An Integrated Classification Approach for Remote Sensing Data Incorporating Fuzzy Neural Networks, GIS and GPSUniversity of Wisconsin--Madison, 1997 - 656 pages |
From inside the book
83 pages matching classification results in this book
Where's the rest of this book?
Results 1-3 of 83
Contents
INTEGRATED CLASSIFICATION APPROACH | 92 |
FEASIBILITY TEST OF THE INTEGRATED APPROACH | 116 |
METHODOLOGY | 151 |
5 other sections not shown
Common terms and phrases
actual additional algorithm analysis ancillary data application bands classification accuracy classification method classification results collected combining comparison components computed coordinates correction corresponding cover cover class data set detailed determined discussed effects error estimated experiments Figure final FNN classification Forest format function fuzzy neural network gating network GIS layer Global Positioning System ground cover ground truth data hypothesis implementation improve incorporate input integrated Kappa known learning maps matrix maximum likelihood means measurement method minimal mixture modified multiple classifiers necessary objective observed obtained operator output output information overall parameters pattern performed pixel representation points polygons position probability problem produce proposed approach reference remote sensing representative rules satellite selected significance single spectral statistical study area supporting Table techniques technologies training samples training set types values Variance vector visits Wetland