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The 3rd ISPRS Workshop on Dynamic and Multi-Dimensional GIS & the 10th Annual Conference of CPGIS on Geoinformatics

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fullscreen: The 3rd ISPRS Workshop on Dynamic and Multi-Dimensional GIS & the 10th Annual Conference of CPGIS on Geoinformatics

Monograph

Persistent identifier:: 856566209

Author:: Chen, Jun

Title:: The 3rd ISPRS Workshop on Dynamic and Multi-Dimensional GIS & the 10th Annual Conference of CPGIS on Geoinformatics

Sub title:: May 23 - 25, 2001, Bangkok, Thailand

Scope:: VI, 434 Seiten

Year of publication:: 2001

Place of publication:: Pathumthani, Thailand

Publisher of the original:: AIT

Identifier (digital):: 856566209

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

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:: THE APPLICATION OF NEURAL NETWORK AND FUZZY SET TO CLASSIFICATION OF REMOTELY SENSED IMAGERY. Dongmin HUO, Jingxiong ZHANG, Jiabing SUN

Document type:: Monograph

Structure type:: Chapter

Contents

Table of contents

The 3rd ISPRS Workshop on Dynamic and Multi-Dimensional GIS & the 10th Annual Conference of CPGIS on Geoinformatics
Cover
ColorChart
Title page
PREFACE
Conference Venue
CONTENTS
DISTRIBUTION ANALYSIS AND AUTOMATIC GENERALIZATION OF URBAN BUILDING CLUSTER. Tinghua AI
GENERALIZATION FOR 3D GIS. Fengwen BAI, Xiaoyong CHEN
USING IKONOS HIGH RESOLUTION REMOTE SENSING DATA FOR LAND USE CLASSIFICATION IN CHINA. Georg BARETH
LARGE SCALE GIS FOR A SUBURBAN TOWNSHIP OF BEIJING TO MODEL STRATEGIES FOR SUSTAINABLE AGRICULTURE ON FIELD LEVEL. Georg BARETH, Si JIN, Tailai YAN and Reiner DOLUSCHITZ
THREE LEVEL HIERARCHICAL QUALITATIVE DESCRIPTIONS FOR DIRECTIONS OF SPATIAL OBJECTS. Han CAO, Jun CHEN, Daosheng Du
THE APPLICATION OF CENTROGRAPHIC ANALYSIS TO THE STUDY OF THE INTRA-URBAN MIGRATORY PHENOMENON IN THE GREATER MONCTON AREA IN CANADA, 1981-1996. Huhua CAO
PER-FIELD CLASSIFICATION INTEGRATING VERY FINE SPATIAL RESOLUTION SATELLITE IMAGERY WITH TOPOGRAPHIC DATA. Mauro CAPRIOLI, Eufemia TARANTINO
INTEGRATION OF GIS WITH PESTICIDES LOSSES RUNOFF MODEL. Bing CHEN, Gordon HUANG, Jonathan LI, Yueren LI, and Yifan LI
RESEARCH ON 3D CITY VISUALIZATION BASED ON INTERNET. Jing CHEN, Qingquan Ll, Jianya GONG, Bisheng YANG
DYNAMIC AND MULTI-DIMENSIONAL GIS: AN OVERVIEW. Jun CHEN, Zhilin LI, Jie JIANG
A GIS-SUPPORTED ENVIRONMENTAL RISK ASSESSMENT FOR PETROLEUM WASTE CONTAMINATED SITE. Su Chen, Gordon Huang, and Jonathan Li
