ABSTRACT
When compared to classical sciences such as math, with roots in prehistory, and physics, with roots in antiquity, geographical information science (GISci) is the new kid on the block. Its theoretical foundations are therefore still developing and data quality and uncertainty modeling for spatial data and spatial analysis is an important branch of t
TABLE OF CONTENTS
part |2 pages
Section I: Overview
part |2 pages
Section II: Modeling Uncertainties in Spatial Data
part |2 pages
Section III: Modeling Uncertainties in Spatial Model
part |2 pages
Section IV: Modeling Uncertainties in Spatial Analyses
part |2 pages
Section V: Quality Control of Spatial Data
part |2 pages
Section VI: Presentation of Data Quality Information
part |2 pages
Section VII: Epilogue