First image
Previous image

Next image
Last image
Show double pages

Use the mouse to select the image area you want to share.

Please select which information should be copied to the clipboard by clicking on the link:

Link to the viewer page with highlighted frame
Link to IIIF image fragment

Mapping without the sun

Access restriction

There is no access restriction for this record.

Copyright

The copyright and related rights status of this record has not been evaluated or is not clear. Please refer to the organization that has made the Item available for more information.

Search in

Bibliographic data

fullscreen: Mapping without the sun

Monograph

Persistent identifier:: 856578517

Author:: Zhang, Jixian

Title:: Mapping without the sun

Sub title:: techniques and applications of optical and SAR imagery fusion ; Chengdu, China, 25 - 27 September 2007

Scope:: 1 Online-Ressource (III, 352 Seiten)

Year of publication:: 2007

Place of publication:: Lemmer

Publisher of the original:: GITC

Identifier (digital):: 856578517

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: RESEARCH ON SURFACE SUBSIDENCE MONITORING WITH INSAR/GPS DATA FUSION IN MINING AREA. ZHANG Ji-chao, SONG Wei-dong, ZHANG Ji-xian, SHI Jin-feng

Document type:: Monograph

Structure type:: Chapter

Contents

Table of contents

Mapping without the sun
Cover
ColorChart
Title page
Table of Content
Foreword
Scientific Committee:
Organizing Committee:
DECISION FUSION OF MULTITEMPORAL SAR AND MULTISPECTRAL IMAGERY FOR IMPROVED LAND COVER CLASSIFICATION B. Waske a, J. A. Benediktsson b’*
SYNERGISTIC USE OF OPTICAL AND INSAR DATA FOR URBAN IMPERVIOUS SURFACE MAPPING: A CASE STUDY IN HONG KONG. Liming Jiang, Hui Lin, Mingsheng Liao, Limin Yang
A NOVEL FUSION METHOD OF SAR AND OPTICAL IMAGES FOR URBAN OBJECT EXTRACTION. Jia Yonghong, Rick S. Blum,Ma Yunxia
REAL-TIME SAR SIMULATION FOR CHANGE DETECTION APPLICATIONS BASED ON DATA FUSION. Timo Balz
THE OPTIMIZING METHOD OF FUSING SAR WITH OPTICAL IMAGES FOR INFORMATION EXTRACTION. Feng Xie, Yingying Chen, Yi Lin
ORTHORECTIFYING SPACEBORNE SAR BY DEM BASED ON FINE REGISTRATION. Hongjian You, Fu Kun
DETECTION AND ANALYSIS OF EARTHQUAKE-INDUCED URBAN DISASTER BASED ON INSAR COHERENCE. M. He, X. F. He
MULTI-SCALE SAR LAND USE/LAND COVER CLASSIFICATION BASED ON CO-OCCURRENCE PROBABILITIES. Yu ZENG, Jixian ZHANG, J. L.VAN GENDEREN, Haitao LI
TERRASAR-X AND TANDEM-X: REVOLUTION IN SPACEBORNE RADAR. Ralf Duering
A MULTI-WAVELENGTH IMAGING SYSTEM FOR DETECTION OF FOREIGN FIBERS IN COTTON. Lu Dehao
