Re-Envisioning Urban Open Spaces

Cities are expanding rapidly, and the impact of dense human-oriented urban systems on ecosystems is both direct (conversion of natural land cover to urban footprint) and indirect. Human settlements are more complex than any other ecosystems as they meet human socio-ecological needs and support local biodiversity. The open spaces of a city with rich cultural character and biodiversity have become important elements of urban design, where urban systems can be planned to coexist with local biodiversity without disturbing the ecosystem. With the need to redefine urban footprint as an ecologically rich urban environment, this chapter addresses the definition of urban open space and questions the coexistence of humans and biodiversity in urban open spaces.

Fast Unsupervised Multi-Scale Characterization of Urban Landscapes Based on Earth Observation Data

Most remote sensing studies of urban areas focus on a single scale, using supervised methodologies and very few analyses focus on the “neighborhood” scale. The lack of multi-scale analysis, together with the scarcity of training and validation datasets in many countries lead us to propose a single fast unsupervised method for the characterization of urban areas. With the FOTOTEX algorithm, this paper introduces a texture-based method to characterize urban areas at three nested scales: macro-scale (urban footprint), meso-scale (“neighbourhoods”) and micro-scale (objects). FOTOTEX combines a Fast Fourier Transform and a Principal Component Analysis to convert texture into frequency signal. Several parameters were tested over Sentinel-2 and Pleiades imagery on Bouake and Brasilia. Results showed that a single Sentinel-2 image better assesses the urban footprint than the global products. Pleiades images allowed discriminating neighbourhoods and urban objects using texture, which is correlated with metrics such as building density, built-up and vegetation proportions. The best configurations for each scale of analysis were determined and recommendations provided to users. The open FOTOTEX algorithm demonstrated a strong potential to characterize the three nested scales of urban areas, especially when training and validation data are scarce, and computing resources limited.

URBAN FOOTPRINT OF MUMBAI - THE COMMERCIAL CAPITAL OF INDIA

Urban footprint refers to the proportion of paved surface (built up, roads, etc.) with the reduction of other land use types in a region. Rapid increase in the urban areas is the major driver in landscape dynamics with the significant erosion in the quality and quantity of the natural ecosystems. The urban expansion process hence needs to be monitored, quantified and understood for effective planning and the sustainable management of natural resources. Cities and towns have been experiencing considerable growth in urban area, population size, social aspects, negative environmental and geographical in?uence, and complexity. Mumbai, the commercial capital of India, has experienced a spurt in infrastructural and industrial activities with globalization and opening up of Indian markets. Unplanned urbanization has resulted in dispersed growth inperi-urban pockets due to socio-economic aspects with the burgeoning population of the city. Consequent to this, there has been an uneven growth pattern apart from the increase in slums in and around the city. This has necessitated the understanding of the urbanization pattern and process focusing especially on the expanding geographical area, its geometry and the spatial pattern of its development. This communication discusses the urban footprint dynamics of Mumbai using multi-temporal remote sensing data with spatial metrics. Land use analysis indicated a decrease of vegetation by 20% with an increase in urban extent by 155% during the last three decades. Landscape metrics aided in assessing the spatial structure and composition of the urban footprints through the zonal analysis by dividing the region into four zones with concentric circles of 1 km incrementing radius from the city centre. The study reveals a significant variation in the composition of the urban patch dynamics with increasing complexity and aggregation of urban area at the centre and sprawl at the outskirts. Shannon’s entropy further confirms of sprawl with time. Further zoning with the circular gradients aided in understanding the transition process of land use categories into urban patch.

URBAN FOOTPRINT OF MUMBAI - THE COMMERCIAL CAPITAL OF INDIA

Urban footprint refers to the proportion of paved surface (built up, roads, etc.) with the reduction of other land use types in a region. Rapid increase in the urban areas is the major driver in landscape dynamics with the significant erosion in the quality and quantity of the natural ecosystems. The urban expansion process hence needs to be monitored, quantified and understood for effective planning and the sustainable management of natural resources. Cities and towns have been experiencing considerable growth in urban area, population size, social aspects, negative environmental and geographical in?uence, and complexity. Mumbai, the commercial capital of India, has experienced a spurt in infrastructural and industrial activities with globalization and opening up of Indian markets. Unplanned urbanization has resulted in dispersed growth inperi-urban pockets due to socio-economic aspects with the burgeoning population of the city. Consequent to this, there has been an uneven growth pattern apart from the increase in slums in and around the city. This has necessitated the understanding of the urbanization pattern and process focusing especially on the expanding geographical area, its geometry and the spatial pattern of its development. This communication discusses the urban footprint dynamics of Mumbai using multi-temporal remote sensing data with spatial metrics. Land use analysis indicated a decrease of vegetation by 20% with an increase in urban extent by 155% during the last three decades. Landscape metrics aided in assessing the spatial structure and composition of the urban footprints through the zonal analysis by dividing the region into four zones with concentric circles of 1 km incrementing radius from the city centre. The study reveals a significant variation in the composition of the urban patch dynamics with increasing complexity and aggregation of urban area at the centre and sprawl at the outskirts. Shannon’s entropy further confirms of sprawl with time. Further zoning with the circular gradients aided in understanding the transition process of land use categories into urban patch.

