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The geographic locations of the 40 sample cities. The size and colour reflect the population and cultural region of the corresponding city.
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Land consumption delineates how effectively we use our living space - whether wastefully in area or efficiently. As the United Nations (UN) projects 5.1 billion population will live in urban areas in 2030, it is crucial to measure, compare, and understand land consumption for our cities across the globe. Currently global approaches for land consump...
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... urban morphology are very complex and challenging for the algorithm development. As large cities, they feature large population as well. Fifth, from a pragmatic point of view, we selected cities where LCZ reference data are available and accessible (X.X. Zhu et al., 2020). Based on these general rules, we selected 40 major cities. As shown in Fig. 1, the selected cities cover nine cultural regions, namely Australia, East Asia, South-east Asia, the Indian subcontinent, the Middle East, Europe, Africa, North America, and South America. Moreover, the selection includes economically less-developed cities, such as Islamabad, and very-developed cities, such as London. The selected ...
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... (2981 people/km 2 ). Moreover, regarding the urban land area, we found Hong Kong the second most dense city consuming at the same time the least urban land. In contrary, the city of Melbourne is the least dense city, yet, its urban land area is comparably large, ranking at seventh place. Rankings of urban land areas and population are shown in Fig. 11 and Fig. 12 in Appendix C, respectively. It is interesting to relate the land consumption data to geographic regions. We conduct a coarse analysis on the correlation between economy and land consumption by dividing the 40 sample cities into two groups: Global North and Global South. Understanding the Global South as geographic regions ...
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... 2 ). Moreover, regarding the urban land area, we found Hong Kong the second most dense city consuming at the same time the least urban land. In contrary, the city of Melbourne is the least dense city, yet, its urban land area is comparably large, ranking at seventh place. Rankings of urban land areas and population are shown in Fig. 11 and Fig. 12 in Appendix C, respectively. It is interesting to relate the land consumption data to geographic regions. We conduct a coarse analysis on the correlation between economy and land consumption by dividing the 40 sample cities into two groups: Global North and Global South. Understanding the Global South as geographic regions with a less ...
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... on our proposed clustering approach, we reveal six morphological types of cites among the 40 sample cities. We identified prominent characteristics for each of the six types, by comparing the cluster centers in Table. 2 and inspecting their classification maps. The classification maps of representative cities of each type are illustrated in Fig. 13 in Appendix D. We understand the term "structure" here on an intra-urban block scale, and the term "type" describes the category of The clustering approach classifies this configuration to a compact type as in the description of urban morphological formation. ...
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... investigate whether different types of cities, which therefore also have different morphological compositions, feature different types of land consumption. To do so, we analyze the correlation between the clustered morphological types of cities and population densities. We reorganize population densities in terms of the six city types as shown in Fig. 10. Since Islamabad is the only city categorized in the lightweight type, it is analyzed with cities of the open-lightweight type which is the most similar type to ...
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... is calculated and shown in the subplot a) of urban structural compactness is positively related to population density. However, the positive correlation is only valid from the statistical perspective of the mean population densities across types but not for individual cities. For example, Melbourne belongs to the compact type as in subplot c) of Fig. 10, but it is the least dense city among the 40 cities. Within the cities of compact type, it appears that the cities of low population density are western cities (Melbourne, Vancouver, and San Francisco). The same situation can also be observed in the compact-open type, as in subplot d) of Fig. 10, including Sydney, Lisbon, and New York. ...
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... belongs to the compact type as in subplot c) of Fig. 10, but it is the least dense city among the 40 cities. Within the cities of compact type, it appears that the cities of low population density are western cities (Melbourne, Vancouver, and San Francisco). The same situation can also be observed in the compact-open type, as in subplot d) of Fig. 10, including Sydney, Lisbon, and New York. For the open type in subplot e) of Fig. 10, all cities have a low population density, ten of the eleven cities are western cities (nine from Europe and one from North America). The industrial type rather presents the industrial functionality of cities with an average of 46.7% land as industrial ...
