Retrodigitalisierung Logo Vollbild
  • Erstes Bild
  • Vorheriges Bild
  • Nächstes Bild
  • Letztes Bild
  • Doppelseitenansicht
Wählen Sie mit der Maus den Bildbereich, den Sie teilen möchten.
Bitte wählen Sie aus, welche Information mit einem Klick auf den Link in die Zwischenablage kopiert werden soll:
  • Link zur Seite mit Hinweisbox im Bild
  • Link zu einem IIIF Bildfragment

Mapping without the sun

Zugriffsbeschränkung

Keine Zugriffsbeschränkung.

Nutzungslizenz

Der Status des Urheberrechts und der verwandten Schutzrechte für diesen Datensatz wurde nicht geprüft oder ist unklar. Bitte wenden Sie sich für weitere Informationen an die Organisation, die das Objekt zur Verfügung gestellt hat.

Bibliografische Daten

fullscreen: Mapping without the sun

Monographie

Persistenter Identifier:
856578517
Autor:
Zhang, Jixian
Titel:
Mapping without the sun
Untertitel:
techniques and applications of optical and SAR imagery fusion ; Chengdu, China, 25 - 27 September 2007
Umfang:
1 Online-Ressource (III, 352 Seiten)
Erscheinungsjahr:
2007
Erscheinungsort des Originals:
Lemmer
Verlag des Originals:
GITC
Identifier (digital):
856578517
Illustrationsangabe:
Illustrationen, Diagramme, Karten
Sprache:
Englisch
Verlag des Digitalisats:
Technische Informationsbibliothek Hannover
Erscheinungsort des Digitalisats:
Hannover
Erscheinungsjahr des Digitalisats:
2016
Dokumenttyp:
Monographie
Sammlung:
Geowissenschaften

Kapitel

Titel:
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
Dokumenttyp:
Monographie
Strukturtyp:
Kapitel

Inhaltsverzeichnis

Inhalt

  • Mapping without the sun
  • Einband
  • Farbkeil
  • Titelseite
  • 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
  • Einband

Volltext

177 
NOAA AVHRR data is relatively low, to obtain higher 
categorized area precision, and it needs to use the pixel 
unmixing method to make the precision of pixel classifications 
reach the level of the sub-pixel. 
Fig.4 Structure of BP Neural Network 
Up to now, the methods of the remote sensing image 
classifications include the traditional supervising classification 
(such as the parallel algorithm, the minimum distance 
algorithm and the maximum likelihood method), 
ISODATA( iterative self-org-anizing data analysis technique) 
not supervising classification, the latest fuzzy classification, 
expert system classification and neural network 
classification(Sun Hong-yu et al,2003). Furthermore, the pixel 
unmixing method includes message extracting methods for sub 
pixel imaging based on linear models, geometrical optics model, 
geometirc model at random, probability model, fuzzy model, 
etc. 
BP neural network is a neural network model adopting the back 
propagation learning algorithm. Nowadays it is applied on 
many fields. The application of images classification and pixel 
unmixing method also make heavy effect(Wang Xi-peng et 
al, 1998). A typical BP neural network is made up of three 
neuron layers, which are the input layer, the output layer and 
the implicating layer (as shown in Fig. 4). 
This text on the basis of NDVI data and the third band AVF1RR 
data with the elevation data of the Yellow River source and the 
temperature precipitation data as the input of BP neural 
network, and the auto-correlation characteristics of 
geographical space and geography experts knowledge and field 
measuring data as the training reference of BP nerve network, 
presents some exercises on the image classification of the 
neural networks and the pixel unmixing function, and 
demonstrates the classifying process of the land cover type of 
the Yellow River source. Among them, the selection of the land 
cover type consults the description of the land cover type of 
Qinghai-Tibet Plateau made by Zhengyi Wu. Finally, we obtain 
the categorized result of the land cover type of the Yellow 
River source in 1990- 2000 years, as shown in Table 2. 
The value region of NDVI reflects the whole trend of area 
changes of land coverage. Also in the table 2 the changes of 
area of land coverage are very distinct. Among which the area 
of all kinds of meadow types show the distinctly decreasing 
trend while the desert type shows increasing tend. However, the 
changes of area of grassland and desert grassland in different 
altitude are different. The area of alpine grassland and the 
representative grassland decreased while the ones of alpine 
desert and alpine grassland, alpine desert, subalpine grassland 
and subalpine desert grassland show the increasing trend. The 
area of desert grassland in lower altitude did not change too 
much. 
Tablet 3 is the correlation modulus between the changes of land 
coverage and the changes of climate factors. The tablet shows 
that there is strong negative relation between the land coverage 
of alpine meadow, alpine grassland, subalpine meadow, 
meadow and grassland and annual average temperature and 
annual highest temperature. While between the area of alpine 
grassland and desert grassland, alpine desert, subalpine desert 
grassland, subalpine desert and desert and the annual average 
temperature and annual highest temperature, there exists a 
strong positive correlation. It suggests that the increasement of 
temperature is a very important inducement of meadow 
degeneration. However, the strong positive correlation between 
annual average temperature and annual highest temperature and 
the area of subalpine grassland indicates the increase of 
temperature accelerates the growth of the vegetation in 
subalpine area. 
The relations between precipitation and the different land 
coverageage type are not accordant. The coverage area of 
meadow shows great negative correlation with precipitation 
which indicates the more precipitation could lessen the value of 
NDVI. While between alpine grassland, subalpine grassland, 
steepe and precipitation, there is a positive correlation which 
suggests the increase of precipitation could improve the 
environment of vegetation growth in normal coverage land. 
Meanwhile, all types of desert area have a weak negative 
correlation with precipitation which indicates that including 
temperature the decrease of precipitation also promote land 
desertification.
	        

