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Hyperspectral Sensor Data Capability for Retrieving Complex Urban Land Cover in Comparison with Multispectral Data: Venice City Case Study (Italy)

View Article: PubMed Central

ABSTRACT

This study aims at comparing the capability of different sensors to detect land cover materials within an historical urban center. The main objective is to evaluate the added value of hyperspectral sensors in mapping a complex urban context. In this study we used: (a) the ALI and Hyperion satellite data, (b) the LANDSAT ETM+ satellite data, (c) MIVIS airborne data and (d) the high spatial resolution IKONOS imagery as reference. The Venice city center shows a complex urban land cover and therefore was chosen for testing the spectral and spatial characteristics of different sensors in mapping the urban tissue. For this purpose, an object-oriented approach and different common classification methods were used. Moreover, spectra of the main anthropogenic surfaces (i.e. roofing and paving materials) were collected during the field campaigns conducted on the study area. They were exploited for applying band-depth and sub-pixel analyses to subsets of Hyperion and MIVIS hyperspectral imagery. The results show that satellite data with a 30m spatial resolution (ALI, LANDSAT ETM+ and HYPERION) are able to identify only the main urban land cover materials.

No MeSH data available.


MIVIS and Hyperion fractional abundance images of the cemetery island north of Venice. IKONOS image is shown as reference. Color scale bar expresses the percentages of occurrence of the four endmembers used in the LSU analysis.
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f7-sensors-08-03299: MIVIS and Hyperion fractional abundance images of the cemetery island north of Venice. IKONOS image is shown as reference. Color scale bar expresses the percentages of occurrence of the four endmembers used in the LSU analysis.

Mentions: Figure 7 illustrates the results attained by applying the LSU trained with the spectra derived from the ROIs drawn on the images (i.e. cypress and grass spectra) and measured during the field campaigns (i.e. limestone and lateritic roof tiles). The fractional abundance images of the endmembers were scaled between 0-1 (a colors scale bar was adopted to depict the LSU results) and compared with those of the IKONOS ground-truth. Looking at Figure 7, the following general considerations could be made: (a) the grass class was retrieved by both sensors with a similar spatial distribution, identifying the sectors where, according to the IKONOS data, the meadow is mainly present; (b) the lateritic tiles are recognized by both sensors in the northern part of the image, where buildings are characterized by a large exposure of not weathered lateritic tiles; (c) the limestone occurrence within the island was retrieved by both MIVIS and Hyperion sensors in the area where the tombstone and the cemetery structures are made of the limestone material.


Hyperspectral Sensor Data Capability for Retrieving Complex Urban Land Cover in Comparison with Multispectral Data: Venice City Case Study (Italy)
MIVIS and Hyperion fractional abundance images of the cemetery island north of Venice. IKONOS image is shown as reference. Color scale bar expresses the percentages of occurrence of the four endmembers used in the LSU analysis.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3675545&req=5

f7-sensors-08-03299: MIVIS and Hyperion fractional abundance images of the cemetery island north of Venice. IKONOS image is shown as reference. Color scale bar expresses the percentages of occurrence of the four endmembers used in the LSU analysis.
Mentions: Figure 7 illustrates the results attained by applying the LSU trained with the spectra derived from the ROIs drawn on the images (i.e. cypress and grass spectra) and measured during the field campaigns (i.e. limestone and lateritic roof tiles). The fractional abundance images of the endmembers were scaled between 0-1 (a colors scale bar was adopted to depict the LSU results) and compared with those of the IKONOS ground-truth. Looking at Figure 7, the following general considerations could be made: (a) the grass class was retrieved by both sensors with a similar spatial distribution, identifying the sectors where, according to the IKONOS data, the meadow is mainly present; (b) the lateritic tiles are recognized by both sensors in the northern part of the image, where buildings are characterized by a large exposure of not weathered lateritic tiles; (c) the limestone occurrence within the island was retrieved by both MIVIS and Hyperion sensors in the area where the tombstone and the cemetery structures are made of the limestone material.

View Article: PubMed Central

ABSTRACT

This study aims at comparing the capability of different sensors to detect land cover materials within an historical urban center. The main objective is to evaluate the added value of hyperspectral sensors in mapping a complex urban context. In this study we used: (a) the ALI and Hyperion satellite data, (b) the LANDSAT ETM+ satellite data, (c) MIVIS airborne data and (d) the high spatial resolution IKONOS imagery as reference. The Venice city center shows a complex urban land cover and therefore was chosen for testing the spectral and spatial characteristics of different sensors in mapping the urban tissue. For this purpose, an object-oriented approach and different common classification methods were used. Moreover, spectra of the main anthropogenic surfaces (i.e. roofing and paving materials) were collected during the field campaigns conducted on the study area. They were exploited for applying band-depth and sub-pixel analyses to subsets of Hyperion and MIVIS hyperspectral imagery. The results show that satellite data with a 30m spatial resolution (ALI, LANDSAT ETM+ and HYPERION) are able to identify only the main urban land cover materials.

No MeSH data available.