This paper examines the utility of high-resolution airborne RGB orthophotos and LiDAR data for mapping residential land uses within the spatial limits of suburb of Athens, Greece. Modem remote sensors deliver ample in...This paper examines the utility of high-resolution airborne RGB orthophotos and LiDAR data for mapping residential land uses within the spatial limits of suburb of Athens, Greece. Modem remote sensors deliver ample information from the AOI （area of interest） for the estimation of 2D indicators or with the inclusion of elevation data 3D indicators for the classification of urban land. In this research, two of these indicators, BCR （building coverage ratio） and FAR （floor area ratio） are automatically evaluated. In the pre-processing step, the low resolution elevation data are fused with the high resolution optical data through a mean-shift based discontinuity preserving smoothing algorithm. The outcome is an nDSM （normalized digital surface model） comprised of upsampled elevation data with considerable improvement regarding region filling and ＂straightness＂ of elevation discontinuities. Following this step, a MFNN （multilayer feedforward neural network） is used to classify all pixels of the AOI into building or non-building categories. The information derived from the BCR and FAR building indicators, adapted to landscape characteristics of the test area is used to propose two new indices and an automatic post-classification based on the density of buildings.展开更多
In order to minimise the bushfires negative impacts on society, an efficient andreliable bushfire detection system was proposed to assess the devastated effects of the2009 Victorian bushfires.It is possible to utilise...In order to minimise the bushfires negative impacts on society, an efficient andreliable bushfire detection system was proposed to assess the devastated effects of the2009 Victorian bushfires.It is possible to utilise the repetitive capability of satellite remotesensing imagery to identify the location of change to the Earth's surface and integrate thedifferent remotely sensed indices.The results confirm that the procedure can offer essentialspatial information for bushfire assessment.展开更多
文摘This paper examines the utility of high-resolution airborne RGB orthophotos and LiDAR data for mapping residential land uses within the spatial limits of suburb of Athens, Greece. Modem remote sensors deliver ample information from the AOI （area of interest） for the estimation of 2D indicators or with the inclusion of elevation data 3D indicators for the classification of urban land. In this research, two of these indicators, BCR （building coverage ratio） and FAR （floor area ratio） are automatically evaluated. In the pre-processing step, the low resolution elevation data are fused with the high resolution optical data through a mean-shift based discontinuity preserving smoothing algorithm. The outcome is an nDSM （normalized digital surface model） comprised of upsampled elevation data with considerable improvement regarding region filling and ＂straightness＂ of elevation discontinuities. Following this step, a MFNN （multilayer feedforward neural network） is used to classify all pixels of the AOI into building or non-building categories. The information derived from the BCR and FAR building indicators, adapted to landscape characteristics of the test area is used to propose two new indices and an automatic post-classification based on the density of buildings.
文摘In order to minimise the bushfires negative impacts on society, an efficient andreliable bushfire detection system was proposed to assess the devastated effects of the2009 Victorian bushfires.It is possible to utilise the repetitive capability of satellite remotesensing imagery to identify the location of change to the Earth's surface and integrate thedifferent remotely sensed indices.The results confirm that the procedure can offer essentialspatial information for bushfire assessment.
