Green Tartu
Spatial Planning Project
The city of Tartu (Tartu linn) is divided into 18 districts with the river Emajõgi running along the most important district of the city – Kesklinn (The City Centre) which dates back to the Swedish occupation of Estonia during the late 15th century. Located to the south of Kesklinn is Karlova which dates back to the post war Estonia and still embodies the aura of its time. Annelinn which is another important district especially in terms of mass housing, was designed and constructed as a mikrorayon during the post war Soviet occupation of Estonia roughly following Le Corbusier’s modern city planning principles. Before and after Estonia’s independence from the Soviet, the city of Tartu has exhibited a centrifugal growth like most cities during which all its peripheral districts like Maarjamõisa emerged. As a result of the diverse historical occupation of Estonia, the many districts of Tartu exhibit a varied land use pattern and therefore the distribution of green spaces in all the districts is not homogenous both in terms of quality and quantity.
Green Tartu
Spatial Planning Project
The city of Tartu (Tartu linn) is divided into 18 districts with the river Emajõgi running along the most important district of the city – Kesklinn (The City Centre) which dates back to the Swedish occupation of Estonia during the late 15th century. Located to the south of Kesklinn is Karlova which dates back to the post war Estonia and still embodies the aura of its time. Annelinn which is another important district especially in terms of mass housing, was designed and constructed as a mikrorayon during the post war Soviet occupation of Estonia roughly following Le Corbusier’s modern city planning principles. Before and after Estonia’s independence from the Soviet, the city of Tartu has exhibited a centrifugal growth like most cities during which all its peripheral districts like Maarjamõisa emerged. As a result of the diverse historical occupation of Estonia, the many districts of Tartu exhibit a varied land use pattern and therefore the distribution of green spaces in all the districts is not homogenous both in terms of quality and quantity.
Spatio-Temporal Relation between
Human Conflicts
and
Refugee Migrations
Conflicts in the human society has been an intrinsic characteristic throughout its history. One of the most significant reason behind it is territoriality. “Territoriality is a means of affecting (enhancing or impeding) interaction and extends the particulars of action by contact. Territoriality is defined here as the attempt to affect, influence, or control actions, interactions, or access by asserting and attempting to enforce control over a specific geographic area” (Sack, 1983). This sense of ownership over a geographical or physical space often leads to divisions within the society and eventually leads to conflicts which might prove to be of a fatal nature, there by threatening the very existence of the communities residing in that space. As a result of this violent nature of conflicts, the most immediate consequence is the dislocation and migration of the inhabitant community in the search of safer abode. This is how both, conflicts and migrations as a spatial phenomena have been interdependent and have been a part of the human society since per-historic times.
Problem Statement and
Analytical Framework
This study on focuses on understanding relation between the human conflicts and refugee migrations. The relation between conflicts and forced migrations seem quite simple at the first glance. However, when observed closely, the relation tends to change when the data set is changed for different regions and different time periods.
According to the first law of geography, developed by Waldo Tobler, “everything is usually related to everything else but those which are near to each other are more related when compared to those that are further away.“ This means all the spatial phenomena which are closer in term of spatial proximity, are related to each other more strongly as compared to the phenomena which are at a farther distance. The same principle is also applicable for the temporal dimension, meaning to say that “everything is related to everything else but near and recent things are more related than distant things both in space and time”. Therefore, applying this principle to understand the relation between conflicts and forced migrations, an analytical framework was generated based on the following illustration.
Method of Analysis
Events of conflicts may or may not be violent in nature. Events of violent conflicts usually have casualties or fatalities associated with them. In order to identify the conflict prone zones and the regions witnessing casualties due to the events of conflicts, the following visualizations have been generated for the period 2001-2015:
- Optimized Hot-Spot Analysis: This visualization represents the conflict prone zones based upon the three different time frames chosen(1990-2000, 2001-2015, 2016-2018). This visualization classifies the locations of the conflict into three different categories, the first category having a 90-99% confidence in the location being a conflict prone region during the given time frame and thus classifies it as the ‘Hot-Spots’, second category is the events that are ‘not significant’ in terms of the conflicts and third category having a 90 99% confidence that the locations having an event of conflict are not conflict prone and thus classifies them as the ‘Cold Spots’. A detailed description of how this tool produces the results has been explained in the next part of this chapter.
Figure (adjacent) represents the events of conflicts in sub-Saharan Africa, Syria , Iraq, Turkey, Israel and Afghanistan.
- Casualties : This visualization through a visual hierarchy in the symbology, represents variation in the number of casualties during the events of conflicts. Events of violent conflicts often results in mass displacement of the inhabitants from the region. In order to understand its relations, the following questions must be addressed:
- Do more refugee migrants originate from the regions which are prone to conflicts?
- Do more refugee migrants originate from the regions witnessing more causalities resulting from violent nature of the conflicts?
- Is it necessary that the conflict prone zones are also the ones witnessing more causalities resulting from the violent nature of conflicts?
And in order to answer the above questions, the following visualizations have been generated.
Figure (adjacent) represents the conflict prone zone during 2016-2018. Its evident that Syria is in a constant state of civil war which started in 2011.
- Conflict Hot-Spots and Migration origins:
This visualization shows the relation between the conflict Hot-Spots and population of migrants from origin countries by overlapping the Hot-Spots on the origin countries of the migrants, which are shown using a color gradient. It helps us to understand if more refugee migrants originate from regions which are more prone to conflict.
Figure (adjacent) represents the hot-spots and the events of conflicts. From this visualization, its clearly observed that as we reduce the scale of analysis, both spatial and temporal, the relation between violent conflicts and the conflict hot-spots is very strong.
- Casualties and Migration origins: This visualization shows the relation between the conflict casualties and population of migrants from origin countries by overlapping the casualties on the origin countries of the migrants. It helps us to understand if more refugee migrants originate from regions which witnessed more casualties resulting from the events of conflicts.
Figure (adjacent) represents the casualties and the refugee migrations. It can be observed that the maximum migrants are originating from Syria and Afghanistan and parts of Africa as well. It was during the 2015 that the EU received the maximum and drastically high number of asylum applications. One of the major reason behind it was the Syrian Civil War which reached its peak in between 2015-2018 which is evident from the next visualization.
- Conflict Hot-Spot and Casualties: This visualization shows the relation between the hot-spots of the events of conflict and the casualties resulting from the events of conflicts. In order to get a scientific evidence of whether or not the above relations are strong enough, a correlation analysis has been performed for the above three visualizations.
Figure (adjacent) It shows the conflict hot-spots during the 2015-2018.
Conclusion
A comprehensive understanding of how the final results depend upon the accuracy, nature of the spatial phenomena being mapped, and the tools and methods opted for analysis, was gained. It was also observed that the hypothesis adopted in the beginning of the analysis might not be completely true, which however can be an important finding at the end of the analysis. This project helped to identify various issues that could arise during the course of analysis and therefore a better research and analytical strategy could be devised to handle any other spatial analysis to be faced in the future.