Spatial And : Spatial Analysis

During this unit of human geography, I have learned so much about religions, ethnicities, and even culture. For example, I learned about the religion Islam and how it is a religion of peace just like the Hindu religion and as well as the Buddhist religion and much more others. These religions and some others have much in common whether they accept it , these religions and some more are all peaceful religions and all teach good morals and principles to the followers, everyone following footsteps of good people and their good actions and/or deeds. When I was reading chapter 7 ( ethnicity) I learned that ethnicity also has to do with culture and that the chapter before that one, we were reading about ( folk culture) and how it much ties in with

The Five Themes of Geography are: Location – Absolute points on a map or grid or Relative to where something may be; Place – The physical and/or human characteristics of a locations; Human/Environment Interactions – How humans have impacted the landscape or environment; Relationship between places Movement – How humans interact on the earth (i.e. how they communicate over distance (short or long)) and Regions – a unit of space that has commonalities defined by physical, human and environmental geography. The Explorers of the New World may have not known what the Five Themes of Geography were but they quickly learned. Of the five themes the ones that they all took advantage of was the physical Location and Place as they learned to navigate

Cronulla is a beachside suburb in southern Sydney, it is located 34.0574° S, 151.1522° E which is 26 kilometres south of the Sydney CBD (see figure 2). It is governed by the Sutherland Shire Council. Cronulla’s coastal environment is on the Kurnell Peninsula, which is made up of a tombolo. A tombolo is a sand spit connecting a rocky outcrop or island to the mainland. So this forms a barrier between Botany Bay and Bate Bay. The two areas of study visited were Wanda Beach and the Greenhills Beach development.

I thought cities had more diversity, more poverty, and low income household than suburb areas and this was supported by the above data. I learned that the increase of wealth and income in a small community hinders the rest of community where middle and low income families live. The ability to live in a “good” neighborhood is linked to income. Income can be one of the factors that determine how a region can be segregated. Even in the city, the income of the household separates the lower income families from the higher income families. High income families tend to live together and low income families tend to live in the same

For my theme, I chose the word change because I feel that throughout this chapter, each civilization has gone through changes as time went on. Western Asia went through changes when it was split into Babylonia and Assyria. The two zones became different and accomplished things on their own after. But in the Mediterranean, after many people settles and migrated from many place of the world, the Mediterranean became more successful because of its goods and success in trading. Also in Israel, when the Bible became more popular and there were more followers of Yahweh, many customs were changed. For example, monotheism was one of the changes the Israelites went through, because before, polytheism, the worship of more than one god, was more popular and well-known.

Given this context, three neighborhood level variables, number of liquor stores, percent vacant houses, and concentrated disadvantage were determined as the best level-2 predictors to explain neighborhood level substantial variance identified by the unconditional model. Table 9 shows the introduction of these three level-2 variables in the HLM equation. When these level-2 predictors are added to unconditional model, level-2’s (intercept, mean level of violent crime arrests) variance component was substantially reduced.

Spillover effects are ‘the economic events in one context that occur because of something else in a seemingly unrelated context’ (Wikipedia, 2016). Though spillover effects may be beneficial, it may also have adverse effects In a study conducted by Schnittker et al., it was noted that THE CRIMINAL JUSTICE SYSTEM AND THE HEALTH CARE SYTSEM ARE RELATED; THE INCREASE IN INCARCERATION RATES IN AN AREA CAN BE LINKED TO QUALITY AND FUNCTION OF THE HEALTHCARE SYSTEMS.

The diverse parts of a metropolitan region play an important role in its economic development. In the New York City metropolitan area, the different cities and towns that make up these sectors are marked by varying community characteristics such as average household income and crime rate. For example, both considered a suburb of New York City, the village of Great Neck and Hempstead are located in the Nassau County on Long Island. These two suburbs are just a 25 minute drive away from each other but have otherwise very different demographics, economic and housing qualities, and income and spending statistics.

In Plato’s Republic, Socrates’s dialogues with minor characters starts after Socrates is involuntarily “persuaded” to take a detour to Polemarchus's house in which they have long and deep philosophical conversations. As the main character in Republic, Socrates shows his understanding of justice, the order and key elements of a just city, and a just man. Specifically in Book VI of Republic, Socrates’s conclusion—the just city will only exist if it is ruled by philosophers—is challenged by Adeimantus who is considered to be a very responsible and moderate person. Adeimantus claims that philosophers are “cranks,” “vicious” and “useless”; however, Socrates refutes his argument by explaining and proving the reasons behind Adeimantus’s misunderstanding of a true philosopher.