Towards a Large-Scale 3D Modeling of the Built Environment—Joint Analysis of TanDEM-X, Sentinel-2 and Open Street Map Data

Continental to global scale mapping of the human settlement extent based on earth observation satellite data has made considerable progress. Nevertheless, the current approaches only provide a two-dimensional representation of the built environment. Therewith, a full characterization is restricted in terms of the urban morphology and built-up density, which can only be gained by a detailed examination of the vertical settlement extent. This paper introduces a methodology for the extraction of three-dimensional (3D) information on human settlements by analyzing the digital elevation and radar intensity data collected by the German TanDEM-X satellite mission in combination with multispectral Sentinel-2 imagery and data from the Open Street Map initiative and the Global Urban Footprint human settlement mask. The first module of the underlying processor generates a normalized digital surface model from the TanDEM-X digital elevation model for all regions marked as a built-up area by the Global Urban Footprint. The second module generates a building mask based on a joint processing of Open Street Map, TanDEM-X/TerraSAR-X radar images, the calculated normalized digital surface model and Sentinel-2 imagery. Finally, a third module allocates the local relative heights of the normalized digital surface model to the building structures provided by the building mask. The outcome of the procedure is a 3D map of the built environment showing the estimated local height for all identified vertical building structures at 12 m spatial resolution. The results of a first validation campaign based on reference data collected for the seven cities of Amsterdam (NL), Indianapolis (US), Kigali (RW), Munich (DE), New York (US), Vienna (AT), and Washington (US) indicate the potential of the proposed methodology to accurately estimate the distribution of building heights within the built-up area.

Mapping and Monitoring Urban Environment through Sentinel-1 SAR Data: A Case Study in the Veneto Region (Italy)

Focusing on a sustainable and strategic urban development, local governments and public administrations, such as the Veneto Region in Italy, are increasingly addressing their urban and territorial planning to meet national and European policies, along with the principles and goals of the 2030 Agenda for the Sustainable Development. In this regard, we aim at testing a methodology based on a semi-automatic approach able to extract the spatial extent of urban areas, referred to as “urban footprint”, from satellite data. In particular, we exploited Sentinel-1 radar imagery through multitemporal analysis of interferometric coherence as well as supervised and non-supervised classification algorithms. Lastly, we compared the results with the land cover map of the Veneto Region for accuracy assessments. Once properly processed and classified, the radar images resulted in high accuracy values, with an overall accuracy ranging between 85% and 90% and percentages of urban footprint differing by less than 1%–2% with respect to the values extracted from the reference land cover map. These results provide not only a reliable and useful support for strategic urban planning and monitoring, but also potentially identify a solid organizational dataflow process to prepare geographic indicators that will help answering the needs of the 2030 Agenda (in particular the goal 11 “Sustainable Cities and Communities”).

Monitoring the land consumption rate of urban growth from the Urban Footprint of Mexico, an online national cartographic platform

The spatial monitoring of the urban expansion and related population growth is useful for urban planning assessment of cities and megacities in the global South. Although market driven public programs for peri-urban low-income housing have retained much attention over the past twenty-five years in Mexico, a spatially explicit database of the consequent urban footprint together with the population census information has not been available online to the public. In this research, we build a geoscientific data collection consisting of: A built-up layer in 2000 and 2010 for the 10 major metropolitan areas of the Mexico Central Altiplano Region; A built-up layer in 2000 for the remaining 14 most prominent cities of the Mexican Urban System. A land consumption index at county (“Municipio”) level in the Mexico Central Altiplano Region. The Urban Footprint of Mexico is the first online national cartography incorporating built-up and demographic expansion.

Archaeological Sites in Small Towns—A Sustainability Assessment of Northumberland County

Background: Land-use change, resulting from urban expansion, has led to the unprecedented importance of rethinking our interactions with the environment in general. The consequences of anthropogenic activity on natural land, as well as sustainable land use types, is a significant concern to the detriment of small towns. In this article, I assess the changes in the urban footprint morphology of Northumberland County while evaluating the consequences of urban fragmentation on archaeological sites. Northumberland has a total population of 85,598 divided into seven municipalities and the Alderville First Nation reserve. Northumberland County is a commuting distance of one hour from Toronto, one of North America’s most important economic hubs. It is of the highest importance to measure and understand the current characteristics of land-use change and its impacts on the sustainability of small towns and local communities. Methods: A total of archaeological sites are used to test the impacts of urbanization and land-use change throughout the perimeter of Northumberland county. Spatial analysis is conducted employing spatial autocorrelation techniques (global and local) to assess the existence of hotspots of archaeological sites and the potential endangerment of these sites due to urban pressure. A hexagonal topology is used to derive a regional understanding of impacted regions within the county, allowing the richness of archaeological heritage sites as well as the possible concerns of these spatial clusters to be examined. Results: It is shown that a significant number of archaeological sites are present in Northumberland county, with a clear indication of a hotspot around Rice Lake. Future urbanization as well as land-use fragmentation may have an impact on the sustainability of these archaeological sites. It is shown that hexagonal geometries may establish relevant spatial surfaces to compare urban and archaeological sites as criteria to understand the endangerment of archaeological sites. The availability of the Global Urban Footprint (GUF) creates a particularly rigorous framework for the detection of impact on archaeological sites. Conclusion: The findings suggest that archaeological sites in small towns can benefit from high-resolution urban land-use footprints to detect impacts on archaeological sites and the relations of land-use change and intrasite management. This is of utmost importance in times of significant anthropogenic change brought by increasing urban pressure on small and medium-sized towns.