MEASURING UNCERTAINTY IN SPATIAL FEATURES IN A THREE-DIMENSIONAL GEOGRAPHICAL INFORMATION SYSTEM. Chui Kwan CHEUNG and Wenzhong SHI
SPATIAL DEVELOPMENT RESEARCH OF LARGE CITY BASED ON GIS SPATIAL ANALYSIS. Anrong DANG, Qizhi MAO, Xiaodong WANG
DIGITAL CLOSE RANGE PHOTOGRAMMETRY: A POTENTIAL TOOL FOR LAND FEATURE PRESENTATION. Gang DENG
3D SPATIAL OBJECTS MODELING AND VISUALIZATION BASED ON LASER LANGE DATA. Jie DU, Apisit EIUMNOH, Xiaoyang CHEN, Michiro KUSANAGI
3D REPRESENTATION AND SIMULATION OF MINING SUBSIDING LAND BASED ON GIS, DPS AND GPS. Peijun DU, Dazhi GUO and Qihao WENG
USE DSM/DTM TO SUPPORT CHANGE DETECTION OF BUILDING IN URBAN AREA. Hong FAN, Jianqing ZHANG, Zuxun ZHANG, Zhifang LIU
ENHANCE MANAGEMENT LEVEL OF URBAN WATER SUPPLY DEPARTMENT WITH 3S TECHNOLOGY. Yewen FAN and Wei WANG
AUTOMATIC REGISTRATION OF SATELLITE IMAGE TO MAP. Kensaku FUJII
DIFFERENTIAL SATELLITE POSITIONING OVER INTERNET. Ying. GAO and Zhi. LIU
FEDERATED SPATIAL DATABASES AND INTEROPERABILITY. Jianya GONG, Yandong WANG
OPTIMIZING PATH FINDING IN VEHICLE NAVIGATION CONSIDERING TURN PENALTIES AND PROHIBITIONS. Gang HAN, Jie JANG, Jun CHEN
DEVELOPMENT OF DYNAMIC MANAGEMENT SPATIAL-TEMPORAL INFORMATION SYSTEM AND APPLICATION FOR CENSUS DATA- TOWARD ASIAN SPATIAL TEMPORAL GIS (ST-GIS) (2)-. Michinori HATAYAMA, Shigeru KAKUMOTO, Hiroyuki KAMEDA
MODELING LAND USE EFFECT ON URBAN STORM RUNOFF AT THE WATERSHED SCALE. Chansheng HE
EXTRACTION OF THE SEA OIL INFORMATION FROM TM AND AVHRR IMAGE BY THE METHOD OF FEATURE DATA LINE -WINDOW. Fengrong HUANG
THE APPLICATION OF NEURAL NETWORK AND FUZZY SET TO CLASSIFICATION OF REMOTELY SENSED IMAGERY. Dongmin HUO, Jingxiong ZHANG, Jiabing SUN
A SELF-ADAPTIVE ALGORITHM OF AUTOMATIC INTERIOR ORIENTATION FOR METRIC IMAGES. Wanshou JIANG, Guo ZHANG, Deren LI
DETECTION OF SHEER CHANGES IN AERIAL PHOTO IMAGES USING AN ADAPTIVE NONLINEAR MAPPING. Yukio KOSUGI, Munenori FUKUNISHI, Mitsuteru SAKAMATO, Wei LU and Takeshi DOIHARA
EFFECTIVENESS OF MENU-DRIVEN VS. SCRIPT-BASED GIS TUTORIAL SYSTEMS. Bin LI
BUILDING OF B/S-BASED OBJECT ORIENTED ELECTRONIC CHART DATABASE. Guangru LI, Shaopeng SUN, Depeng ZHAO
MINE GIS 3D DATA MODEL AND SOME THINKING. Q. Y. LI, D. Y. CAO, X. D. ZHU
THE RESEARCH OF THE INFINITELY VARIABLE MAP SCALE IN GIS. Yifan LI, Shaopeng SUN
RESEARCH ON INFORMATION AUTOMATIC GENERALIZATION WITH VARYING MAP SCALE. Yuanhui LI, Dan LIU, Yifan LI