A FUSION ALGORITHM OF HIGH SPATIAL AND SPECTRAL RESOLUTION IMAGES BASED ON ICA. GuoKun Zhang, LeiGuang Wang, Hongyan Zhang
A SUPER RESOLUTION RECONSTRUCTION ALGORITHM TO MULTI-TEMPORAL REMOTE SENSING IMAGES. Pingxiang Li, Jixian Zhang, Huanfeng Shen, Liangpei Zhang
COMPARISON OF MORPHOLOGICAL PYRAMID AND LAPLACIAN PYRAMID TECHNIQUES FOR FUSING DIFFERENT FOCUSING IMAGES. Jia Yonghong, Fu Xiujun, Yu Hongwei
MONITORING AND CHARACTERIZING NATURAL HAZARDS WITH SATELLITE INSAR IMAGERY. Z. Lu
PREDICTION AND SIMULATIONS OF MALAYSIAN FOREST FIRES BY MEANS OF RANDOM SPREAD. Jean Serra, Mohd Dini Hairi Suliman, and Mastura Mahmud
TEXTURE CLASSIFICATION RESEARCH BASED ON LIFTING-BASED DWT 9/7 WAVELET. Hong Zhang, Ning Shu
REMOTE SENSING IMAGE SEGMENTATION BASED SELF-ORGANIZING MAP AT MULTI-SCALE. Zhao Xi-an, Zhang Xue-wen Wei Shi-yan
A JOINT SPATIAL-TEMPORAL CLASSIFICATION AND FEATURE BOUNDARY UPDATING MODEL. P. Caccetta
THE APPLICATION RESEARCH IN ASSISTANT CLASSIFICATION OF REMOTE SENSING IMAGE BY TEXTURE FEATURES COMBINED WITH SPECTRA FEATURES. Y. M. Fang, X. Q. Zuo, Y. J. Yang, J. H. Feng
A KIND OF THE METHODS FOR SAR AND OPTICAL IMAGES FUSION BASED ON THE LIFTING WAVELET. Shao Yongshe, Chen Ying, Li Jing
SOIL MOISTURE RETRIEVAL COMBINING OPTICAL AND RADAR DATA DURING SMEX02. Chen Quan, Li Zhen, Tian Bangsen
A TARGET DETECTION METHOD BASED ON SAR AND OPTICAL IMAGE DATA FUSION. Sun Mu-han, Zhou Yin-qing, Xu Hua-ping
FUSION SAR AND OPTICAL IMAGES TO DETECT OBJECT-SPECIFIC CHANGES. Mu H. Wang, Hai T. Li, Ji. X Zhang ,Jing H. Yang
APPLICATION OF DINSAR AND GIS FOR UNDERGROUND MINE SUBSIDENCE MONITORING. YAN Ming-xing, MIAO Fang, WANG Bao-cun, QI Xiao-ying
THE DETECTION OF SUBSIDENCE AT PERMANENT FROZEN AREA IN QINGHAI-TIBETAN PLATEAU. Z. Li, C. Xie, Q. Chen
RESEARCH ON SURFACE SUBSIDENCE MONITORING WITH INSAR/GPS DATA FUSION IN MINING AREA. ZHANG Ji-chao, SONG Wei-dong, ZHANG Ji-xian, SHI Jin-feng
SEVEN YEARS OF MINING SUBSIDENCE DETECTED BY D-InSAR TECHNIQUE IN FUSHUN CITY, CHINA. Y. L. Chen, X. L. Ding, C. Huang, Z. W. Li
A METHOD ON HIGH-PRECISION RECTIFICATION AND REGISTRATION OF MULTI-SOURCE REMOTE SENSING IMAGERY. Bin Liu, Guo Zhang, Xiaoyong Zhu, Jianya Gong
STUDY ON TIE POINT SELECTION FOR CO-REGISTRATION OF DIFFERENT RESOLUTION IMAGERY. Zhen Xiong, Yun Zhang
THE STUDY OF SPACE INTERSECTION MODEL BASED ON DIFFERENT-SOURCE HIGH RESOLUTION RS IMAGERY. Weixi Wang, Qing Zhu
AN OPTIMIZATION HIGH-PRECISION REGISTRATION METHOD OF MULTI-SOURCE REMOTE SENSING IMAGES. LIN Yi, JIAN Jianfeng , ZHANG Shaoming, XIE Feng