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... city among the 40 cities. Within the cities of compact type, it appears that the cities of low population density are western cities (Melbourne, Vancouver, and San Francisco). The same situation can also be observed in the compact-open type, as in subplot d) of Fig. 10, including Sydney, Lisbon, and New York. For the open type in subplot e) of Fig. 10, all cities have a low population density, ten of the eleven cities are western cities (nine from Europe and one from North America). The industrial type rather presents the industrial functionality of cities with an average of 46.7% land as industrial structures. Six of the eight cities are from China. There is no significant evidence ...
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... cities are western cities (nine from Europe and one from North America). The industrial type rather presents the industrial functionality of cities with an average of 46.7% land as industrial structures. Six of the eight cities are from China. There is no significant evidence for correlation with population density. As shown in subplot b) of Fig. 10, the open-lightweight and lightweight types have an outstanding finger print which features a very high population density in the lightweight ...
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... C. Ranks of land area and population Fig. 11 and Fig. 12 show the ranking of the 40 cities in terms of land area and population, respectively. The values are calculated based on the refined GHS-POP data. Fig. 12. This figure shows the rank of the 40 cities in terms of population. The total population is given by the GHS-POP data that is spatially overlapped with the MUA urban ...
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... C. Ranks of land area and population Fig. 11 and Fig. 12 show the ranking of the 40 cities in terms of land area and population, respectively. The values are calculated based on the refined GHS-POP data. Fig. 12. This figure shows the rank of the 40 cities in terms of population. The total population is given by the GHS-POP data that is spatially overlapped with the MUA urban extent. The ...
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... C. Ranks of land area and population Fig. 11 and Fig. 12 show the ranking of the 40 cities in terms of land area and population, respectively. The values are calculated based on the refined GHS-POP data. Fig. 12. This figure shows the rank of the 40 cities in terms of population. The total population is given by the GHS-POP data that is spatially overlapped with the MUA urban extent. The population of possible residing urban blocks are also given, which are compact, open, and lightweight structures. The population is calculated after the ...
Citations
... The contribution of each city to these numbers depends, among many aspects, on the size of urban settlements as well as on their land use patterns. These spatial patterns of urban land, including the two-and three-dimensional form and structure, have significant impact on GHG emissions (IPCC, 2014), land consumption (Hu, Wang, Taubenböck, & Zhu, 2021), land use efficiency (Schiavina et al., 2022), the urban heat island effect (Massaro et al., 2023), mobility patterns (Kang, Ma, Tong, & Liu, 2012), quality of life (Sapena et al., 2021), among many other issues. Thus, the spatial patterns of urban settlement growth influence a city's social, economic, and ecological conditions. ...
... However, we need to be aware that substantial variations exist across the globe as, for example, we measure different city sizes for different continents and geographical regions. Hu et al. (2021) showed how diverse land consumption is with respect to the structural configuration of cities across the globe. Using the extremes of their study, Mumbai in India is measured with 46,406 inhabitants per km 2 and Melbourne in Australia with 4069 inhabitants per km 2 , allows to project theoretically what that would mean for our set of all cities across the globe larger than 300,000 inhabitants: In the three decades from 1985 to 2015 these cities expanded their settlement area by 120,178 km 2 and increased their population by 1.142 billion. ...
Cities are expanding all over the world. In this study we aim to understand how the pace and scale of urban growth dynamics vary across geographies. This study contributes to the literature in four key ways: First, the study is comprehensive including all 1567 cities worldwide that had >300,000 inhabitants in 2015. Second, comparison of settlement dynamics of cities is performed in relation to continents, to geographic regions, to national levels and to city sizes. Third, a data-driven approach to delineate city boundaries allows for consistent comparisons across geographies. Fourth, the measured past urban trends are projected into the future and linked to climate scenarios used by the Panel on Climate Change (IPCC) to estimate where spatial focal areas of urbanization and climate-change meet. The study is based on remote sensing-derived geodata such as the World Settlement Footprint Evolution dataset for the period 1985 to 2015 and morphological urban areas. The key findings are: At continental scale, highest relative urban growth rates are measured in Asia. Among the IPCC regions, highest relative urban growth rates are in East Asia. In contrast, lowest growth rates are in Oceania and Europe. As expected, across most regions, there is a general decline in relative growth rates over the study period. One surprising finding is that absolute settlement expansion rates are not declining over time, but are rather relatively constant. It is also interesting to see that across and within countries growth rates of urban settlements vary widely in Asia, whereas in Europe there are only marginal differences. And finally, a look into the future reveals that certain regions can expect particularly high exposures. In South Asia and West Africa, for example, very high urban growth rates and a very high increase in predicted maximum rainfall are forecast. The greatest increase in extreme temperatures is predicted for Europe and North America. Settlement growth has already slowed there, so adaptation measures are taking center stage.
