Modelling of the Interaction Between Urban Sprawl and Agricultural Landscape Around Denizli City, Turkey

Transcription

1 Modelling of the Interaction Between Urban Sprawl and Agricultural Landscape Around Denizli City, Turkey Serhat Cengiz, Sevgi Gormus, Şermin Tagil

2 Outline of Presentation Urban Growth Urban Models Denizli City Modeling Urban Growth Urban Growth in Denizli Urban Politics and Urban Growth Geographic Location Urban Politics Urban Growth Model: Logistic Regression Analysis Evaluation of The Variables Effective On Urban Growth via LRM What is Suitable Model for Denizli City

3 Urban Sprawl in Turkey Small Scale City Bartın Medium Scale City Malatya Large Scale City Ankara Metropolitan City İstanbul

4 Urban Growth and Urban Models As a result, the city is growing or spreading despite everything. And urban planning policies have failed. WHY? One of the most important reasons why urban planning policies are insufficient and unsuccessful is the limited techniques used for understanding and evaluating spatial-temporal designs and dynamics. Planning is a prudential action and so it needs building strong bonds between the past and the future. By developing urban planning decisions, the responsible planners are required to make temporal analyses for urban dynamics in order to think analytically and make decisions.

5 Materials And Method Study Area : Denizli

6 Materials And Method (Logistic Regression Model) Data Process The classification of satellite images Determining and Creating Variables Creating the Model Estimation Model Simulation 2025 Knowledge Land use change Urban sprawl Identifıng variables that effect urban sprawl Control model-2015 The most variables that prove urban sprawl Evaluation urban politics

7 Materials And Method (Modeling Urban Growth) Modeling the urban growth in the study is processed in two phases as: Control model (2015) and Estimation model (2025). In control model, it was estimated an urban growth for 2015 by using data from and the accuracy of the model was tested by comparing with the real urban growth (2015). In estimation model, it was estimated an urban growth for 2025 by using data from and it was revealed how the variables used in the model would affect the urban growth. In creating models, the studies were respectively carried out under the following main titles: 1. classification of satellite images, 2. determining/creating variables to be considered effective in urban growth and creating model.

8 Materials And Method (The classification of satellite images) In this study for Landsat image classification was used object based classification method (Threshold) Landsat 5 (08/1987) Landsat 7 (08/2001) Landsat 8 (08/2013) Specific to this study, two-scale-factor was determined in the phase of segmentation. In order to create road details, the scale factor was weighted «1» and all the bands were scaled 1 (chess board segmentation). The scale factor and NIR band were weighted respectively as «25» and 2 for the fundamental land use categories. Overall accuracy was determined 82%, 83% and 88% by years.

9 Materials And Method (Creating the Model) Urban Growth Model: Logistic Regression Analysis Logistic regression (LR) is one of the experimental and statistical methods. LR is also a parametric model that is commonly used and models the change of spatial use. LR provides with an analysis of the future growth designs based on the data and observations in the past years.

10 Materials And Method (Determining and Creating Variables) Based on these identifications, urban growth maps and the variables leading the urban growth were also identified Urban growth variables Variables Contents Variable structure Dependent variable Y 0= No Urban Growth, 1= Urban Growth Binary category X 1 Agricultural Land Use 1=Agricultural Land, 0= Not Agricultural Land Binary category X 2 Waste/Arid Land 1= Waste/Arid Land, 0= Not Waste/Arid Land Binary category X 3 Distance to Important Centers Continuous X 4 Distance to City Center (M) Continuous Existence of Forest Lands Independent X 5 Binary category 1= Forest Land, 0= Non Forest Land variables X 6 1=High Intensive Urban Area, 0= Not High Intensive Urban Area Binary category X 7 1=Low Intensive Urban Area, 0= Not Low Intensive Urban Area Binary category X 8 Distance to Nearest Urban Cluster (M) Continuous X 9 Other Land Cover/Land Use Binary category X 10 Distance to Roads (M) Continuous X 11 Distance to Centers of Urban Economy Continuous

11 Materials And Method (Creating the Model) Two models were created in the study. Model (control model) 2015 Model (estimation model) 2025

12 Results And Discussion Change LULC The city grows all three times. At the second time, there was a growth according to the road network, but at the end of the day the city started to grow in every direction.