A METHODOLOGY OF LUCC CHANGE DETECTION BASED ON LAND USE SEGMENT. Ning Shu, Hong Zhang, Xue Li, Yan Wang
APPLICATION OF MULTI-TEMPORAL TM (ETM+) IMAGE IN MONITORING MINING ACTIVITIES AND RELATED ENVIRONMENT CHANGES: A CASE STUDY AT DAYE, HUBEI, CHINA. Shiyong YU, Zhihua CHEN, Yanxin WANG
LAND COVER CHANGE AND CLIMATIC VICISSITUDE RESEARCH IN HEADSTREAM REGIONOF YELLOW RIVER IN THE NINETIES OF THE TWENTIETH CENTURY. DAI Ji-guang, YANG Tai-bao, REN Jia-qiang
LAND USE CHANGES IN THREE GORGES RESERVOIR AREA IN RECENT 30 YEARS. Sun xiaoxia, Zhang jixian, Liu zhengjun
AUTOMATED VEHICLE INFORMATION EXTRACTION FROM ONE PASS OF QUICKBIRD IMAGERY. Zhen Xiong, Yun Zhang
CLASSIFICATION OF LAND TYPES IN MINERAL AREAS BASED ON CART. Wenbo Wu, Yuping Chen, Jiaojiao Meng, Tingjun Kang
OBJECT-ORIENTED CLASSIFICATION OF HIGH-RESOLUTION REMOTE SENSING IMAGERY BASED ON MRF AND SVM. GU Haiyan, LI Haitao, ZHANG feng, HAN Yanshun, YANG Jinghui
EXTENSIBLE LAND USE AND LAND COVER CLASSIFICATION FRAMEWORK DESIGN BASED ON REMOTELY SENSED DATA. Wang Juanle
THE ROAD EXTRACTION IN THE AREA COVERED WITH HIGH VEGETATION USING THE FUSION IMAGE OF SAR AND TM. Shen Jin-li, Yu Wu-yi, Qi Xiao-ping, Zhang Yi-min
DISCRETE WAVELET-BASED FUSION OF TM MULTI-SPECTRAL IMAGE AND SAR IMAGE DATA. Liang Shouzhen, Li Lanyong
FUSING SAR AND OPTICAL IMAGES BASED ON COMPLEX WAVELET TRANSFORM. Shuai Xing, Qing Xu
A COMPREHENSIVE QUALITY EVALUATION METHOD OF INFORMATION FUSION FROM HIGH-RESOLUTION AIRBORNE SAR AND SPOT5 IMAGES. Wenqing Dong, Qin Yan,
A SIMPLIFIED FUSION METHOD BASED ON SYNTHETIC VARIABLE RATIO. Pang Xinhua, Xi Bin, Chen Luyao, Pan Yaozhong,, Zhuang Wei
A NOVEL IMAGE FUSION METHOD BASED ON 2DPCA IN REMOTE SENSING. Xue-ming Wu, Wu-nian Yang
A METHOD TO DETERMINE SPATIAL RESOLUTION OF REMOTE SENSING FUSED IMAGE QUANTITATIVELY. X. J. Yue, L. Yan, G. M. Huang
A NEW PAN-SHARPENING ALGORITHM AND ITS APPLICATION IN GEOGRAPHIC FEATURES INFORMATION EXTRACTION. ZHU Lijiang
RESEARCH ON THE PROCESS OF LAND USE/COVER CHANGE IN THREE GORGES RESERVOIR AREA IN RECENT 30 YEARS. SHAO Huai-Yong, XIAN Wei, LIU Xue-Mei, YANG Wu-Nian
THE STUDY OF LAND USE CHANGE DETECTION BASED ON SOLE PERIOD RS IMAGE. Song Weidong, Wang Jingxue, Qin Yong
ANALYSIS OF THE LAND USE OF SHENYANG MINING DISTRICT AND ITS DRIVING FORCE. Kaixuan Zhang, Wenbo Wu, Chongchang Wang, Tingjun Kang
REMOTE-SENSING IMAGE COMPRESSION BASED ON FRACTAL THEORY. Chao Mu, Qin Yan, Jie Yu, Huiling Qin
MATRIX DECOMPOSITION AND MATRIX SOLVERS IN PHOTOGRAMMETRY. Cheng Chunquan, Deng Kazhong, Zhang Jixian, YanQin