... Although the LCZ scheme was originally designed for urban heat islands (Quan and Bansal, 2021;Xue et al., 2020), its application has expanded to urban planning, public health implications even preliminary attempts at population estimation (Zhao et al., , 2021Ma et al., 2023) as the physical parameters defining LCZ types (e.g., building height, compactness, etc.) are highly related to population density. In terms of evidence of correlation between population and LCZs, Hu et al. (2021a) have disaggregated population through LCZs for assessing land consumption. Demuzere et al. (2020) briefly defined the range of population counts with LCZ types from the LCZ map of the continental United States, while Zhou et al. (2022a) further conducted an in-depth analysis of the population density of LCZ types and found a hierarchical effect of population density among built LCZs in differently sized cities. ...
... The population density of the settlement layer can be generally interpreted as the product of several variables, such as building spacing, building height, and others (Weber et al., 2018), resulting in a positively skewed log-normal distribution of the population density due to the multiplicative effects (Hara and Kotze, 2010). It has been already found that LCZ type, defined by multiple parameters (e.g., building floors, compactness, etc.), is related to population density (Demuzere et al., 2020;Hu et al., 2021a). However, for the LCZ classification scheme, it is not yet clear how specific built types are linked with population density. ...
... To qualify the variation of population density with LCZs and city size in detail, we specify population density intervals at a confidence level of 68.3% (i.e., μ ± 1σ) in different city sizes and urban LCZ categories (Fig. 3), like Demuzere et al. (2020). The results are generally consistent with previous studies (Demuzere et al., 2020;Hu et al., 2021a;Zhou et al., 2022a). In particular, compact LCZ types containing more buildings show higher population densities than the open types, and high-rise LCZ types associated with high buildings show higher population densities than the low-rise types (Fig. 3). ...
... In traditional urban studies, population serve as the main method to measure the size of cities. With the development of remote sensing and geographic information system, the measure of built-up areas through satellite images has become an essential technique to examine urban growth (Herold, Goldstein, & Clarke, 2003;Seto, Fragkias, Güneralp, & Reilly, 2011), thereby leading to the exploration of the relationship between urban land expansion and population growth, and further the calculation of the area of built-up land per capita (Hu, Wang, Taubenböck, & Zhu, 2021;Marshall, 2007). However, compared to the abundance of demographic data, evidence of urban land size in historical times is extremely limited (Karakuyu, 2011). ...
... According to the calculation method of single indicators, the development level of a city can be visualized using a traffic light system, with green, yellow, orange, and red colors [41]. Based on the sub-indicator scores for ranking, among the 13 cities and counties, those ranked 1-4 are considered green indicators, those ranked 5-9 are considered yellow indicators, and those ranked 10-13 are considered orange indicators. ...
