与光学植被指数NDVI的关系探讨[J].遙感信息,2009,2009(6):39-42.
[17] Choudhury B J, Tucker C J, Golus R E, et al. Monitoring vegetation using Nim bus-7 scanning multichannel microwave radiometer’s data[J]. International Journal of Remote Sensing, 1987,8(3):533-538.
[18] Choudhury B J, Tucker C J. Monitoring global vegetation using Nimbus-737 GHz Data some empirical relations[J]. International Journal of Remote Sensing, 1987,8(7):1085-1090.
[19] Paloscia S, Pampaloni P. Microwave vegetation indexes for detecting biomass and water conditions of agricultural crops[J]. Remote Sensing of Environment, 1992,40(1):15-26.
[20] Becker F, Choudhury B J. Relative sensitivity of normalized difference vegetation index(NDVI)and microwave polarization difference index(MPDI)for vegetation and desertification monitoring.[J]. Remote Sensing of Environment, 1988,24(2):297-311.
[21] 毛克彪,唐华俊,周清波,等. Amsr-e微波极化指数与modis植被指数关系研究[J].国土资源遥感,2007,1(1):27-31.
[22] Kachi M, Imaoka K, Shimoda H. Long-term observations of water and climate by AMSR-E and GCOM-W[J]. Proceedings of Spie-the International Society for Optical Engineering, 2009,7474(1):24-26.
[23] Li L, Njoku E G, Im E, et al. A preliminary survey of radio-frequency interference over the U. S. In Aqua AMSR-E data[J]. Geoscience & Remote Sensing Ieee Transactions on, 2004,42(2):380-390.
[24] Njoku E G, Ashcroft P, Chan T K, et al. Global survey and statistics of radio-frequency interference in AMSR-E land observations[J]. Ieee Transactions on Geoscience & Remote Sensing, 2005,43(5):938-947.
[25] Kidd C. Radio frequency interference at passive microwave earth observation frequencies[J]. International Journal of Remote Sensing, 2006,27(18):3853-3865.
[26] Njoku E G, Jackson T J, Lakshmi V, et al. Soil moisture retrieval from AMSR-E[J]. Ieee Transactions on Geoscience & Remote Sensing, 2003,41(2):215-229.
[27] 李秀花,师庆东,常顺利,等.中国西北干旱区1981-2001年NDVI对气候变化的响应分析[J].中国沙漠,2009,29(5):989-994.

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