QUANTITATIVE MEASURES FOR SPATIAL INFORMATION OF MAPS. Zhilin LI and Peizhi HUANG
AN ALGEBRA FOR SPATIAL RELATIONS. Zhilin LI, Renliang ZHAO and Jun CHEN
A STUDY ON THE EXTRACTION OF DEM FROM SINGLE SAR IMAGE. Mingsheng LIAO, Jie YANG, Hui LIN
A GIS-BASED ENVIRONMENTAL DECISION SUPPORT SYSTEM FOR THE ERHAI LAKE WATERSHED MANAGEMENT. Lei LIU, Gordon HUANG, and Jonathan LI
APPLICATION OF 4D AND ASSOCIATED ENABLING TECHNOLOGIES FOR URBAN DECISION SUPPORT SYSTEM. Rong LIU, Penggen CHENG, Zhuguo XING, Kaiyun LU
3D RECONSTRUCTION OF A BUILDING FROM SINGLE IMAGE. Yawen LIU, Zuxun ZHANG, Jianqing ZHANG
AN INTELLIGENT GIS SEARCH ENGINE TO RETRIEVE INFORMATION FROM INTERNET. Zhe LIU, Yong GAO
AN ENHANCED TIN GENERATION METHOD FOR USING CONTOUR LINE AS CONSTRAINS. Wei LU, Takeshi DOIHARA
NON-LINEAR RECTIFICATION OF MAP WITH COLLINEAR CONSTRAIN. Wei LU, Takeshi DOIHARA
A STUDY ON VEHICLE POINT CORRECTING ALGORITHM IN GPS/AVL SYSTEMS. HongShan NIU, Jie XU, Hong LI
A SPATIO-TEMPORAL GEOGRAPHIC INFORMATION SYSTEM BASED ON IMPLICIT TOPOLOGY DESCRIPTION: STIMS. Yutaka OHSAWA, Atushi NAGASHIMA
APPLICATION OF VRML IN A DYNAMIC AND MULTI-DIMENSIONAL DIGITAL HARBOR. Mingyang PAN, Yifan LI, Depeng ZHAO
A COMMON DATA MODEL AND REQUESTING LANGUAGE FOR SPATIAL INFORMATION MARKETPLACES. Matthew Y. C. PANG, Wenzhong SHI, Geoffrey SHEA
TOPOLOGIC DATA STRUCTURE FOR A 3D GIS. Mattias Pfund
AUTOMATIC RECOGNITION AND LOCATION OF ROAD SIGNS FROM TERRESTERIAL COLOR IMAGERY. Sompoch PUNTAVUNGKOUR, Xiaoyang CHEN, Michiro KUSANAGI
A NEW STEREO MATCHING APPROACH USING EDGES AND NONLINEAR MATCHING PROCESS OBJECTED FOR URBAN AREA. Mitsuteru SAKAMOTO, Wei LU, Pingtao WANG
MINING SEQUENTIAL PATTERN FROM GEOSPATIAL DATA. Yin SHAN
THE ADVANCED GIS AND GPS TECHNOLOGIES TO BE USED IN THE LANCHANG BASIN AREA OF YUNNAN PROVINCE OF CHINA. Kun SHI
PRIMARY SPATIAL CHANGES. Hong SHU, Christopher GOLD and Jun CHEN
INCORPORATING 3D GEO-OBJECTS INTO AN EXISTING 2D GEO-DATABASE: AN EFFICIENT USE OF GEO-DATA. Jantien STOTER, Peter VAN OOSTEROM
A FRAMEWORK FOR AUTOMATED CHANGE DETECTION SYSTEM. Haigang SUI, Deren LI, Jianya GONG
BUILDING DISTRIBUTED GEOGRAPHIC INFORMATION SYSTEM FOR OCEAN TRANSPORTATION (GIS-OT). Shaopeng SUN, Guangru LI, Depeng ZHAO
COMPUTATION OF ACCURACY ASSESSMENT IN THE INTEGRATION OF PHOTOGRAPH AND LASER DATA. Taravudh TIPDECHO & Xiaoyong CHEN
PROXIMITY AND ACCESSIBILITY TO SUITABLE JOBS AMONG WORKERS OF VARIOUS WAGE GROUPS. Fahui WANG
WEB MAPPING WITH GEOGRAPHY MARKUP LANGUAGE. Xingling WANG, Chongjun YANG, Donglin LIU
