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Methodology to integrate hyperspectral Remote Sensor data with GIS for decision support systems:- A case of hail storm damage in Sydney
Field Check
A good understanding of the surface features is essential for accurate analysis of the Hymap image. A database was created for different land-uses, which showed the material composition of the surface features which ranged from roof types (terracotta tiles, concrete tiles, slate tiles, corrugated fibro and metal) to pavers and bitumen. A database was also created by surveying the field in the study area with the aid of a laptop and high resolution aerial photo image as well as other GIS layers such as street network and census layers (see Fig xxx). Most of the materials fell into the category of terracotta tiles, concrete tiles, slate tiles, corrugated fibro and metal roofs, pavers and bitumen which were found almost exclusively in some places and in a mixed form in others. Since the spatial resolution of the HyMap image was 5m by 5m care was taken to examine those areas which could be also be spatially resolved on the hymap image. Apart from the material composition, the age, location, use and function of the place where the sample feature was found was also recorded. In some instances where the roofs could not be seen directly, local but reliable knowledge was obtained from staff who were working at these places. Methodology and Analysis Various samples of urban surface materials, mainly consisting of roofing materials and pavers were gathered from different sources. Table 2 shows some of the different surface materials used in the analysis.
Table 2
Apart from the types of roofing materials collected, particular care was also taken to collect weathered and non-weathered materials. The methodology was to generate a reference spectral library consisting of different types of spectra from roofing materials. The HyMap sensor cover both the reflective V-I-S; 0.4-0.7µm, N-I-R; 0.7-1.1µm and SWIR; 1.1-2.5 µm wavelengths. A FieldSpec® Pro Full Range (FR) spectro-radiometer from Analytical Spectral Devices (ASD, Colorado, Boulder, USA) as shown in Fig 1 that measures reflectance in the VIS, SWIR I & II was used to collect reflectance (i.e in the white reference mode). The spectrometer unit incorporates 3 spectrometers to cover the 0.350-2.500µm wavelength. The HyMap image has 126 bands which were reduced to 115 bands due to poor data quality in bands 63,64,65,66,67,94,95,96,97,125 and 126. This was done for two reasons: firstly to avoid data from pronounced absorption features operating outside the atmospheric window such as water H2O near 1.4µm and carbon-dioxide CO2 at 1.9µm and secondly to avoid negative reflectance values from the image spectra, since the reference spectral library were all in positive reflectance values. The negative values from image spectra were possibly due to some inconsistencies in the sensor. The reference spectra was calibrated and forced to the image spectra and a supervised classification Spectral Angle Mapper (SAM) was performed in order to create surface abundance maps showing roofing materials with different resistances to hail storm. Accuracy estimation was carried in the field with the aid of high spatial aerial photo images. The classified image was georeferenced to the UTM projection system zone 56. Integration with GIS data to show the areas at risk was performed by spatial overlay over the geo-referenced classified HyMap image. 
Figure.2 Methodology |