I searched for " green belt" and I found this article: /info/en/?search=Green_belt

The article is relevant to the topic. The advantage of this article is its first sentences, which give the audience a quick view of green belt. However, in the first sentence I would like to add land use designing after “ land use planning” : greenbelt is a policy and land use designation used in land use planning and land use designing. I personally believe that one of the most important goals of creating green belt is preventing urban sprawl and it should be mention in the purposes of greenbelt and also in the first sentence: greenbelt is a policy and land use designation used in land use planning to prevent urban sprawl and retain areas of largely undeveloped, wild, or agricultural land surrounding or neighbouring urban areas. (Citation needed here!) Note: urban sprawl needs a citation for the audience for finding it by clicking on it. The purpose part needs the citation. Moreover, the information in this part is dispersed and needs to be organized.

The method Weighted Urban Proliferation (WUP) is a method for measuring urban sprawl. This method is presented by Jaeger et al. (2010b) ^[1] which indicates the level of sprawl as a matter of degree. The WUP method includes 3 components: 1)Percentage of built-up areas (PBA) which is the ratio of the size of built-up area divided by the size of the landscape (reporting unit): PBA = Size of built-up area / Reporting unit, 2) Dispersion of built-up areas (DIS) for measuring the dispersion of built-up areas based on the distances between any two points within the built-up areas , and 3) Land uptake per person (LUP) which is expressed as inhabitant or job per square meter. Weighted Urban Proliferation (WUP) used to quantify urban sprawl. It combines all three components into one metric which is an important advantage when comparing the resulting values with other studies in the past that used only a single component of urban sprawl. ^[2] WUP is the result of the Multiplicating of:

Urban Permeation (UP) which measures the permeation of a landscape by built-up areas, UP = PBA. DIS,

By the weighting of DIS (w₁(DIS))

and the weighting of the LUP (w₂(LUP))

The WUP method can be applied at any scale. ^[2]

Built-up areas “may include various types of settlement and buildings, ranging from places with urban character to villages to separate single buildings in the open landscape. Generally, a built-up area is defined as a surface covered by man-made structures. Roads and railways outside towns and cities are not included in this definition, since they are not perceived to be part of urban sprawl (but rather contribute to landscape fragmentation)" (EEA and FOEN, 2016, p. 47). ^[2]

(Weilenmann et al, 2016) worked on analysis of the major socio-economic determinants of changes in some urban patterns considered as sprawl in Switzerland. Their analysis covers the years 1980–2010, and has been conducted for all of the 2495 Swiss municipalities. ^[3]

In the other research (Jaeger et al, 2014 or and Schwick) ^[4], "Switzerland serves as an example of applying WUP method to examine the current state, for comparisons among regions, for historical analysis, and for assessing planning scenarios. The degree of urban sprawl in Switzerland increased by 155% between 1935 and 2002, and without rigorous measures, scenarios of future urban sprawl show that it is likely to further increase by more than 50% until 2050". ^[5]

(Nazarnia et al, 2016) ^[6] also used WUP method for measuring urban sprawl in Montreal and Quebec City in Canada between 1951 and 2011. They compared patterns of accelerated increase in sprawl in the Montreal and Quebec Census Metropolitan Areas in Canada with the Zurich metropolitan area in Switzerland between 1951 and 2011.  “On the Island of Montreal, the degree of urban sprawl (WUP) increased 26-fold from 0.49 UPU/m² in 1971 to 12.74 UPU/m² in 2011, while in Quebec City it increased 9-fold from 2.41 UPU/m² to 21.02 UPU/m² from 1971 to 2011. In contrast, the level of sprawl (WUP) in the Inner Zurich metropolitan area increased almost 3-fold from 3.12 UPU/m² in 1960 to 8.91 UPU/m² in 2010”. ^[6]

(Torres et al 2016) ^[7] used WUP Method to present a quantitative assessment of urban sprawl to test the stability, non-stationarity, and scale-dependency of the relationship between landscape fragmentation patterns and urban sprawl. ^[7]

Sierra Club (1998) used four metrics for measuring urban sprawl, including: population moving from the inner city to suburbs; comparison of land-use and population growth; time cost on traffic; and decrease of open space, to rank major metropolitan in the United States. ^[8]

Smart Growth America (2002) also used four metrics (residential density; mixture of residence, employment and service facilities; vitalization of inner city; and accessibility of road network) for the measurement of urban sprawl to study the impacts of sprawl on quality of life.