INTEGRATION OF COMPACTNESS MEASUREMENT METHODS USING FUZZY MULTICRITERIA DECISION MAKING : A NEW APPROACH FOR COMPACTNESS MEASUREMENT IN SHAPE BASED REDISTRICTING ALGORITHM. Yinchai WANG
GIS-BASED SYSTEM FOR RAINFALL ESTIMATION USING RAINGAUGE DATA: A PROTOTYPE. Yinchai WANG, Teck Kiong SIEW
A NEW APPROACH FOR DISTRIBUTED GIS. Yuxiang WANG, Chongjun YANG, Donglin LIU
GEOD2D: A FLEXIBLE SOLUTION FOR GIS DATA EXCHANGE BASED ON COM. Huayi WU, Xinyan ZHU
GEOLOGICAL DATA ORGANIZATION FOR FEM BASED ON 3D GEOSCIENCE MODELING. Lixin WU, Enke HOU, Chunan TANG
DIGITAL MODEL AND GPS BASED PATH REPRESENTATION AND OPTIMIZATION. Linyuan XIA
AN COMPOSITE TEMPORAL DATA MODEL IN CADASTRAL INFORMATION SYSTEM. Changsheng XUE, Qingquan LI, and Bisheng YANG, Yuanchun HUA, Shiwu XU
A SPATIAL-TEMPORAL DATA MODEL FOR MOVING AREA PHENOMENA. Shanzhen Yl, Yong ZHONG, Lizhu ZHOU, Jun CHEN, Qilun LIU
CONSTRUCTION OF 3D MODELS FOR ELEVATED OBJECTS IN URBAN AREAS USING AIRBORNE SAR POLARIMETRIC DATA. Yalkun YUSUF, Masashl MATSUOKA, Fumio YAMAZAKI, Seiho URATSUKA, Tatsuharu KOBAYASHI, Makoto SATAKE
COASTAL GIS: FUNCTIONALITY VERSUS APPLICATIONS. Thomas Q ZENG, Qiming ZHOU, Peter COWELL and Haijun HUANG
CIS AIDED CHARACTERIZATION OF SOIL AND GROUNDWATER ARSENIC CONTAMINATION IN SOUTHERN THAILAND. Jianjun ZHANG, Xiaoyong CHEN, Preeda PARKPIAN, Monthip Sriratana TABUCANON, Janewit WONGSANOON, Kensuke FUKUSHI, Skorn MONGKOLSUK and N.C.THANH
MULTIRESOLUTION TERRIAN MODEL. Jin ZHANG
A TROUS WAVELET DECOMPOSITION APPLIED TO DETECTING IMAGE EDGE. Xiaodong ZHANG, Deren LI
RESEARCH OF THE LAND MANAGEMENT INFORMATION SYSTEM BASED ON WEB GIS AND SPATIAL DATABASES FOR PROVINCIAL AND LOCAL GOVERNMENTS IN CHINA. Junsan ZHAO, Yaolong ZHAO, Qiaogui ZHAO and Tao WEI
ANALYSING BRANCH BANK CLOSURES USING GIS AND THE SMART MODEL. Lihua ZHAO, Barry J. GARMER
QTM-BASED ALGORITHM FOR THE GENERATING OF VORONOI DIAGRAM FOR SPHERICAL OBJECTS. Xuesheng ZHAO, Jun CHEN
MODELING AND LANDSCAPE OF HIGHWAY CAD. Jiaqing ZHENG, Xi’an ZHAO, Chujiang CHEN
ASSISTING THE DEVELOPMENT OF KNOWLEDGE FOR PREDICTIVE MAPPING USING A FUZZY C-MEANS CLASSIFICATION. A-Xing ZHU, Edward ENGLISH
THE DESIGN AND IMPLEMENTATION OF CYBERCITY GIS (CCGIS). Qing ZHU, Deren LI, Yeting ZHANG, Hanjiang XIONG
3D COMPUTER SIMULATION OF ANCIENT CHINESE TIMBER BUILDINGS. Yixuan ZHU, Jie YANG, Deren LI
3D MODELLING FOR AUGMENTED REALITY. Siyka ZLATANOVA
THE DESIGN OF SPATIAL DATA WAREHOUSE. Yijiang ZOU
AUTHOR INDEX
Cover

