Presentation + Paper
20 September 2020 Remote sensing and GIS approach for environmental green areas planning using Landsat imagery, Dubai-UAE
Author Affiliations +
Over the last decade, Dubai emirate witnessed a vast, rapidly growing population, that doubled since 2008. Nowadays, Dubai considers as the most populated emirate within the United Arab Emirates (UAE). With such an increasing population and new urban developments, sustainable urban planning procedures play an essential role in Dubai's environmental quality such as air quality, and pollution. Therefore, this study will utilize the Remote Sensing and Geographic Information system (GIS) to investigate Dubai's environmental quality by addressing and locating green areas and pollution percentages within each district. The study methodology is divided into three steps. First, Landsat Satellite medium spatial resolution and multi-spectral imagery will be used as an input for segmentation and object-based analysis. Considering the spectral and spatial signatures for green areas machine learning techniques will be adopted to select the most significant features to classify and extract green areas. Second, using environmental relational indices, green areas percentages will be quantitatively compared to Sentinel air quality data, such as NO2 and SO2, as well as the population density maps. Finally, GIS techniques will be used to create Dubai Environmental Critical Map (DECM), to locate districts with limited green areas and high pollution to improve environmental standards. The study results can be used as a measure for the municipality policymakers to ensure sustainable urban development for a healthy living.
Conference Presentation
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Diena Aldogom, Saeed Al Mansoori, Alya AlMaazmi, and Tasnim Nazzal "Remote sensing and GIS approach for environmental green areas planning using Landsat imagery, Dubai-UAE", Proc. SPIE 11534, Earth Resources and Environmental Remote Sensing/GIS Applications XI, 115340F (20 September 2020);
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Geographic information systems

Environmental sensing

Remote sensing

Satellite imaging


Earth observing sensors

Image segmentation

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