Jiang et al. (2007) used 13 geospatial indicators: 1) Area index, 2) Shape index, 3) Discontinuous development index, 4) Strip development index, 5) Leapfrog development index, 6) Planning consistency index, 7) Horizontal density index, 8) Vertical density index, 9) Population density index, 10) GDP density index, 11) Agriculture impact index, 12) Open space impact index and 13) Traffic impact index. They applied these indices in three groups (urban growth efficiency, spatial configuration and external impacts). The datasets for calculating these indicators were different. The datasets included: former land use maps, land use maps, land prices maps, floor area maps, land use planning maps, and population datasets. However, this method has its own drawback, which is the necessity of various datasets to calculate the 13 geospatial indices. ^[9]

One of the measures commonly used for urban sprawl measurement is Shannon’s entropy (Yeh and Li, 2001). ^[10] This method measures the patterns of built-up area as either dispersed or concentrated over time (Yeh and Li, 2001). The Entropy method is based on the calculation of area (Singh 2014). ^[11] In addition, the Entropy method is measured by a combination of remote sensing (RS), geographic information system (GIS) and photogrammetric techniques (Sudhira et al., 2004). ^[12]

Angel et al. (2007) used five metrics for measuring manifestations of sprawl (metrics of main urban core, secondary urban core, urban fringe, ribbon development and scatter development). They used these five metrics in their research about measurement of sprawl in Bangkok and Minneapolis case studies. They “define and measure sprawl both as a pattern of urban land use⎯that is, a spatial configuration of a metropolitan area at a point in time⎯and as a process, namely as the change in the spatial structure of cities over time” (Angel et al. 2007). They measured the changes of sprawl over time, and they also considered sprawl as a geographic pattern. The disadvantage of this method is that it provides complicated results due to the large number of metrics. ^[13]

Hello Mehrdokht, Evaluation Comments!

I have looked over your article and I have a few suggestions. For the first section, Weighted Urban Proliferation, I would try to describe in words each of the components of the WUP method (i.e. urban permeation (UP), dispersion (DIS), and utilization density (UD)). I would also incorporate the second section “Definition of built-up areas” into the first section – it doesn’t need to stand alone. For the third section “Some projects which used WUP method to measure urban sprawl” I would condense it a wee bit and try to say it all in your own words instead of using quotations. I can totally help you with this! For the last section "other methods" - I would removed it!! - it has a lot of information not relevant to the topic of WUP. Let me know if you want me to look over it again. Cheers!

Weighted Urban Proliferation (WUP) is a method used for measuring urban sprawl. This method, first introduced by Jaeger et al (2010) ^[1], calculates and presents the degree of urban sprawl as a numeric value. The method is based on the premise that as the built-over area in a given landscape increases (amount of built-up area), and the more dispersed this built-up area becomes (spatial configuration), and the higher the uptake of this built-up area per inhabitant or job increases (utilization intensity in the built-up area), the higher the overall degree of urban sprawl. ^[2]

The WUP method, thus. measures urban sprawl by integrating these three dimensions into a single metric. ^[2]

WUP = UP * w1(DIS) * w2(UD)

Where UP = Urban Permeation, w1(DIS) = Weighting1(Dispersion), and w2(UD) = Weighting2(Utilization Density).

Since the utilization density and dispersion are weighted with the weighting functions w2(UD) and w1(DIS), this metric of urban sprawl is referred to as Weighted Urban Proliferation (WUP).

The first component of the WUP method is urban permeation (UP). UP measures the size of the built-up area as well as its degree of dispersion throughout the study area (reporting unit). The formula for UP is

UP = (size of built up area /reporting unit) * dispersion

UP is expressed in urban permeation units per m² of land (UPU/m²). Within the framework of the WUP method, built-up areas are defined as areas where buildings are located. Since roads, railway lines, and parking lots, etc. are not buildings, they are disregarded in the WUP method of measuring urban sprawl.

The second component of the WUP method is dispersion (DIS). This component is based on the idea that the degree of urban sprawl intensifies with both increasing amount of urban area and increasing dispersion. The dispersion metric analyses the pattern of built-up area on the landscape from a geometric perspective. The analysis is preformed by taking distance measurements between random points within the built-up area. The average value is them computed from the measurement of all possible pairs of points. The farther apart any two points are, the higher the measurement value, and the higher their contribution to dispersion. Whereas the closer any two points are, the lower the value and the lower their contribution to dispersion. With the w1(DIS) function, dispersion values are weighted. This weighting function allows sections of the of the landscape where built-up areas are more dispersed to receive a higher weight, or a lower weighting for compact settled areas with low dispersion.

