Urban Land-Use Multi-Scale Textural Analysis

Author

Pacifici, F. ; Chini, M. ; Emery, W.J.

Author_Institution

Earth Obs. Lab., Tor Vergata Univ., Rome

Volume

5

fYear

2008

fDate

7-11 July 2008

Abstract

Urban areas are composed of numerous materials arranged by humans in complex ways. A simple building may appear as a complex structure with many architectural details surrounded by gardens, trees, buildings, roads, social and technical infrastructure and many temporary objects, such as cars, buses or daily markets. In this paper, we analyze the effectiveness of 8 textural features (resulting from the Grey Level Co-occurrence Matrix) derived from a 50 cm WorldVieW-1 image of Washington D.C. (U.S.A.). The information extracted from the panchromatic and textural features are fused and processed by a Multi-Layer Perceptron (MPL) neural network producing a land-use map with accuracy above 0.90 in term of K-coefficient.

Keywords

geophysical signal processing; image texture; multilayer perceptrons; neural nets; remote sensing; USA; Washington D.C; WorldVieW-1 image; architectural details; buildings; complex structure; gardens; grey level co-occurrence matrix; land-use map; multilayer perceptron neural network; multiscale textural analysis; panchromatic images; roads; social infrastructure; technical infrastructure; trees; urban land use; Automotive materials; Buildings; Data mining; Humans; Image analysis; Image texture analysis; Multilayer perceptrons; Neural networks; Roads; Urban areas; Multi-scale texture analysis; WorldView-1; urban land-use;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International

Conference_Location

Boston, MA

Print_ISBN

978-1-4244-2807-6

Electronic_ISBN

978-1-4244-2808-3

Type

conf

DOI

10.1109/IGARSS.2008.4780098

Filename

4780098