Residential areaA residential area is a land used in which housing predominates, as opposed to industrial and commercial areas. Housing may vary significantly between, and through, residential areas. These include single-family housing, multi-family residential, or mobile homes. Zoning for residential use may permit some services or work opportunities or may totally exclude business and industry. It may permit high density land use or only permit low density uses.
Sustainable urbanismSustainable urbanism is both the study of cities and the practices to build them (urbanism), that focuses on promoting their long term viability by reducing consumption, waste and harmful impacts on people and place while enhancing the overall well-being of both people and place. Well-being includes the physical, ecological, economic, social, health and equity factors, among others, that comprise cities and their populations.
SuburbA suburb, more broadly suburban area, is an area within a metropolitan area where most jobs are located. It is primarily a commercial or residential area, and often includes mixed-use areas and can sometimes have more jobs than population. A suburb can exist either as part of a larger city/urban area or as a separate political entity. The name describes an area which is either more or less densely populated than an inner city. In many metropolitan areas, suburbs exist as separate residential communities within commuting distance of a city (cf "bedroom suburb".
Residential communityA residential community is a community, usually a small town or city, that is composed mostly of residents, as opposed to commercial businesses and/or industrial facilities, all three of which are considered to be the three main types of occupants of the typical community. Residential communities are typically communities that help support more commercial or industrial communities with consumers and workers. That phenomenon is probably because some people prefer not to live in an urban or industrial area, but rather a suburban or rural setting.
Affordable housingAffordable housing is housing which is deemed affordable to those with a household income at or below the median as rated by the national government or a local government by a recognized housing affordability index. Most of the literature on affordable housing refers to mortgages and a number of forms that exist along a continuum – from emergency homeless shelters, to transitional housing, to non-market rental (also known as social or subsidized housing), to formal and informal rental, indigenous housing, and ending with affordable home ownership.
NeighbourhoodA neighbourhood (Commonwealth English) or neighborhood (American English; see spelling differences) is a geographically localised community within a larger city, town, suburb or rural area, sometimes consisting of a single street and the buildings lining it. Neighbourhoods are often social communities with considerable face-to-face interaction among members. Researchers have not agreed on an exact definition, but the following may serve as a starting point: "Neighbourhood is generally defined spatially as a specific geographic area and functionally as a set of social networks.
Multifamily residentialMultifamily residential (also known as multidwelling unit or MDU) is a classification of housing where multiple separate housing units for residential inhabitants are contained within one building or several buildings within one complex. Units can be next to each other (side-by-side units), or stacked on top of each other (top and bottom units). A common form is an apartment building. Many intentional communities incorporate multifamily residences, such as in cohousing projects.
Spatial databaseA spatial database is a general-purpose database (usually a relational database) that has been enhanced to include spatial data that represents objects defined in a geometric space, along with tools for querying and analyzing such data. Most spatial databases allow the representation of simple geometric objects such as points, lines and polygons. Some spatial databases handle more complex structures such as 3D objects, topological coverages, linear networks, and triangulated irregular networks (TINs).
Machine learningMachine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.
Sustainable cityThe sustainable city, eco-city, or green city is a city designed with consideration for social, economic, environmental impact (commonly referred to as the triple bottom line), and resilient habitat for existing populations, without compromising the ability of future generations to experience the same. The UN Sustainable Development Goal 11 defines sustainable cities as those that are dedicated to achieving green sustainability, social sustainability and economic sustainability.
SustainabilitySustainability is a social goal for people to co-exist on Earth over a long time. Specific definitions of this term are disputed and have varied with literature, context, and time. Experts often describe sustainability as having three dimensions (or pillars): environmental, economic, and social, and many publications emphasize the environmental dimension. In everyday use, sustainability often focuses on countering major environmental problems, including climate change, loss of biodiversity, loss of ecosystem services, land degradation, and air and water pollution.
Sustainable designEnvironmentally sustainable design (also called environmentally conscious design, eco-design, etc.) is the philosophy of designing physical objects, the built environment, and services to comply with the principles of ecological sustainability and also aimed at improving the health and comfort of occupants in a building. Sustainable design seeks to reduce negative impacts on the environment, the health and well-being of building occupants, thereby improving building performance.
Urban sprawlUrban sprawl (also known as suburban sprawl or urban encroachment) is defined as "the spreading of urban developments (such as houses and shopping centers) on undeveloped land near a city". Urban sprawl has been described as the unrestricted growth in many urban areas of housing, commercial development, and roads over large expanses of land, with little concern for urban planning. In addition to describing a special form of urbanization, the term also relates to the social and environmental consequences associated with this development.
Commercial areaCommercial areas in a city are areas, districts, or neighborhoods primarily composed of commercial buildings, such as a strip mall, office parks, downtown, central business district, financial district, "Main Street", or shopping centers. Commercial activity within cities includes the buying and selling of goods and services in retail businesses, wholesale buying and selling, financial establishments, and a wide variety of uses that are broadly classified as "business.
Spatial analysisSpatial analysis is any of the formal techniques which studies entities using their topological, geometric, or geographic properties. Spatial analysis includes a variety of techniques using different analytic approaches, especially spatial statistics. It may be applied in fields as diverse as astronomy, with its studies of the placement of galaxies in the cosmos, or to chip fabrication engineering, with its use of "place and route" algorithms to build complex wiring structures.
Online machine learningIn computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once. Online learning is a common technique used in areas of machine learning where it is computationally infeasible to train over the entire dataset, requiring the need of out-of-core algorithms.
Middle classThe middle class refers to a class of people in the middle of a social hierarchy, often defined by occupation, income, education, or social status. The term has historically been associated with modernity, capitalism and political debate. Common definitions for the middle class range from the middle fifth of individuals on a nation's income ladder, to everyone but the poorest and wealthiest 20%. Theories like "Paradox of Interest" use decile groups and wealth distribution data to determine the size and wealth share of the middle class.
Working classThe working class, sometimes incorrectly referred to as the middle class, includes all employees who are compensated with wage or salary-based contracts. Working-class occupations (see also "Designation of workers by collar colour") include blue-collar jobs, and most pink-collar jobs. Members of the working class rely exclusively upon earnings from wage labour; thus, according to more inclusive definitions, the category can include almost all of the working population of industrialized economies, as well as those employed in the urban areas (cities, towns, villages) of non-industrialized economies or in the rural workforce.
Random forestRandom forests or random decision forests is an ensemble learning method for classification, regression and other tasks that operates by constructing a multitude of decision trees at training time. For classification tasks, the output of the random forest is the class selected by most trees. For regression tasks, the mean or average prediction of the individual trees is returned. Random decision forests correct for decision trees' habit of overfitting to their training set.
Binary classificationBinary classification is the task of classifying the elements of a set into two groups (each called class) on the basis of a classification rule. Typical binary classification problems include: Medical testing to determine if a patient has certain disease or not; Quality control in industry, deciding whether a specification has been met; In information retrieval, deciding whether a page should be in the result set of a search or not. Binary classification is dichotomization applied to a practical situation.
