Hierarchical classification of complex landscape with VHR pan-sharpened satellite data and OBIA techniques-Reference-Cited by-同舟云学术

Hierarchical classification of complex landscape with VHR pan-sharpened satellite data and OBIA techniques

Published:2014-01 Issue:1 Volume:47 Page:229-250
ISSN:2279-7254
Container-title:European Journal of Remote Sensing
language:en
Short-container-title:European Journal of Remote Sensing

Author:

Gianinetto Marco¹,Rusmini Marco²,Candiani Gabriele³,Via Giorgio Dalla¹,Frassy Federico¹,Maianti Pieralberto¹,Marchesi Andrea¹,Nodari Francesco Rota¹,Dini Luigi⁴

Affiliation:

1. Laboratory of Remote Sensing (L@RS), Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Via Ponzio 31, 20133, Milano, Italy

2. ERM Italia S.p.A., Via San Gregorio 38, 20124, Milano, Italy

3. Institute of Electromagnetic Sensing of Environment (IREA), Italian National Research Council (CNR), Via Bassini 15, 20133, Milano, Italy

4. Cosmo Sky Med-CIDOT Center for the Interpretation of Earth Observation Data, Italian Space Agency, Space Geodesy Center “G.Colombo”, C/da Terlecchia, c.p. 11, 75100, Matera, Italy

Publisher

Informa UK Limited

Subject

Applied Mathematics,Atmospheric Science,Computers in Earth Sciences,General Environmental Science

Link

https://www.tandfonline.com/doi/pdf/10.5721/EuJRS20144715

Reference51 articles.

1. GeoEye-1 and WorldView-2 pan-sharpened imagery for object-based classification in urban environments

2. Fine Spatial Resolution Simulated Satellite Sensor Imagery for Land Cover Mapping in the United Kingdom

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4. Per-pixel and object-oriented classification methods for mapping urban features using Ikonos satellite data

5. Object based image analysis for remote sensing

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