Zitieren und Nachnutzen

Zitieren und Nachnutzen

Hier finden Sie Downloadmöglichkeiten und Zitierlinks zu Werk und aktuellem Bild.

Monographie

METS MARC XML Dublin Core RIS Mirador ALTO TEI Volltext PDF DFG-Viewer OPAC
TOC

Kapitel

PDF RIS

Bild

PDF ALTO TEI Volltext
Herunterladen

Bildfragment

Link zur Seite mit Hinweisbox im Bild Link zu einem IIIF Bildfragment

Zitierlinks

Zitierlinks

Monographie

Um dieses Werk zu zitieren, stehen die folgenden Varianten zur Verfügung:
Hier kann eine Goobi viewer eigene URL kopiert werden:

Kapitel

Um dieses Strukturelement zu zitieren, stehen die folgenden Varianten zur Verfügung:
Hier kann eine Goobi viewer eigene URL kopiert werden:

Bild

Um dieses Bild zu zitieren, stehen die folgenden Varianten zur Verfügung:
Hier kann eine Goobi viewer eigene URL kopiert werden:

Zitierempfehlung

zhang, jixian. Mapping without the Sun. GITC, 2007.
Bitte das Zitat vor der Verwendung prüfen.

Werkzeuge zur Bildmanipulation

Werkzeuge nicht verfügbar

Bildausschnitt teilen

Wählen Sie mit der Maus den Bildbereich, den Sie teilen möchten.
Bitte wählen Sie aus, welche Information mit einem Klick auf den Link in die Zwischenablage kopiert werden soll:
  • Link zur Seite mit Hinweisbox im Bild
  • Link zu einem IIIF Bildfragment

Kontakt

Haben Sie einen Fehler gefunden, eine Idee wie wir das Angebot noch weiter verbessern können oder eine sonstige Frage zu dieser Seite? Schreiben Sie uns und wir melden uns sehr gerne bei Ihnen zurück!

Wie viele Buchstaben hat "Goobi"?:

Hiermit bestätige ich die Verwendung meiner persönlichen Daten im Rahmen der gestellten Anfrage.