![]() ![]() For example, building height – or related information like floor area – has been shown to be an important indicator for estimating energy consumption ( Resch et al., 2016), material stock allocation ( Tanikawa et al., 2015), greenhouse gas emissions ( Borck, 2016), human wellbeing and urban heat island effects ( Perini and Magliocco, 2014), or the distribution of population ( Alahmadi et al., 2013). Many quantities scale linearly with building height. For understanding urban process regimes, knowing building heights is key ( Zhu et al., 2019), and the vertical structure of settlements has been identified as a central parameter to systematize multi-dimensional urban form ( Wentz et al., 2018). While cities only cover a small portion of the Earth's land surface, their impact is far-ranging as they are, for example, accountable for up to 80% of total energy consumption and 75% of carbon emissions ( United Nations, 2020). Three quarters of humanity currently lives in cities and towns ( Dijkstra et al., 2020), and it is estimated that this trend will continue unabatedly. ![]() physical analysis of structural features or mapping society's resource usage. It mostly relies on freely available satellite imagery and open source software, which potentially permit frequent update cycles and cost-effective mapping that may be relevant for a plethora of different applications, e.g. We emphasize the straightforward applicability of this approach on the national scale. The average building height varies considerably across Germany with lower buildings in Eastern and South-Eastern Germany and taller ones along the highly urbanized areas in Western Germany. ![]() ![]() When testing the model against independent datasets, very consistent performance was achieved (frequency-weighted RMSE of 2.9 m to 3.5 m), which suggests that the prediction of the most frequently occurring buildings was robust. Results indicate that both radar-only and optical-only models can be used to predict building height, but the synergistic combination of both data sources leads to superior results. The novelty of this method lies in the very fine resolution yet large spatial extent to which it can be applied, as well as in the use of building shadows in optical imagery. We trained machine learning regression models with highly accurate building height information from several 3D building models. We utilized information from the spectral/polarization, temporal and spatial dimensions by combining band-wise temporal aggregation statistics with morphological metrics. In this study, we combined Sentinel-1A/B and Sentinel-2A/B time series to map building heights for entire Germany on a 10 m grid resolving built-up structures in rural and urban contexts. However, openly accessible information at high spatial resolution is still missing at large for complete countries or regions. Architect and Contractor Takenaka Corporation Construction Takenaka Corporation and Kitano Construction Corp joint venture Site area 6,262.42㎡ Zoning district Commercial zone Fire protection district Fire preventive zone Utility and function Office, hall, retail/service establishment Structure type Steel construction, steel-frame reinforced concrete structure and reinforced concrete structure Number of floors 4 underground floors, 31 above ground floors and 2 penthouse floors Maximum height 146m Building area 2,958㎡ Building coverage ratio 47.24% Total floor area 83,298.65㎡ Total floor space for lease 75,144㎡ Floor space index 1,199.Urban areas and their vertical characteristics have a manifold and far-reaching impact on our environment. Design supervision Mitsubishi Estate Co., Ltd. Second phase construction September 2002 Building owners The Sankei Building Co., Ltd. Property Outline Location 1-7-2 Otemachi, Chiyoda-ku, Tokyo Completion First phase construction September 2000, ![]()
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