INVESTIGATING SEVERAL POINT CLOUD REGISTRATION MOTHEDS. Luo Dean, Zhou Keqin, Huang Jizhong
THE ACCURACY ASSESSMENT OF ORTHORECTIFIED ASTER IMAGE. Li Baipeng, Yan Qin, Chen Chunquan
EPIPOLAR RESAMPLING OF DIFFERENT TYPES OF SATELLITE IMAGERY. Jiaying Liu, Guo Zhang, Deren Li
REFINEMENT AND EVALUATION OF BEIJING-1 ORTHORECTIFICATION BASED ON RFM. Jianming Gong, Xiaomei Yang, Chenghu Zhou, Xiaoyu Sun, Cunjin Xue
LAND COVER CLASSIFICATION BY IMPROVED FUZZY C-MEAN CLASSIFIER. ZHAO Quan-hua, SONG Wei-dong, Bao Yong
RESEARCH ON GRIDDING PROCESSING STRATEGIES OF REMOTE SENSING IMAGE SEGMENTATION BY REGION GROWTH. ZHU Hong-chun, ZHANG Ji-xian, LI Hai-tao, YANG Jing-hui, LIU Hai-ying
TEXTURE ANALYSIS IN INFORMATION EXTRACT IN THE HIGH RESOLUTION RS IMAGES LU Shuqiang
THE STUDY OF REMOTE SENSING IMAGE INFORMATION EXTRACTION TECHNIQUES BASED ON KNOWLEDGE. Wenbo Wu, Jiaojiao Meng, Yuping Chen, Jing Chen
A NEW METHOD OF SIMULATION OF INTERFEROGRAM IMAGE FOR REPEAT-PASS SAR SYSTEM. Jianmin Zhou, Zhen Li, Xinwu Li, Chou Xie
COMPARISON AND IMPROVEMENT OF POSITION METHODS OF AIRBORNE STEREO SAR IMAGES. H. D. Fan, K. Z. Deng, G. M.Huang, Z. Zhao., X. J. Yue, X. M. Luo, Y. F. Ling
STUDY ON TOPOGRAPHIC MAP UPDATING WITH HIGH RESOLUTION AIRBORNE SAR IMAGE. X .M. Luo, G. M. Huang, Z. Zhao
AN EXPERIMENT OF HIGH RESOLUTION SAR IMAGE IN DYNAMIC MONITORING THE CHANGE OF CONSTRUCTION LAND. CaoYinxuan, Zhang Yonghong, YanQin, ZhaoZheng
RESEARCH ON STATISTICS AND SPATIAL ANALYSIS OF DRAINAGE BASIN'S IMPORTANT GEOGRAPHICAL ELEMENTS. Liu Ping, Liu Jiping, Zhao Rong
THE RESEARCH AND ESTABLISHMENT OF IMAGE DATABASE SYSTEM BASED ON ORACLE. Li Lanyong, Song Weidong, Chen Zhaoliang, Zhao Hongfeng
SITE SELECTION FOR SATELLITE GEOMETRIC TEST RANGE IN CHINA. Xinxin Zhu, Guo Zhang, Qing Zhu, Xinming Tang
ANALYSIS OF IMAGES GEOMETRIC RECTIFICATION FOR QUICKBIRD. WANG Chong-chang , WANG Li-li, Zhang Li, Zhang Kai-xuan, Ma Zhen-li, ZHANG Zhen-yong
RESEARCH ON DYNAMIC SYMBOL BASE. Yang ping, Tang Xinming, Wang Shengxiao, Lei Bing, Wang Huibing
DETERMINATION OF CHLOROPHYLL CONCENTRATION IN THREE GORGES DAM USING CHRIS/PROBA IMAGE DATA. GAI Li-ya, LIU Zheng-jun,ZHANG Ji-xian
RESEARCH ON LAND SANDY DESERTIFICATION WITH REMOTE SENSING -Take Qinghai Lake Areas as an example. Jian Ji, Chen Yuanyuan, Yang wunian, Tang nengfu
METHODS AND APPLICATION OF QUALITY ASSESSMENT FOR REMOTE SENSING IMAGE COMPRESSION. ZHAI Liang, TANG Xinming, ZHANG Guo, ZHU Xiaoyong
ON-ORBIT MTF ESTIMATION METHODS FOR SATELLITE SENSORS. LI Xianbin, JIANG Xiaoguang, Tang Lingli
AUTHOR INDEX
KEYWORDS INDEX
Cover