Full text

ISPRS, Vol.34, Part 2W2, "Dynamic and Multi-Dimensional GIS”, Bangkok, May 23-25, 2001 
139 
and with different precision. 
The difference between the training samples and the export 
from the net produces error, which can be gradually decreased 
by means of repeating iteration and finally calculating the 
solution in the training process. The error indicates the coming 
classification accuracy of a NN classifier at least indirectly. 
Obviously, the other accuracy indexes can be easily calculated 
after every time of iteration. Besides, the accuracy of the net that 
is underway or has been trained can be evaluated through 
another group of independent checking samples. They may be 
fuzzy and the evaluation of accuracy may be nearly real-time. 
From the above, a fully fuzzy supervised process may be 
realized by means of the NN method. It can theoretically 
describe any nonlinear relation and have the capability of 
learning and generalization. It can also get used to the dynamic 
change of the learning environment by renewing to learn. 
Therefore, it is a good choice to realizing the fully fuzzy 
classification by means of the NN method. 
TEST 
In order to prove the property of the study, we take a small 
scene of Landsat TM image as the test data. Its pixel size is 30 
meters. It is located in the Delta of the Yellow River in China. It is 
suitable for the test field of fuzzy classification for its land cover 
types interpolating mutually. According to the practical conditions, 
the system of image classification in the test is classified into 
seven types, namely arbor tree, bush, grassland, reed, dry land, 
paddy field and water. After visual interpretation, The bands 3, 4 
and 5 are selected as the original data for practical classification 
in order to simplify the latter management. The rectification of 
the image is performed according to the coordinates of a group 
of easily identified ground features from a map, such as the 
crossing of roads, corners of huge building structure. 
Table 1. The Classification results by Non-fuzzy (N) and Fully Fuzzy (F) Methods 
r ' ' 1 11 1 IU ' , - 1 - 1 i,J - ■ 
Training 
Classification 
Accuracy evaluation 
Classification 
method 
Mode 
Pixel 
number 
Iteration 
number 
Pixel 
number 
mode 
Pixel 
number 
Classification 
accuracy(%) 
Cross 
-entropy ! 
Maximum probability 
N 
416 
1 
1566 
N 
1566 
38 
- 
: j 
NN 
N 
143 
5567 
1709 
N 
1566 
51 
: 
Fully fuzzy NN 
F 
80 
5186 
1709 
F 
1629/96 
45.6/57.3 
0.456 
(Note: The data under the diagonal is acquired from the crispy pixels) 
For the purpose of comparison, the routine maximum 
probability method is taken for image classification at first. The 
appropriately distributing and representative pixels are used for 
its training. The sample pixel numbers of arbor tree, bush, 
grassland, reed, dry land, paddy field and water are respectively 
55, 60, 53, 63, 45,58,56 and 26. The result of classification is 
listed in table 1. 
After repeating experiments, the NN classifier designed by 
this paper is a net structure including 3 nodes in import layer, 10 
nodes in hide layer and 7 nodes in export layer. Its selected step 
length of learning is 0.1 and its momentum parameter is 0.1. 
Using the traditional method, the NN training is performed by 
means of equably distributing and more representative crispy 
pixels as samples. They include 25 arbor tree classes, 30 bush 
classes, 15 grassland classes, 22 reed classes, 18 dry land 
classes, 28 paddy field classes and 5 water classes. Next, the 
classification is performed by the fully fuzzy NN method. The 
training of the net is based on a fuzzy sample having 80 pixels 
totally. The sample pixel numbers of arbor tree, bush, grassland, 
reed, dry land, paddy field and water are respectively 15, 15, 13, 
13, 12,10 and 2. They are all selected from the fuzzy reference 
data layer by computer at random, which have different affiliation 
degrees between 0 and 1. The fuzzy reference data layer can be 
acquired from the aerial photo covering the same area by means 
of geostatistical method. Except for the training samples, all the 
pixels are used to evaluate the classification accuracy. From the 
table 1, it can be seen that the training samples of the maximum 
probability method are biggest and its accuracy is lowest. 
Generally speaking, the accuracy of the NN classification is 
higher than the accuracy of the fully fuzzy NN classification. But 
the former one need more training samples, which are 
comparably crispy. It is a over-strict request in the fuzzy 
phenomenon. As a whole, the result of the fully fuzzy NN 
classification is best. 
CONCLUSIONS 
From the table 1, we can see that the whole accuracy of 
classification is not good enough. It is the fuzziness of the land

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