Quantifying the progress and interactions of the 11 indicators of Sustainable Development Goal 11 plays a crucial role in improving urban living and promoting urban prosperity. SDG 11, focused on sustainable cities and communities, employs forward-thinking strategies to address challenges arising from urban prosperity and development, such as land scarcity and resource shortages. This paper positions the indicators of SDG 11, analyzing the patterns, trends, dynamics, and issues of urbanization development in Guilin using a combination of geospatial satellite resource data and categorical statistical data. The study introduces a framework and positioning method for assessing sustainable development at the city–county scale, exploring the current state, spatial aggregation, synergies, and trade-offs in the development of Guilin City. The study introduces a framework and positioning method for assessing sustainable development at the city–county scale. Utilizing a localized evaluation system, it explores the developmental status of Guilin City. The application of Moran’s Index observes spatial aggregation among entities. By investigating Spearman’s rank correlation coefficient, it delves into the interplay of synergies and trade-offs within the studied region. Ultimately, it reveals significant disparities in the developmental landscape of the evaluated area, with a comprehensive spatial distribution indicating higher levels of development in the central and western regions and lower levels in the southeastern part. Strengthened cross-leverage and coordination are imperative to address the interconnections and harmonization of the developmental trends of the six synergistic indicators and nine trade-off indicators during the developmental process. The sustainable development of Guilin lays the groundwork for urban planning, construction, conservation, and management, positioning it as a potential model for successful sustainable development practices.
... As more than half of the world's population lives in urban areas, inhabited land is dramatically expanding and used in myriad ways, impacting natural landscapes and constantly challenging-environmental, economic, and social-the three bottom lines of sustainability (Hu et al., 2021;Irwin & Bockstael, 2007;Kopnina, 2016;Purvis et al., 2019). ...
... We found that studies conducted at the local scale such as city blocks or neighborhoods provided better typologies and characteristics of urban form than studies at the coarser scale such as cities. Studies mostly applied spatial units defined by political boundaries and municipal designated units, while units precisely delineating homogeneous urban morphological characteristics such as morphological urban area (MUA) (Hu et al., 2021;Taubenböck et al., 2019) and urban structural units (de Castro et al., 2019;Haggag and Ayad, 2002;Łaszkiewicz et al., 2022) were not considered in the selected studies. In particular, MUA is a spatial unit capturing realistic settlement boundaries from urban to rural transition areas (Taubenböck et al., 2019) and could be used to explore the heterogeneity of urban morphological characters and its impact on sustainability in less densely settled areas. ...
... Landsat was the most frequently used satellite imagery data in the selected articles. There are, however, other useful remote sensing data such as high-resolution Sentinel-1 and Sentinel-2, Global Urban Footprint data (GUF), Local Climate Zone (LCZ) data, and more recently So2Sat Global Urban LCZ data with detailed urban form parameters are available at the global scale (Bechtel et al., 2015;Esch et al., 2012;Hu et al., 2021;Stewart & Oke, 2012;Taubenböck et al., 2020;Zhu et al., 2022). We encourage future studies to seek and use updated highresolution datasets for investigating sustainable urban morphological studies at different spatial scales and geographic locations globally. ...
Urban morphology is examined in various disciplines as it is associated with a range of ecological, social, and economic sustainable outcomes. Yet there is a lack of clarity and consensus on measuring urban morphology indicators that will allow interdisciplinary scholarship at a city, regional, or global scale for integrated sustainable solutions. This systematic review aims to 1) develop a taxonomy of measures of urban form indicators linked to sustainable outcomes spanning environmental, economic, and social dimensions, 2) systematically summarize the quantitative methods used to analyze urban morphology-sustainability relationships, 3) identify existing research trends, gaps, and future research directions for sustainable urban morphology studies. Based on the 89 systematically searched and synthesized articles, we identified 365 unique metrics of urban morphology with a wide variability of names, operational definitions, and data used. We provided a list of these metrics classified into six aspects (i.e., urban tissue configuration, street network, building-plot characteristics, land use, natural features and greenspace, and urban growth) and their sub-categories, highlighting the most used metrics. Even though urban morphology is inherently a spatial concept, considerations of spatial models in understanding urban morphology-sustainability relationships were limited. Synthesizing nine groups of sustainable outcomes further informed that future studies should focus more on the natural features and ecosystem health of cities. This review recommended adopting a consistent classification scheme in measuring, quantifying, and assessing urban forms in relation to sustainable outcomes to facilitate interdisciplinary research as an important step to finding solutions for achieving environmental, social, and economic sustainable outcomes worldwide.
