PIF method for relative radiometric correction of remote sensing images

doi:10.6046/gtzyyg.2017.01.02

Abstract
References
Related Articles
Metrics

Download: PDF(1911 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

Relative radiometric normalization of multi temporal remote sensing images is the prerequisite of dynamic monitoring of remote sensing. The effect of pseudo-invariant feature(PIF) relative radiation correction is largely determined by the selection of PIF points. The method of ordinary artificial point selection has a lot of shortcomings, such as strong subjectivity and the fact that the points' quality and quantity cannot be controlled. The following operations proposed in this paper will solve these problems. First, the accurate geometric correction and registration of the two TM images were carried out. Then the PIF was refined in stepwise way by combining the band ratio operation and quality control to improve the quality of PIF and reduce the subjectivity of its selection. The quality of selected points was evaluated by using the correlation coefficient of corresponding sample points of each band. The method of least square regression analysis was used to get the gain and offset based on the qualified PIF points selected. Then the relative radiometric correction of the two TM images was carried out. The spectrum curves of typical features, root mean square error, NDVI statistics between corrected image and original image were analyzed. The results show that the correction effect is satisfactory.

Keywords Caofeidian Newly-developed Area land subsidence PSInSAR technique groundwater engineering disturbance

:	TP751.1
	P237

Issue Date: 23 January 2017

	Service

	E-mail this article
	E-mail Alert
	RSS
	Articles by authors

	LI Man
	GE Daqing
	ZHANG Ling
	LIU Bin
	GUO Xiaofang
	WANG Yan

Cite this article:

LI Man,GE Daqing,ZHANG Ling, et al. PIF method for relative radiometric correction of remote sensing images[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(1): 7-13.

URL:

https://www.gtzyyg.com/EN/10.6046/gtzyyg.2017.01.02 OR https://www.gtzyyg.com/EN/Y2017/V29/I1/7

[1] 赵英时.遥感应用分析原理与方法[M].北京:科学出版社,2003. Zhao Y S.The Principle and Method of Analysis of Remote Sensing Application[M].Beijing:Science Press,2003.
[2] 王永锋,靖娟利.基于FLAASH和ATCOR2模型的Landsat ETM⁺影像大气校正比较[J].测绘与空间地理信息,2014,37(9):122-125. Wang Y F,Jing J L.Comparison of FLAASH and ATCOR2 atmospheric correction modules on Landsat ETM⁺ data[J].Geomatics & Spatial Information Technology,2014,37(9):122-125.
[3] Chavez P S Jr,Mackinnon D J.Automatic detection of vegetation changes in the southwestern United States using remotely sensed images[J].Photogrammetric Engineering and Remote Sensing,1994,60(5):571-583.
[4] 张友水,冯学智,周成虎.多时相TM影像相对辐射校正研究[J].测绘学报,2006,35(2):122-127. Zhang Y S,Feng X Z,Zhou C H.Relative radiometric correction for multitemporal TM images[J].Acta Geodaetica et Cartographica Sinica,2006,35(2):122-127.
[5] 丁丽霞,周斌,王人潮.遥感监测中5种相对辐射校正方法研究[J].浙江大学学报:农业与生命科学版,2005,31(3):269-276. Ding L X,Zhou B,Wang R C.Comparison of five relative radiometric normalization techniques for remote sensing monitoring[J].Journal of Zhejiang University:Agriculture & Life Sciences,2005,31(3):269-276.
[6] 邓书斌.ENVI遥感图像处理方法[M].北京:科学出版社,2010:290. Deng S B.Remote Sensing Image Processing Method[M].Beijing:Science Press,2010:290.
[7] 郑伟,曾志远.遥感图像大气校正的黑暗像元法[J].国土资源遥感,2005,17(1):8-11.doi:10.6046/gtzyyg.2005.01.02. Zheng W,Zeng Z Y.Dark-object methods for atmospheric correction of remote sensing image[J].Remote Sensing for Land and Resources,2005,17(1):8-11.doi:10.6046/gtzyyg.2005.01.02.
[8] Ahern F J,Goodenough D G,Jain S C,et al.Use of clear lakes as standard reflectors for atmospheric measurements[C]//Proceedings of the 11th International Symposium on Remote Sensing of Environment. Ann Arbor,America,1977:731-775.
[9] Gordon H R.Removal of atmospheric effects from satellite imagery of the oceans[J].Applied Optics,1978,17(10):1631-1636.
[10] 张鹏强,余旭初,刘智,等.多时相遥感图像相对辐射校正[J].遥感学报,2006,10(3):339-344. Zhang P Q,Yu X C,Liu Z,et al.A study on relative radiometric correction of multitemporal remote sensing images[J].Journal of Remote Sensing,2006,10(3):339-344.
[11] 韩改新.一种新的遥感影像变化检测相对辐射校正方法[J].测绘与空间地理信息,2008,31(3):84-86,89. Han G X.A new method of the relative radiometric normalization in remote sensing image change detection[J].Geomatics & Spatial Information Technology,2008,31(3):84-86,89.
[12] 邓书斌,武红敢,江涛.遥感动态监测中的相对辐射校正方法研究[J].遥感应用,2008(5):71-75. Deng S B,Wu H G,Jiang T.A study on relative radiometric normalization for remote sensing dynamic monitoring[J].Remote Sensing Information,2008(5):71-75.
[13] 邢宇.小波变换在遥感图像相对辐射校正中的应用[J].测绘与空间地理信息,2015,38(6):13-14,31. Xing Y.Application of wavelet transform in relative radiometric correction of remote sensing image[J].Geomatics & Spatial Information Technology,2015,38(6):13-14,31.
[14] 诸云强,孙九林.土地利用遥感动态监测应用研究——以兰州安宁区为例[J].资源科学,2006,28(2):82-87. Zhu Y Q,Sun J L.Dynamic monitoring of land use through remote sensing technology:A case study in Anning district,Lanzhou City[J].Resources Science,2006,28(2):82-87.
[15] 郭丽峰,高小红,亢健,等.伪不变特征法在遥感影像归一化处理中的应用[J].遥感技术与应用,2009,24(5):588-595. Guo L F,Gao X H,Kang J,et al.Application of the pseudo-invariant feature in normalization process of the remote sensing images[J].Remote Sensing Technology and Application,2009,24(5):588-595.
[16] 李居亮,都金康,张友水.用基于相对辐射校正的TM影像监测绍兴土地覆盖变化[J].遥感信息,2004(4):22-25. Li J L,Du J K,Zhang Y S.Land cover change monitoring in Shaoxing by radiometric calibrated TM data[J].Remote Sensing Information,2004(4):22-25.

