Title :
Integration of COSMO-SkyMed and GeoEye-1 Data With Object-Based Image Analysis
Author :
Gianinetto, M. ; Rusmini, M. ; Marchesi, A. ; Maianti, P. ; Frassy, F. ; Dalla Via, G. ; Dini, L. ; Nodari, F. Rota
Author_Institution :
Dept. of Archit., Built Environ., & Constr. Eng. (ABC), Politec. di Milano, Milan, Italy
Abstract :
This paper describes the potentialities of data integration of high spatial resolution multispectral (MS) and single-polarization X-band radar for object-based image analysis (OBIA) using already available algorithms and techniques. GeoEye-1 (GE1) MS images (0.5/2.0 m) and COSMO-SkyMed (CSK®) stripmap images (3.0 m) were collected over a complex test site in the Venetian Lagoon, made up of an intricate mixture of settlements, cultivations, channels, roads, and marshes. The validation confirmed that the integration of optical and radar data substantially increased the thematic accuracy [about 20%-30% for overall accuracy (OA) and about 25%-35% for k coefficient] of MS data, and unlike the outcomes of some new researches, also confirmed that, with appropriate preprocessing, traditional OBIA could also be applied to X-band radar data without the need of developing ad hoc algorithms.
Keywords :
geophysical image processing; object-oriented methods; radar imaging; radar polarimetry; remote sensing by radar; terrain mapping; COSMO-SkyMed data; COSMO-SkyMed stripmap images; GeoEye-1 MS images; GeoEye-1 data; OBIA; Venetian lagoon; ad hoc algorithms; channels; complex test site; cultivations; data integration; high spatial resolution multispectral analysis; marshes; object-based image analysis; optical data; radar data; roads; settlements; single-polarization X-band radar; thematic accuracy; Accuracy; Laser radar; Optical imaging; Optical sensors; Remote sensing; Standards; Synthetic aperture radar; COSMO-SkyMed (CSK®); COSMO-SkyMed (CSK??); GeoEye-1 (GE1); data integration; object-based image analysis (OBIA); thematic classification;
Journal_Title :
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
DOI :
10.1109/JSTARS.2015.2425211