Exploring Built-Up Indices and Machine Learning Regressions for Multi-Temporal Building Density Monitoring Based on Landsat Series.

Uncontrolled built-up area expansion and building densification could bring some detrimental problems in social and economic aspects such as social inequality, urban heat islands, and disturbance in urban environments. This study monitored multi-decadal building density (1991-2019) in the Yogyakarta urban area, Indonesia consisting of two stages, i.e., built-up area classification and building density estimation, therefore, both built-up expansion and the densification were quantified. Multi sensors of the Landsat series including Landsat 5, 7, and 8 were utilized with some prior corrections to harmonize the reflectance values. A support vector machine (SVM) classifier was used to distinguish between built-up and non built-up areas. Regression algorithms, i.e., linear regression (LR), support vector regression (SVR), and random forest regression (RFR) were explored to obtain the best model to estimate building density using the inputs of built-up indices: Urban Index (UI), Normalized Difference Built-up Index (NDBI), Index-based Built-up Index (IBI), and NIR-based built-up index based on the red (VrNIR-BI) and green band (VgNIR-BI). The best models were revealed by SVR with the inputs of UI-NDBI-IBI and LR with a single predictor of UI, for Landsat 8 (2013-2019) and Landsat 5/7 (1991-2009), respectively, using separate training samples. We found that machine learning regressions (SVM and RF) could perform best when the sample size is abundant, whereas LR could predict better for a limited sample size if a linear positive relationship was identified between the predictor(s) and building density. We conclude that expansion in the study area occurred first, followed by rapid building development in the subsequent years leading to an increase in building density.

Effects of residential building height, density, and floor area ratios on indoor thermal environment in Singapore.

Building height, building density, and floor area ratio are the three key parameters in urban planning. However, little is known about their impact on indoor thermal environments as compared with outdoor thermal environments. The study aimed to investigate their impact on indoor air temperatures in Singapore. Singapore's residential buildings were reviewed from the perspective of the three parameters, and the Envi-met model was employed for simulation after its accuracy was confirmed by field experiments. Indoor air temperatures under 18 scenarios were simulated and analyzed. The analytical results revealed that among the three parameters, the building density was the most influential. An increase in building density reduced the indoor temperature. In Singapore, the building density increases from 0.0625 to 0.766, which reduced the mean indoor temperature by 4.7 °C. The indoor temperature decreased slightly with an increase in building height. An increase in building height from 12 to 72 m produced an indoor temperature decrease of approximately 1.7 °C. The influence of floor area ratio on indoor air temperature was the most complex. For a fixed floor area ratio of 2, the indoor temperature first increased and then decreased with an increase in building density, which resulted in an indoor temperature difference of 2.1 °C when the building density increased from 0.141 to 0.766.

Effects of neighborhood building density, height, greenspace, and cleanliness on indoor environment and health of building occupants.

The influences of indoor environment quality on occupant health have long been one of the main focuses in built environment and public health research. However, evidence to this effect has been inconsistent. Furthermore, previous urban studies have indicated the interaction between urban morphology and indoor environment. This study thus goes beyond indoor environment to investigate: i) the effects of neighborhood environment on occupant health; and ii) the mediating roles of indoor environment on the neighborhood environment and occupant health relationships. To achieve this aim, buildings located in different neighborhood environment in Hong Kong are selected. Data are collected by post-occupancy evaluation (occupant health), indoor environment assessment (thermal comfort, indoor air quality, ventilation, visual comfort, and acoustic comfort) and neighborhood environment assessment (neighborhood building density, building height, cleanliness and greenspace) through questionnaire survey. Through correlation analysis, regression modelling and Sobel test, it is found that: i) occupant health is significantly affected by neighborhood building height, building density and cleanliness; ii) the relationships between neighborhood environment and occupant health are significantly mediated by indoor environment, in terms of visual and acoustic comfort; and iii) neighborhood greenspace affects occupant health indirectly through influencing indoor air quality. To cross validate the results of the survey study, which is conducted using subjective data, objective measurements and analyses are further conducted. The objective study, echoing the survey study results, indicates that buildings with lower neighborhood building density and height, and cleaner neighborhood environment have better visual (higher illuminance level) and acoustic (lower noise level) performances.

Effects of exurban development and temperature on bird species in the southern Appalachians.