[1]	YU Bing, TAN Qingxue, LIU Guoxiang, LIU Fuzhen, ZHOU Zhiwei, HE Zhiyong. Land subsidence monitoring based on differential interferometry using time series of high-resolution TerraSAR-X images and monitoring precision verification[J]. Remote Sensing for Natural Resources, 2021, 33(4): 26-33.
[2]	ZHOU Chaofan, GONG Huili, CHEN Beibei, LEI Kunchao, SHI Liyuan, ZHAO Yu. Prediction of land subsidence along Tianjin-Baoding high-speed railway using WT-RF method[J]. Remote Sensing for Natural Resources, 2021, 33(4): 34-42.
[3]	SHI Min, GONG Huili, CHEN Beibei, GAO Mingliang, ZHANG Shunkang. Monitoring of land subsidence in Beijing-Tianjin-Hebei plain during 2016—2018 based on InSAR and Sentinel-1A data[J]. Remote Sensing for Natural Resources, 2021, 33(4): 55-63.
[4]	YU Hairuo, GONG Huili, CHEN Beibei, ZHOU Chaofan. Emerging risks and the prospect of urban underground space security based on InSAR-GRACE satellite under the new hydrological background[J]. Remote Sensing for Land & Resources, 2020, 32(4): 16-22.
[5]	WANG Baocun, ZHU Lin, PAN Deng, GUO Lingfei, PENG Peng. Research on temporal and spatial evolution law of land subsidence in Zhengzhou[J]. Remote Sensing for Land & Resources, 2020, 32(3): 143-148.
[6]	Yike SUN, Huili GONG, Beibei CHEN, Chaofan ZHOU, Wenfeng CHEN, Xiaojing ZHANG. Quantitative analysis of uneven subsidence by Moran’s I and cross wavelet[J]. Remote Sensing for Land & Resources, 2020, 32(2): 186-195.
[7]	Xiaojing ZHANG, Beibei CHEN, Kunchao LEI, Wenfeng CHEN, Mingliang GAO, Chaofan ZHOU, Guangyao DUAN. Characteristics of land subsidence along Beijing-Tianjin inter-city railway (Beijing section)[J]. Remote Sensing for Land & Resources, 2019, 31(1): 171-179.
[8]	Gang LIU, Yunpeng YAN, Jianyu LIU. Research on relationship between lakes and tectonic background in western Tibetan Plateau using remote sensing[J]. Remote Sensing for Land & Resources, 2018, 30(2): 154-161.
[9]	WANG Xuqing, WANG Yu, GUO Yingping. Application of ZY1-02C satellite data to the survey of groundwater overflow zone in the front of alluvial-pluvial fan zone of Golmud River[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(s1): 155-159.
[10]	CHEN Jiwei, ZENG Qiming, JIAO Jian, ZHAO Binchen. SBAS time series analysis technique based on Sentinel-1A TOPS SAR images: A case study of Yellow River Delta[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(4): 82-87.
[11]	LI Man, GE Daqing, ZHANG Ling, LIU Bin, GUO Xiaofang, WANG Yan. Characteristics and influencing factors of land subsidence in Caofeidian Newly-developed Area based on PSInSAR technique[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(4): 119-126.
[12]	YANG Chengsheng, LIU Yuanyuan, AO Meng. Study of land subsidence and groundwater activity using SBAS time-series analysis[J]. REMOTE SENSING FOR LAND & RESOURCES, 2015, 27(1): 127-132.
[13]	WANG Yan, ZHANG Ling, GE Daqing, ZHANG Xuedong, LI Man. Experimental study of vertical and horizontal displacement retrieval by joint analysis of ascending and descending PSInSAR data[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(4): 97-102.
[14]	GE Daqing, YIN Yueping, WANG Yan, ZHANG Ling, GUO Xiaofang, WANG Yi. Seasonal subsidence-rebound and ground water level changes monitoring by using coherent target InSAR technique：A case study of Dezhou, Shandong[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(1): 103-109.
[15]	LUO Hao, WANG Hong, SHI Changhui. Retrieving groundwater in Yellow River Delta area using remote sensing[J]. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(3): 145-152.

Viewed

Full text

Abstract

Cited

Shared

Discussed