13 Results And Discussion Urban Growth According to their areal distribution, the urban sprawl is seen to develop from the core of the city (continuous urban areas) to outwards in all directions. It is seen that the sprawl was through the road directions and it increased to the east, west and southwest in The gained, continuous and lost urban areas according to successive time periods

14 Results And Discussion The Growth Pattern Of Denizli In the both periods, the greatest loss in agricultural lands is seen to be around motorway routes and industrial areas. With the effect of the factors mentioned, first circular, then linear and leapfrog sprawl are seen from the core of the city towards the periphery. The reason why the leapfrog sprawl became more active in 2001 was the intensive administrative status change in Denizli as well as the self-authority of planning by the municipalities. The growth pattern of Denizli

15 Results And Discussion (Control model) Urban Growth= -0, ,318912*Agriculture + 0,331123* Barren And Sparsely Vegetation+ 0,020835*Centerofattractiontodistance-0,092369*Center Of Urban To Distance +0,315676*Forestry+ 0,081198*High Density Settlement + 0,109580*Low Density Settlement -0,000427*Nearest Urban Cluster To Distance+ 0,210126* Other LULC -0,112782* Road Todistance * Center Of Urban Economy To Distance Variables (The year 1987) Coefficient t_test ( ) Symbol Intercept X 1 Agriculture X 2 Barren And Sparsely Vegetation X 3 Center Of Attraction To Distance X 4 Center Of Urban To Distance X 5 Forestry X 6 High Density Settlement X 7 Low Density Settlement X 8 Nearest Urban Cluster To Distance X 9 Other LULC X 10 Road To Distance X 11 Center Of Urban Economy To Distance

16 Results And Discussion (Estimation model) Urban growth = *Agriculture * Barren And Sparsely Vegetation *Center Of Attraction To Distance *Center Of Urban To Distance * Forestry *High Density Settlement *Low Density Settlement * Nearest Urban Cluster To Distance * Other LULC * Road To Distance * Center Of Urban Economy To Distance

17 Results And Discussion Evaluation of The Variables Effective on Urban Growth via LRM In the control model, the general overlap of true urban growth with 2015 was determined as 86%. high probability areas (47%), moderate probability areas (25%) low probability areas (14%). The model did not generate any data related to the existent area of 5.84 km 2 (14%). When analyzed the part 14%, it was observed that these areas have been developed in a leapfrog growth. Prediction of urban growth for 2015 High overall consistency in the overlap shows that LRM generates satisfactory results in the urban growth modeling.

18 Results And Discussion Evaluation of The Variables Effective On Urban Growth via LRM According to the estimation model for 2025 (1. scenario), the city of Denizli is continuing the leapfrog and linear growth. The construction from the city center to the periphery is proceeding in all directions adjacent to the existent area; but the linear growth is in the northeast direction and sets a border between the agricultural lands. While there occurs leapfrog sprawl in the north direction and it results in a fragmentation and perforation in agricultural lands, this also leads to a pressure on archaeological settlements and archaeological protected areas. In the second scenario the interaction between the urban growth and the protected area is shown because there would be no construction on the areas of protected status. Prediction of 2025 urban growth

19 Results And Discussion Evaluation of The Variables Effective On Urban Growth via LRM The urban growth model of 2025 was produced for Denizli. It was seen that the variables causing urban growth and sprawl in Denizli affected the agricultural lands in a negative way. The settlements, trading and industrial areas located around the motorways as a consequence of those motorways built through plain valleys and arable lands brought about the loss of agricultural lands. Increasing transportation opportunities promoted construction and caused urban sprawl in the vicinity of motorways to Ankara, Izmir and Antalya, as 3 main routes. Prediction of 2025 urban growth

20 Conclusion and Outlook It is possible to make ecological decisions in urban planning and management by using RS, GIS and LRM techniques providing urban growth model. It is also important for healthy urban life to extend such research studies in Turkey, where urban policies are insufficient. Urban expansion continues to evolve over urban areas such as the cancer cell, which benefits from this weakness. RS, GIS and various statistical models are of course very important to show this situation. However, the lack of a planning / evaluation system to evaluate these estimates demonstrates that Urban sprawl will continue to adversely affect agricultural areas and urban ecosystems. The variables used in this study vary according to the regional urban planning policies and the phenomenon of urban growth in the related region. It is seen, according to RS, GIS and LRM results, that many factors affect the urban development.

21 Conclusion and Outlook In this regard, when analyzed the city models, it is thought that the model of compact city is a sustainable model for Denizli. The primary aim should be taking the control of construction and the city should be accordingly established upon a new model. When modeling results are evaluated together with urban politics, it is more appropriate to think that "urban sprawl follows urban politics" rather than "urban sprawl follows roads". Because the main factor causing urban expansion in Denizli is the inadequacy and confusion of national spatial and social planning policies. Along with the effects of the variables such as population growth, urban policies, central and local governments, subscales and upper scale plans, the works for preventing the loss of agricultural lands and the disordered settlement in the city center and its surrounding.

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