Land-use dynamics and climatic gradients have large effects on many terrestrial systems. Exurban development, one of the fastest growing forms of land use in the United States, may affect wildlife through habitat fragmentation and building presence may alter habitat quality. We studied the effects of residential development and temperature gradients on bird species occurrence at 140 study sites in the southern Appalachian Mountains (North Carolina, U.S.A.) that varied with respect to building density and elevation. We used occupancy models to determine 36 bird species' associations with building density, forest canopy cover, average daily mean temperature, and an interaction between building density and mean temperature. Responses varied with habitat requirement, breeding range, and migration distance. Building density and mean temperature were both included in the top occupancy models for 19 of 36 species and a building density by temperature interaction was included in models for 8 bird species. As exurban development expands in the southern Appalachians, interior forest species and Neotropical migrants are likely to decline, but shrubland or edge species are not likely to benefit. Overall, effects of building density were greater than those of forest canopy cover. Exurban development had a greater effect on birds at high elevations due to a greater abundance of sensitive forest-interior species and Neotropical migrants. A warming climate may exacerbate these negative effects.

Public exposure to broadband electromagnetic fields and its association with population density and building density: The case study of Beijing.

The gradual increase in electromagnetic field (EMF) exposure levels poses a potential threat to human health and the normal operation of electronic systems. In order to know the environmental EMF conditions, measurements were carried out on roads of about 400 km in the urban area of Beijing, China. The measurement results show that the electric field strength of about 89% of the sampling points is within 3 V/m, and the electric field strength of other sampling points is relatively high. Combined with further spectrum analysis, it was found that the electric field strength of one road section exceeded the national standard limits. In addition, to help quickly identify the general condition of the environmental EMF, a set of procedures for mining the association rules between the electric field strength and population density and building density is proposed in this paper. The final association rules show that the electric field strength is usually lower than 1.5 V/m in areas with medium or lower population density and areas with low building density; the electric field strength in areas with extremely high population density and areas with high building density is usually 1.5-4 V/m; while the electric field strength higher than 4 V/m mainly occurs in areas with extremely high population density. It is recommended to focus on strengthening the monitoring of EMF in areas with extremely high population density, and at the same time continuously pay attention to the trend of the urban EMF levels, so as to achieve early warning and treatment of relevant risks.

The spatial configuration of buildings: A vital consideration impossible to ignore in regulating urban land surface temperature? Evidence from 35 Chinese cities.

Land urbanization not only efficiently met the requirements of social development but also brought severe heating effects, especially the changes in Land Surface Temperature (LST). The effects of building density on LST and driving relation of the configuration of buildings remain poorly understood over large areas. Using Landsat 8 satellite imagery acquired from the summer of 2019, this study quantified the heating effects (k) of building density on LST across 35 cities in China, and further analyzed the driving relation of the configuration of buildings such as the size, shape, and spatial distribution on k. Here the regression analysis results showed that the building density had a significant relationship with LST, and the k varied from 1.10 to 7.27 amount of the different cities. The size and aggregation distribution of buildings were the main positive drivers for the effects of building density on LST, and the shape of buildings was not obviously related to the k-value. The results of thermal environment simulation showed that the major reason might be that the close spatial relationship reduced the heat exchange between buildings and the atmosphere, resulting in higher LST. These conclusions will provide an important reference for urban planning and design.

Wildland-urban interface typologies prone to high severity fires in Spain.

Due to complex interactions between climate and land use changes, large forest fires have increased in frequency and severity over the last decades, impacting dramatically on biodiversity and society. In southern European countries affected by demographic challenges, fire risk and danger play special relevance at the wildland-urban interfaces (WUIs), where decision-making and land management have strong socio-ecological implications. WUIs have been historically typified according to both fire occurrence probability and settlement vulnerability, but those classifications lack generality regarding fire regime components. We aim to develop an integrated and comprehensive scheme for identifying the WUI typologies most at risk to fire severity across large territories. We selected fourteen large wildfires (over than 500 ha) occurred in Spain (2016-2021) containing different WUI scenarios. First, based on a building cartography and a multi-temporal series of Sentinel-2 imagery, each WUI was delimited and spatially characterized according to building density and pre-fire fuel characteristics (type, amount, and structure). Afterwards, a decision tree regression model was applied to identify the most relevant pre-fire vegetation parameters driving burn severity. The combined effect of the selected pre-fire vegetation drivers and the building density patterns on fire severity was evaluated using linear mixed models. Finally, the WUI typologies most prone to high burn severity were recognized using Tukey post-hoc tests. Results indicated that building density, land cover class and vegetation cover fraction determined fire severity in areas close to human settlements. Specifically, isolated, scattered and sparsely clustered buildings enclosed in a high-cover shrub matrix were the WUI typologies most susceptible to high-severity fires. These findings contribute to the development of appropriate strategies to minimize the risk of severe fires in WUIs and avoid potential losses of multiple ecosystem services valuable for society.

Analyzing the Variation of Building Density Using High Spatial Resolution Satellite Images: the Example of Shanghai City.

