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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:: ASSISTING THE DEVELOPMENT OF KNOWLEDGE FOR PREDICTIVE MAPPING USING A FUZZY C-MEANS CLASSIFICATION. A-Xing ZHU, Edward ENGLISH

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-Dimensionai GIS", Bangkok, May 23-25, 2001
399
ASSISTING THE DEVELOPMENT OF KNOWLEDGE FOR PREDICTIVE MAPPING USING
A FUZZY C-MEANS CLASSIFICATION
A-Xing ZHU 12 Edward ENGLISH 1
’Department of Geography
University of Wisconsin
550 North Park Street
Madison, Wisconsin 53706
Tel: (608) 262-0272
Fax: (608) 265-3991
Email: axina@aeoqraphv.vvisc.edu
State Key Lab of Resources and Environmental Information System
Institute of Geography
Chinese Academy of Sciences
Beijing 100101, China
Keywords: Fuzzy Set, Geographic Information System, Soil Mapping, Expert System, Case-Based Reasoning
Abstract
Knowledge of relationships between a given geographic phenomenon and its observable environmental factors is needed for mapping
geographic phenomena/features which cannot be directly observed, for example, soils, habitat potential. The knowledge is often
developed through extensive fieldwork which is not only very labor intensive and slow, but also very costly. Methods are needed to
assist local domain experts to acquire this knowledge efficiently. This paper presents an approach based on fuzzy c-means
classification to assist the development of local domain experts’ knowledge of the relationships. The method is based on the assumption
that the observable environmental factors have dominant impact on the distribution of the given geographic phenomenon and that
unique environmental configurations reflect the unique status or properties of the geographic phenomenon. Under this assumption,
clusters in the environmental space (parameter space) are directly related to different types (status) of the given phenomenon. We
employed a fuzzy c-means classification to identify the natural clusters in the environmental space and use the centroids of these fuzzy
clusters as a guide to allocate field investigation efforts for developing knowledge on relationships between environmental factors and
the phenomenon to be mapped. Through a soil mapping case study, we found the approach is effective in helping local soil scientists to
develop their understanding (knowledge) of soil-environmental relationships in areas the local soil experts are not familiar with the
relationships. The soil map derived using the understandings achieved over 76% accuracy overall, compared to about 60% accuracy
through the extensive fieldwork. For areas with a good environmental gradient, the accuracy is over 90% while the accuracy for area
with little relief is about 63%.
1. Introduction
Predictive mapping, such as soil mapping and habitat potential
mapping, uses observable environmental conditions to predict
the spatial distribution of the geographic phenomenon to be
mapped. Predictive mapping requires the knowledge of the
relationships between the phenomenon and the observable
environmental conditions. This knowledge is often developed
through extensive fieldwork. For example, with conventional
soil mapping, extensive field campaign is required for local soil
scientists to develop the knowledge on how the soils in an
area are related to the observable environmental conditions
(such as elevation, slope gradient). Once the understanding of
relationships has been developed through the campaign, the
local soil scientists will then delineate the spatial distribution of
soils based on the knowledge of the relationships and the
observable environmental conditions.
Field campaigns for natural resource surveys are often very
labor intensive, time consuming, and costly. Although field
scientists may employ statistical sample strategies (such as
random sampling, regular grid sampling, or stratifying
sampling), their field efforts may still not be effectively directed
due to the repeated spatial patterns and the gradation of the
phenomenon/feature. The layout of field investigation is often
dependent on the experience of individual field experts. For
example, some field scientists may be able to avoid transition
areas and distill the major relationships very quickly while
others may spend a lot of time in the transitional areas and
was not able to quickly capture the major relationships. As a
result, the development of knowledge on the relationships is
often very slow and the accumulated knowledge is often very
subjective.
Methods are needed to assist field scientists to quickly identify
the key areas for developing the relationships. This paper
investigates the use of an unsupervised fuzzy classification
technique to identify areas of unique environmental niches
from those areas of environmental transition. Using the results
from the fuzzy classification field investigation efforts are
directed towards areas of unique environmental niches to
discover relationships between these niches and the
geographic phenomena to be mapped.
The next section of this paper describes our method. Section 3
shows a case study using this method. Summaries are given
in Section 4.
2. Methodology
2.1 The Basis:
The underlying assumption behind predictive mapping is that
there is a relationship between the geographic phenomenon to
be mapped and its observable environmental conditions. We
further assume that the unique status of the given geographic
phenomenon (such as different types of soils) is created under
unique combinations of environmental conditions. Under this
assumption, the spatial locations of the geographic
phenomenon with unique status can be approximated by the
locations of unique combination of environmental conditions.
Thus, discovering the relationships between the geographic
phenomenon and its environmental conditions is a matter of
finding which unique combination of environmental conditions
is related to which unique status (types) of the phenomenon.
Relating unique status of a given geographic phenomenon to
unique combination of environmental conditions requires field
investigation. Due to the repetition of spatial patterns and
graduation of geographic phenomenon, locating the unique
combination of environmental conditions is still very
challenging. The efficiency of field investigation can be greatly
improved if we can first identify the spatial locations of these

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