The third component of the WUP model is utilization density (UD). This component is based on the premise that as more people and jobs are located in the built-up area, the more efficient the utilization of the land becomes.

UD = (number of Inhabitants + number of jobs)/size of built up area

The number of jobs is included in the calculation to emphasis the fact that many downtown areas are dominated by office buildings that have very few residents, yet each building and thus the land they are on, is densely utilized and should not be considered sprawl. With the w1(UD) function, utilization density values are weighted. This weighting function allows sections of the built-up area to receive a value between 0-1 depending on their utilization density. The higher the utilization density, the lower the weighting value. This lower weight reflects the understanding that dense subsections of the reporting unit, like inner cities, are not considered as urban sprawl.

Jaeger & Schwick (2014) analysed historical changes as well as future scenarios for urban sprawl in Switzerland. They concluded that the degree of urban sprawl had increased by 155% between 1935 and 2002 and that, within the framework of modelling future scenarios, urban sprawl is likely to further increase by more than 50% by 2050 without abrupt mitigation measures. ^[4]

Nazarnia, Schwick & Jaeger (2016) compared patterns of accelerated urban sprawl, between 1951 and 2011, in the metropolitan areas of Montreal and Quebec City Canada, and Zurich in Switzerland. Their research determined that, in Montreal, the degree of urban sprawl increased 26-fold, Quebec City increased 9-fold, and Zurich 3-fold. ^[6]

Torres, Jaeger & Alonso (2016) quantified spatial patterns of urban sprawl for mainland Spain at multiple scales. They tested the stability, non-stationarity, and scale-dependency of the relationship between landscape fragmentation patterns and urban sprawl. ^[7]

Weilenmann, Seidl & Schulz (2017) analysed the major socio-economic determinants of change in urban patterns in Switzerland. Their analysis covered the years 1980–2010 and was conducted on all of the 2495 Swiss municipalities. ^[3]

On the other study, Jaeger et al.(2015) have used the Weighted Urban Proliferation (WUP) method on 32 countries in Europe to measure urban sprawl.The results show that large parts of Europe are affected by urban sprawl. It increased significantly between 2006 and 2009, but the values ​​of the individual countries differ greatly. ^[16]

Hayek et al. (2010) used settlement development scenarios for Switzerland, to find some causes of urban sprawl in order to reduce undesired future settlement developments in time.The results show that overall in Switzerland the urban permeation and dispersion of settlement areas is likely to increase in all scenarios in 2030,but to different degrees. ^[17]

== Examples of projects which used the WUP method. == Revised!

Hayek et al. (2010) used settlement development scenarios for Switzerland, to find the causes of urban sprawl in order to reduce undesired future settlement developments. The results show that overall urban permeation and dispersion of settlement areas is likely to increase, in varying degrees, in all scenarios by 2030. [17]

Jaeger & Schwick (2014) analysed historical changes as well as future scenarios for urban sprawl in Switzerland. They concluded that the degree of urban sprawl had increased by 155% between 1935 and 2002 and that, within the framework of modelling future scenarios, urban sprawl is likely to further increase by more than 50% by 2050 without abrupt mitigation measures. ^[4]

Jaeger et al. (2015) analysed the degree of urban sprawl for 32 countries in Europe. The results show that large parts of Europe are affected by urban sprawl, and that significant increases took place between 2006 and 2009, however, the values of the individual countries differ greatly. [16]

Nazarnia, Schwick & Jaeger (2016) compared patterns of accelerated urban sprawl, between 1951 and 2011, in the metropolitan areas of Montreal and Quebec City Canada, and Zurich in Switzerland. Their research determined that, in Montreal, the degree of urban sprawl increased 26-fold, Quebec City increased 9-fold, and Zurich 3-fold. ^[6]

Torres, Jaeger & Alonso (2016) quantified spatial patterns of urban sprawl for mainland Spain at multiple scales. They tested the stability, non-stationarity, and scale-dependency of the relationship between landscape fragmentation patterns and urban sprawl. ^[7]

Weilenmann, Seidl & Schulz (2017) analysed the major socio-economic determinants of change in urban patterns in Switzerland. Their analysis covered the years 1980–2010 and was conducted on all of the 2495 Swiss municipalities. ^[3]