Land-cover and land-use change are highly dynamic and contribute to changes in the water balance. The most common changes are urbanisation, deforestation and desertification. This dissertation deals with the topic of projecting land cover (LC) into the near future with the help of the scenario technique. The aim of the thesis is the projection of the urban and rural land-cover change (LCC) till 2025. Two research questions are addressed in this work: (1) Which integrated concept can be developed to combine different methods to project urban and rural LCC into the future based on past LCC? (2) Is it possible to implement the developed concept and does the implementation deliver plausible results?
To answer the research questions, a 4-step concept is adopted which serves as workflow for projecting the LCC: (i) the definition of the scenario context, and with that the definition of the study area, (ii) the identification of spatial and dynamic drivers for LCC, consisting of spatial drivers that are location-dependent, such as slope or soil type, and dynamic drivers of LCC, such as demographic and economic development, (iii) scenario formulation and projection of identified drivers, and (iv) scenario-based projections of future LCC, which means its quantitative and spatial modification (demand and allocation).
For implementation and testing, the Upper Western Bug River catchment in Ukraine serves as the study site. The extent of the study area reaches from the source of the Western Bug to the Dobrotvir gauging station and is thus entirely located in Ukraine. This presents the first step of the developed concept of the projection of LCC. The existing geo-database for implementation is scarce. LC data is available for the territory of the EU (e.g. CORINE Land Cover) but not for Ukraine.
Therefore, the implementation of the second step had to focus on the derivation of LC data for three-time steps to get the basis for the LCC. A classification of satellite scenes of Landsat and SPOT are done for the time steps 1989, 2000, and 2010. The two decades show a huge development of LCC. The increase of ‘artificial surface’ and unmanaged ‘grassland’ is visible with the decrease of ‘arable land’ and ‘forests’.
An extended statistical analysis considering the systematic LCC reveals stable transition pathways, which in turn are the basis of the projection of future land cover. This refers to the second step of the concept: change detection.
One transition pathway is that ‘arable land’ is not used and converted in settlement areas, but rather changes into ‘grassland’. With the derived LC and the analysed LCC as a basis of the work, the search for spatial and dynamic drivers start at the third time step. A list of dynamic drivers is first compiled, via literature research, and then tested for effect on LCC with statistical analyses.
The dynamic driving forces are the ‘Gross Domestic Product’ (GDP) and ‘population development’. Spatial driving forces are laws/planning practices, fertility, slope, distance to the city Lviv, settlements, roads, or rivers. As a result, population development has an effect on the change in the LC class to 'artificial surface' from 'grassland' and 'arable land' from ‘grassland'.
The implementation of the third step is done with the help of four storylines where the overall development of the dynamic drivers are included towards 2025. With that it is possible to project them into the future.
The fourth step includes the calculation of the demand for each LC class with the projected dynamic drivers. The areas that have a high probability to change into another LC class are determined in suitability maps (allocation) which are derived by translating the transition pathways into GIS algorithms including the spatial driving forces. The class of 'artificial surface' changes the most under scenario A until 2025 and less under scenario D — the sustainable scenario. The LC class 'arable land' decreases in scenario A and B, but has the strongest development in scenario D. The LC class of unmanaged ‘grassland’ is quite stable under scenario A and B, but decreases in C and D.
The results of systematic changes in ‘arable land’ that changes into ‘grassland’ are different compared to developments in other countries like Germany. The protection and conservation of arable land is not seen as strongly in other Eastern European countries as it is in the Upper Western Bug River catchment. In turn, the identified spatial and dynamic drivers fit other studies in Eastern Europe.
The applied concept of projecting LCC with these steps are highly flexible for implementation in other study sites. However, the volume of work can differ within the steps because of the available databases. In Ukraine the available LCC data was not detailed enough to carry out a future projection. So, a main part of the work is dedicated to the derivation of past LC for different time steps. The involvement of regional experts helped to gain detailed knowledge of processes of LCC. The advantage of the presented concept with the mixture of quantitative (e.g. satellite analyses, statistical analyses) and qualitative methods can overcome methodological knowledge gaps. In addition, the retrospective analyses, as starting points, for the projection of future LCC carves out the site-specific allocation of change.:Acknowledgements..............................................................................................................................III
Abstract..................................................................................................................................................IV
Zusammenfassung..............................................................................................................................VII
Contents..................................................................................................................................................X
Abbreviations......................................................................................................................................XIV
1.Introduction.................................................................................................................................1
1.1Background................................................................................................................................1
1.2Objectives and Research Questions.......................................................................................3
1.3Structure....................................................................................................................................3
2.Basics of the Work......................................................................................................................5
2.1Land Cover, Land Use and Land-cover Change....................................................................5
2.2Projection of Land-Cover Change...........................................................................................6
2.3Drivers of Land-Cover and Land-Use Change.....................................................................10
2.4Basics of Scenario Methods..................................................................................................12
3.Conceptual Framework............................................................................................................15
3.1Step1: Definition of the Scenario Context...........................................................................17
3.2Step 2: Identification of Spatial and Dynamic Drivers of Land-Cover Change...............18
3.3Step 3: Scenario Formulation and Projection of Identified Drivers.................................18
3.4Step 4: Scenario-based Projections of Future Land-Cover Change.................................19
4.Implementation and Testing of the Framework..................................................................20
4.1Step 1: Definition of the Scenario Context..........................................................................20
4.2Step 2: Identification of Spatial and Dynamic Drivers for Land-Cover Change..............24
4.3Step 3: Scenario Formulation and Projection of Drivers...................................................28
4.4Step 4: Scenario-based Projections of future Land-Cover Change..................................32
5.Discussion..................................................................................................................................36
5.1Discussion of the Methods....................................................................................................36
5.2Discussion of the Empirical Results.....................................................................................42
6.Conclusions and Outlook........................................................................................................47
7.Reference List............................................................................................................................49
8.Appendix....................................................................................................................................58
8.1Position and Affiliation of the Interviewed Experts...........................................................59
8.2Suitability Maps.......................................................................................................................60
8.3Research Articles.....................................................................................................................66
8.3.1Research Article 1: Retrospective Analysis of Systematic Land-Cover Change in the.........
Upper Western Bug River catchment, Ukraine.....................................................................67
8.3.2Research article 2: Cross-Sectoral Projections of Future Land-Cover Change for the........
Upper Western Bug River catchment, Ukraine.....................................................................80
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:78542 |
| Date | 21 March 2022 |
| Creators | Burmeister, Cornelia |
| Contributors | Schanze, Jochen, Weitkamp, Alexandra, Haase, Dagmar, Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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