... They include the commonly used supervised or unsupervised methods applying pixel-based or object-based approaches. Some of the existing methods are based on a mix of semi-automatic classification and photointerpretation of satellite and airborne optical images [7], whereas more recent methods are focused on spectral indices [14,15], machine learning technics [16], integration of SAR and optical images [1], or a combination between radar and Geospatial Big Data [17]. However, those methods always are dependent on the datasets used. ...
... A total of 22 studies out of 25 selected have chosen a local/city/regional scale study area. Just three articles [17,55,56] consider the national scale as a study area to detect land consumption. These methods, indeed, were used to produce, respectively, a comparative study of 40 cities across the world and the national land consumption map of Italy. ...
... It is free. [1,17,55,59,61,[68][69][70]72] Lastly, Google Earth Engine is used by different studies to implement pre-processing and classification algorithms. It is a very useful instrument, since it allows for directly visualizing images through the Copernicus hub and working on them without downloading them, and quickly changing location, type of products, etc. ...
The development of remote sensing technology has redefined the approaches to the Earth’s surface monitoring. The Copernicus Programme promoted by the European Space Agency (ESA) and the European Union (EU), through the launch of the Synthetic Aperture Radar (SAR) Sentinel-1 and the multispectral Sentinel-2 satellites, has provided a valuable contribution to monitoring the Earth’s surface. There are several review articles on the land use/land cover (LULC) matter using Sentinel images, but it lacks a methodical and extensive review in the specific field of land consumption monitoring, concerning the application of SAR images, in particular Sentinel-1 images. In this paper, we explored the potential of Sentinel-1 images to estimate land consumption using mathematical modeling, focusing on innovative approaches. Therefore, this research was structured into three principal steps: (1) searching for appropriate studies, (2) collecting information required from each paper, and (3) discussing and comparing the accuracy of the existing methods to evaluate land consumption and their applied conditions using Sentinel-1 Images. Current research has demonstrated that Sentinel-1 data has the potential for land consumption monitoring around the world, as shown by most of the studies reviewed: the most promising approaches are presented and analyzed.
... (2) Lower bound = + Land consumption rate/population growth rate Land consumption (LC) is the conversion of any land use into urban (i.e., residential, commercial, industrial). Hu et al. (2021) define it as "modified natural lands to man-made structures due to the living, social, and economic purposes of the urban residences." It is simply a measure of urban sprawl. ...
... The LC increased more than seven times in Kastamonu, six times in Çanakkale, and five times in Bolu. However, significant differences among cities in urban land consumption are a global fact, according to a study where 40 cities were compared (Hu et al., 2021). ...
Urban forests are becoming more critical as climate-induced disasters and disturbances tend to increase and affect cities. Forest managers are the responsible technical people on the ground to implement forestry-related climate policies. There is limited knowledge on the capacities of forest managers related to climate change issues. In this study, we surveyed 69 forest district managers of 28 provinces and compared their responses with actual data to understand their perceptions of urban green areas and climate change issues. We used a set of digital maps of the 1990–2015 period to identify land cover changes. To calculate the urban forest cover in the city centers, we used the city limit delineation shapefiles produced by the EU Copernicus program. We also employed the land consumption rate/population growth rate metric and a principle component analysis (PCA) to identify and discuss the provinces’ land and forest cover changes. The results showed that forest district managers were aware of the general condition of the forests in their provinces. Still, there was a considerable inconsistency between actual land use changes (i.e., deforestation) and their responses. The study also revealed that the forest managers were aware of the increasing influence of climate change issues but were not knowledgeable enough to establish the connection between their tasks and climate change. We concluded that the national forestry policy should prioritize the urban-forest interaction and develop the capacities of district forest managers to improve the efficiency of climate policies on a regional scale.
... However, more recently the concept of land consumption has been attributed to all lands characterized by the loss of multifunctional, fertile soils and in the deterioration of biodiversity and ecosystem services [34][35][36]. In this sense, land degradation, defined as the reduction or loss of biological productivity and ecological integrity [37], includes land consumption resulting from modified natural lands in urban structures [38]. Degradation factors can be many and include topography (i.e., slope), soil quality, and resilience, extreme events, land-use and land-cover change, and land mismanagement, which can cause environmental, social, and economic impacts [2,39,40]. ...