Full text

137 
X s — X s» X $ (t 1 0 ) 
(6) 
B = B 0 + t(t - t 0 ) 
(4) 
\ a x a i 
L = BX = I rol lift, b 2 
U C 2 
Linearized equation (2) will get the measurement error equation. 
Showed in equation (5). 
V x =A x X-L x 
(5) 
where 
Vx = 
A = 
V .V 
. V 
\ 
L x y 7 Z 
J 
«i» 
a X2 
a il7 
a 2\ 
a 22 
a 217 
_ a 3i 
°22 
^317 
X — [AX S0 ,AY S0 ,AZ S0 ,A(p 0 ,A(O 0 ,AK 0 ,AÀ X) , 
AX° s ,AYs,AZ° s ,A<p 0 ,Aco 0 ,A/c 0 ,AÀ 0 ,AB 0 ,AB 0 ,AO 0 ] t 
where Z, = coordinates matrix of GPS 
B = coordinates matrix of image 
X= conversion coefficient matrix 
For determining the conversion coefficient, there shall be at 
least 3 light points made by the comer reflectors in the SAR 
imagery. 
When more comer reflectors are available, the least square 
estimation algorithm could be used to obtain the conversion 
coefficient. The observation equation and the least square 
estimation are shown in equation (7) and equation (8). 
L = BX + A 
(7) 
There are 17 unknown parameters in equation (5), so 6 GPS 
ground control points needed at least to compute the orbital 
parameters. 
2.2.3 Geometric correction 
Geometric correction of InSAR data could be realized by using 
accurate orbital parameters, but this method cannot meet the 
demand of monitoring the surface subsidence in mining area 
accurately. Generally, it can only used to monitor the surface 
subsidence as a qualitative tool , and cannot achieve 
quantitative degree entirely (Ge, L., et al., 2003). 
Another approach is to deal with InSAR data geometric 
correction with GPS measurements. This work also needs 
comer reflectors or ground permanent scatterers (PSs). Using 
the geodetic coordinates of PSs (which can be obtained by GPS) 
and InSAR imageries’ pixel coordinates, precise InSAR 
geographic coding products could be created. 
The permanent scatterer InSAR (PS-InSAR) technique is an 
advanced InSAR technology (Bürgmann, R., et al., 2006). By 
selecting isolated ground points which exhibit extremely stable 
interferometric phase behavior in a certain period, the new 
approach overcomes most problems such as the resolution, 
temporal and spatial baseline limitations that hindered 
conventional InSAR processing. It has greatly improved the 
accuracy of InSAR to ground deformation monitoring, 
especially in the cities or the places where the rocks are well 
exposed. Sometimes the ground deformation can be measured 
to millimetre level accuracy under certain conditions (Zhang, J., 
et al., 2007). But PS-InSAR technique needs large amount of 
InSAR images, and it can only used to small areas for slow 
surface deformation of mining area generally. 
If the image coordinates of a reflector are assumed to be 
(Irowdcol)j and the corresponding geodetic coordinates is to be 
(G, at>G[ on ), the conversion between them with the same 
projection could be expressed in equation (6). 
where A = observation error vector 
X = (b t PbYb t PL (8) 
where p = £)“' 
Z) A = variance of vector A 
After conversion parameters are obtained, image coordinates 
can be converted one by one. The geometric corrected InSAR 
imagery then could be overlapped with other graphics to make 
detail analysis on the mining-induced surface subsidence. 
2.3 InSAR and GPS data’s interpolation 
Compared with cities, the mining area has a higher speed in 
surface subsidence. The repeated monitoring period (about a 
month) could meet the demand approximately. However, for 
determining the subsidence parameters, the repeat monitoring 
period must be shortened during the active stages of mining 
surface subsidence. In the case, the InSAR data must be 
interpolated with other data. 
As mentioned above, during monitoring mining subsidence, 
InSAR and GPS technology are very strong complementary in 
temporal and spatial domain. Therefore, it is very necessary to 
interpolate the InSAR data with GPS measurements by 
effective means. 
To interpolate InSAR and GPS data (Diao, J., 2005), the 
following steps could be applied. 
Firstly, select the InSAR image that was corrected with GPS 
data as the spatial distribution model, and the GPS data can be 
interpolated in the spatial domain at grid points. Least-square 
adjusted can be used here to get distribution model of 
subsidence deformation from the InSAR and GPS results. Then 
the GPS subsidence original results with the spatial 
interpolation could be obtained.

Cite and reuse

Cite and reuse

Here you will find download options and citation links to the record and current image.

Monograph

METS MARC XML Dublin Core RIS Mirador ALTO TEI Full text PDF DFG-Viewer OPAC

TOC

Chapter

Image

PDF ALTO TEI Full text

Preview 114×150 jpg

Small 780×1024 jpg

Medium 1560×2048 jpg

Master 3928×5156 MASTER

Image fragment

Link to the viewer page with highlighted frame Link to IIIF image fragment

Citation links

Citation links

Monograph

To quote this record the following variants are available:

Here you can copy a Goobi viewer own URL:

Chapter

To quote this structural element, the following variants are available:

Here you can copy a Goobi viewer own URL:

Image

To quote this image the following variants are available:

Here you can copy a Goobi viewer own URL:

Citation recommendation

zhang, jixian. Mapping without the Sun. GITC, 2007.

Please check the citation before using it.

Image manipulation tools

Tools not available

Share image region

Use the mouse to select the image area you want to share.

Please select which information should be copied to the clipboard by clicking on the link:

Link to the viewer page with highlighted frame
Link to IIIF image fragment

Contact

Have you found an error? Do you have any suggestions for making our service even better or any other questions about this page? Please write to us and we'll make sure we get back to you.

Name: (Required)

Last name:

E-mail: (Required)

Message: (Required)

Security question:

What is the first letter of the word "tree"?:

I hereby confirm the use of my personal data within the context of the enquiry made.

Accept:

No Yes