As I have mentioned above, the origin of spatial mismatch phenomenon was found through the empirical test. However, the theoretical conception is still unclear. There was no literature which provides the micro foundations for this hypothesis until Brueckner & Martin (1997) develop a theoretical model to directly address the welfare effect of spatial mismatch hypothesis. The authors adopted a fixed-wage model with a setup of the linear city. Besides taking the traditional assumption of the hypothesis, the authors also take two spatial elements into account, that is, job decentralization and a restriction of non-white housing relocation to the suburbs. Under the analyses, Brueckner & Martin indicated that spatial mismatch has caused the non-white inner-city workers to pay higher rent at a certain commuting distance and thus obtain lower real wage. This was translated as a welfare loss for non-white.

Having differences between the two types of fMRI, “Spatial Correlations of Laminar BOLD and CBV Responses to Rate Whisker Stimulation with Neuronal Activity Localized by Fos Expression” by Lu et al. exemplifies the spatial limitations of BOLD fMRI and in contrast demonstrates CBV fMRI’s superior spatial specificity. The paper states that the spatial specificity of BOLD fMRI is limited due to two reasons: the physiological process to the hemodynamic response and the microcirculation of the brain (Lu et al, 2004). Duvernoy et al.’s discovery of the venous unit is specifically deteriorates BOLD’s spatial specificity. The venous unit is compromised of large cortical penetrating veins to drain the amount of deoxygenated blood. This propagation of DH makes it difficult to pinpoint the origin of brain activity which gave reason to Lu et al. to hypothesize that the venous unit employs inaccurate positive BOLD signals (Duvernoy et al., 1981). Menon and Goodyear add that BOLD fMRI suffers greatly due to its low contrast to noise ratio (Menon and Goodyear, 1999). It was also made known, by Lee et al., that fractional changes in blood vessel diameter are

Employment is often a key indicator of the population movement. Hence, we use unemployment rate (%) as a factor in the model. The quarterly unemployment rate data is obtained from SLA Markets publications by the Department of Employment, Australian Government. To minimise the variability inherent in small area estimates, the Department provides smooth data, i.e., a four-quarter average, at the SA2s from 2010. Before 2010 data are only available at the SLA . The SLA has a spatial misalignment with the SA2, and to overcome this issue we use the dynamic spatial modelling technique (Bakar, Kokic, & Jin, 2015) and estimate the quarterly unemployment rate from 2006 to 2009 at the SA2 level. Details of the modelling approach is provided in the supplementary section. To match the yearly time-series format of the net population flow data, we aggregate the unemployment data at the FY level and consequently calculate the maximum and the average unemployment rate at each SA2s for

In spatial analysis, the aim is often to identify the natural relationship between pairs of variables. And the most common type of analysis used to achieve this aim is regression (Fotheringham & Rogerson, 2009, p. 243). In a conventional linear regression model, we use a single equation to assess the overall relationships between a single dependent and more independent variables across space. An important assumption underlying this approach is that the relationships of interest are stationary or homogeneous over space (Fotheringham & Charlton, 1998). So, the parameter estimates from the regression model are constant over space (Fotheringham & Rogerson, 2009, p. 244). Relationships which exhibit spatial nonstationarity (or heterogeneity) will create the problem for the interpretation of parameter estimates from a linear regression model (Fotheringham & Charlton, 1998). To address this issue, Dr. Brunsdaon et al., (1996) developed a

Before the decision of our final residential location choice model, we tested how preferences of residential location are different among age and income groups. Stratifying the sample of households by age and income is helpful to identify some of the heterogeneity in housing preferences among different market segments as well as investigate whether differences of location preferences exist between different groups. All the household location choice models performed reasonably well as shown in table 1, 2, and 3.

In the Carlino-Mills (1987) model, the underlying assumption are that (1) households and firms are spatially mobile, (2) households migrate to maximize their utility from the consumption of private goods and services and use of non-market goods (amenities), and (3) firms locate to maximize their profit whose production costs and revenues depend on business conditions, local public services, markets, and supply of inputs. These assumptions indicate that interdependence between employment and household income exists because household migrate if they can obtain better income