Quantifying the City’s Green Area Potential Gain Using Remote Sensing Data
Information about green spaces available in a city is essential for urban planning. Urban green areas are generally assessed through environmental indicators that reflect the city’s quality of life and urban comfort. A methodology based on 3D measure and analysis of green urban areas at the city sca...
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| Veröffentlicht in: | Sustainability 2016-12, Vol.8 (12), p.1247-1247 |
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| creator | Santos, Teresa Tenedório, José Gonçalves, José |
| description | Information about green spaces available in a city is essential for urban planning. Urban green areas are generally assessed through environmental indicators that reflect the city’s quality of life and urban comfort. A methodology based on 3D measure and analysis of green urban areas at the city scale is presented. Two products are proposed: (1) measuring current vegetation cover at ground level through object-oriented classification of WorldView-2 imagery; and (2) estimating potential green cover at rooftop level using 3D data obtained by LiDAR sensor. The methodology, implemented in Lisbon, Portugal, demonstrates that: (1) remote sensing imagery provides powerful tools for master planning and policy analysis regarding green urban area expansion; and (2) measures of urban sustainability cannot be solely based on indicators obtained from 2D geographical information. In fact, 2D urban indicators should be complemented by 3D modelling of geographic data. |
| doi_str_mv | 10.3390/su8121247 |
| format | Article |
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| source | MDPI - Multidisciplinary Digital Publishing Institute; EZB-FREE-00999 freely available EZB journals |
| subjects | Buildings Cities Environmental indicators Geographic information systems Geography Ground level Image classification Indicators Interdisciplinary aspects Remote sensing Remote sensors Roofing Roofs Social sciences Sustainability Two dimensional models Urban areas Urban planning Vegetation mapping |
| title | Quantifying the City’s Green Area Potential Gain Using Remote Sensing Data |
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