Among the UNCCD SDGs 2030, there is the recognition that land consumption can strongly affect the provision of ecosystem services. From the perspective of land degradation neutrality, urban level is the right scale when planning actions against land consumption. The aims of this research are: (1) to assess land consumption at urban landscape scale and its effects on natural capital flow provision; and (2) to identify sustainable strategic planning choices for land consumption mitigation and natural capital enhancement. We propose and test an approach based on multi-temporal landscape spatial analysis (land use/land cover map, land consumption map, and landscape metrics) and ecosystem services’ flow assessment for the identification of areas at risk of loss of natural capital flow. The results have shown that from 2006 to 2019, land consumption has increased with a consequent decrease of natural capital flow. LULC dynamics has been analyzed in terms of landscape risk to lose natural capital flow, highlighting that the management of Galatone urban landscape is still far from land consumption neutrality. Landscape metrics have allowed the analysis of the aggregation among land consumption areas. The mitigation of land consumption should be based on the identification of suitable nature-based solutions towards the balance between past land consumption and future land recovery.
... It should be noted that the correlation between population growth and land consumption has been addressed by many authors at the international level, especially in the last 10 years, testifying to the growing importance of the topic (Nicolau et al., 2018;Wang et al., 2020;Sharma et al., 2012;Calka et al., 2022;Abdulkadir et al., 2019;Marquard et al., 2020;Jantz and Manuel, 2013;Ningal et al., 2008;Hu et al., 2021;Shelestov et al., 2020). ...
Over the last few years, land take monitoring in Europe and in Italy has become increasingly accurate and detailed owing to improved technologies that help acquire and make available free, easily accessible and high-resolution data. Nevertheless, the key issue is controlling this phenomenon, long considered pathological in its current form and scale, in order to mitigate / reverse it and achieve the 2030 containment targets set in international guidelines. To attain these results, firm regulatory action is certainly needed, underpinned by thresholds and reference limits to regulate the development of transformation activities planned by local authorities.
In 2015, the United Nations Global Agenda for Sustainable Development Goals (SDGs) put forward a parameter for this purpose, namely the "Ratio of land consumption rate to population growth rate" (11.3.1 LCRPGR). It monitors the ratio between the extent of urban development and demographic dynamics in spatial-administrative units in order to link the growth of urbanized areas to actual population growth. This paper sets out a reconnaissance experiment to identify LCRPGR cut-off that can be used in legislation in relation to life quality indicators calculated repeatedly for Italy at the provincial level. The conclusions highlight the considerable difficulty inherent in identifying normative thresholds for the containment of negative spatial and social phenomena, and the need to develop scientific methods that are more reliable and robust than what is present in current practice.
... which was found to be significant, confirms established notions that high-density developments conserve land (Towers, 2002;Glaeser, 2011). A corollary of these building types is a high population density per unit area (Hu et al., 2021). In contrast, single-family dwellings, which were highly significant in our study, positively influenced land take. ...
Rapid transitions induced by migration flows and socio-economic developments brought about massive changes in urbanization processes and resulted in increasingly uncertain futures. The implications and complexities of the ensuing urbanization patterns are difficult to predict and project into the future. While most studies are focused on large cities and major urban centers, urbanization processes in small and medium-sized cities have garnered little scholarly and political attention. To understand future urbanization patterns, we used the TOPOI method, a novel approach for classifying territorial settlements, and spatial autoregressive models to examine contrasting futures of population growth and shrinkage in one small and one medium-sized city in Lower Saxony, Germany. Results revealed that despite planning frameworks, high population density and functional mix, respectively, were insufficient mechanisms to reduce land take. Contrary to current assumptions on the functional mix of small and medium-sized towns, our findings showed that more than half of the settlements across the study area accommodated three or more functions. Since the share of residential buildings and functional mix strongly influenced land take, further research is needed to understand their implications on sustainable urban planning. Shrinking towns in Lower Saxony continue to present multidimensional challenges and emphasize the need for transforming local planning cultures and institutional frameworks to sustainably manage and repurpose these potentially vacant areas.