Building density is an important issue in urban planning and land management. In the article, building coverage ratio (BCR) and floor area ratio (FAR) values extracted from high resolution satellite images were used to indicate buildings' stretching on the surface and growth along the third dimension within areas of interest in Shanghai City, P.R. China. The results show that the variation of FAR is higher than that of BCR in the inner circle, and that the newer commercial centers have higher FAR and lower BCR values, while the traditional commercial areas have higher FAR and BCR ratios. By comparing different residential areas, it was found that the historical "Shikumen" areas and the old residential areas built before 1980s have higher BCR and lower FAR, while the new residential areas have higher FAR and lower BCR, except for the villa areas. These results suggest that both older building areas and villa areas use land resources in an inefficient way, and therefore better planning and management of urban land are needed for those fast economic growing regions.

Relationship Between the Built Environment and Body Mass Index in a Rural Context: A Cross-Sectional Study from Vermont.

Objective To evaluate the association between a marker of urban development (commercial building density) and body mass index (BMI) in a predominantly rural context. Methods A cross-sectional analysis of two geocoded datasets from Vermont. The first includes subjects from the Vermont Diabetes Information System (VDIS), an extensively attributed dataset of adult diabetics (n = 610); the second was the complete driver's license records for Vermont (n = 401,367). The dependent variable was BMI, measured objectively for the VDIS data and self-reported for the driver's license data. The explanatory variable was commercial buildings per hectare within 250 m of the home address used as a proxy for walkability. We regressed BMI against density in both datasets, controlling for age and gender; a separate regression was run for the VDIS data, controlling for a number of additional confounders related to health, activity, diet, and income. Results All models demonstrated a significant positive relationship between BMI and commercial building density. For the three VDIS data models, coefficients of density were +0.75, +0.79, and +0.90, all of which indicate an approximate ¾ kg/m2 increase in BMI for each additional commercial facility per hectare (p < 0.01). For the driver's license data, the coefficient was +0.16, which also indicates an increase in BMI with increasing density (p < 0.01). Discussion We found that BMI displays a positive association with commercial building density in Vermont, which is inconsistent with previous findings. The difference may be due to the unique rural focus of this study. Other characteristics of rural life may be associated with lower incidence of obesity and should be studied further.

Effects of urban form on the urban heat island effect based on spatial regression model.

The urban heat island (UHI) effect is becoming more of a concern with the accelerated process of urbanization. However, few studies have examined the effect of urban form on land surface temperature (LST) especially from an urban planning perspective. This paper used spatial regression model to investigate the effects of both land use composition and urban form on LST in Wuhan City, China, based on the regulatory planning management unit. Landsat ETM+ image data was used to estimate LST. Land use composition was calculated by impervious surface area proportion, vegetated area proportion, and water proportion, while urban form indicators included sky view factor (SVF), building density, and floor area ratio (FAR). We first tested for spatial autocorrelation of urban LST, which confirmed that a traditional regression method would be invalid. A spatial error model (SEM) was chosen because its parameters were better than a spatial lag model (SLM). The results showed that urban form metrics should be the focus for mitigation efforts of UHI effects. In addition, analysis of the relationship between urban form and UHI effect based on the regulatory planning management unit was helpful for promoting corresponding UHI effect mitigation rules in practice. Finally, the spatial regression model was recommended to be an appropriate method for dealing with problems related to the urban thermal environment. Results suggested that the impact of urbanization on the UHI effect can be mitigated not only by balancing various land use types, but also by optimizing urban form, which is even more effective. This research expands the scientific understanding of effects of urban form on UHI by explicitly analyzing indicators closely related to urban detailed planning at the level of regulatory planning management unit. In addition, it may provide important insights and effective regulation measures for urban planners to mitigate future UHI effects.

Building-Based Analysis of the Spatial Provision of Urban Parks in Shenzhen, China.

Urban parks provide important environmental, social, and economic benefits to people and urban areas. The literature demonstrates that proximity to urban parks is one of the key factors influencing people's willingness to use them. Therefore, the provision of urban parks near residential areas and workplaces is one of the key factors influencing quality of life. This study designed a solution based on the spatial association between urban parks and buildings where people live or work to identify whether people in different buildings have nearby urban parks available for their daily lives. A building density map based on building floor area (BFA) was used to illustrate the spatial distribution of urban parks and five indices were designed to measure the scales, service coverage and potential service loads of urban parks and reveal areas lacking urban park services in an acceptable walking distance. With such solution, we investigated the provision of urban parks in ten districts of Shenzhen in China, which has grown from several small villages to a megacity in only 30 years. The results indicate that the spatial provision of urban parks in Shenzhen is not sufficient since people in about 65% of the buildings cannot access urban parks by walking 10-min. The distribution and service coverage of the existing urban parks is not balanced at the district level. In some districts, the existing urban parks have good numbers of potential users and even have large service loads, while in some districts, the building densities surrounding the existing parks are quite low and at the same time there is no urban parks nearby some high-density areas.