Going beyond landscape change description: Quantifying the importance of driving forces of landscape change in a Central Europe case study

Hersperger, Anna M.; Bürgi, Matthias

doi:10.1016/j.landusepol.2008.08.015

Cited by 174 publications

(102 citation statements)

References 32 publications

(37 reference statements)

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“…This roughly corresponds to the classification of indirect drivers given by Hersperger 5 and Bürgi (2009), with "natural and spatial driving forces" corresponding to our group (1), and all other categories (political, economic, cultural and technological) to our group (2). Our third group consists of a direct land use activity (grazing) which is not considered by Hersperger and Bürgi (2009), as well as activities / regulations with direct local land use impacts (the presence of tourism, the delineation of nature protection areas). These drivers are directly connected to benefits 10 (ecosystem services) that society obtains from grasslands (fodder production, aesthetic beauty and biodiversity conservation).…”

Section: Predictor Variables 20mentioning

confidence: 99%

“…The concept of driving forces and its use in landscape change research can help to move emphasis from patterns to processes, extrapolate results in space and time, link data of different quality, and consider socio-cultural aspects of landscape change (Bürgi et al 2004). Hersperger and Bürgi (2009) distinguish five different groups of driving forces:…”

Section: Introductionmentioning

confidence: 99%

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Drivers of grassland loss in Hungary during the post-socialist transformation (1987–1999)

et al. 2012

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The increase in the speed of land-cover change experienced worldwide is becoming a growing concern. Major socio-economic transitions, such as the breakdown of socialism in Europe, may lead to particularly high rates of landscape transformations. In this paper we examined the loss of semi-natural grasslands in Hungary between 1987 and 1999. We studied the relationship between 9 5 potential driving forces and the fate of grasslands using logistic GLMs.Grassland loss was found to be very high (1.31 % per year), which is far higher than either before or after this period. The most influential predictors of grassland loss were environmental and landscape characteristics (soil type, area of remnant grassland patches), and the socio-economic context (distance to paved road, and nearest settlement, human population density). Several 10 processes and relationships can only be understood from a historical perspective (e.g. large extent of afforestation, strong decrease of soil water table). Grassland loss during the study period emerged as a consequence of survival strategies of individual farmers seeking adaptation to the changing environmental and socio-economic conditions, and not urbanization and agricultural intensification which are the main underlying drivers for the ongoing landscape transformations in 15 most parts of the developed world.Though globalization increasingly influences local land use decisions , reconstructing and modelling recent landscape changes cannot be done without a proper understanding of local history and culture. Our analysis shows the importance of large-area yet high resolution landscape change research, which may reveal unexpected patterns of land cover change, undetected at coarser scales. 20Keywords: East-Central Europe, land-cover change, logistic GLMs, proximate and underlying driving forces LANDSCAPE ECOLOGY, 28: (5) pp. 789-803. (2013) 3

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Section: Predictor Variables 20mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Drivers of grassland loss in Hungary during the post-socialist transformation (1987–1999)

et al. 2012

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“…Physical DFs are determined by biophysical characteristics of the environment such as topography, spatial configuration, climate, soil type, and natural disturbances [33,34]. Socioeconomic DFs can be determined by the human utilization of land resources to meet life needs [33], which could be divided into four categories: political, economic, cultural, and technological DFs [34]. Typically these DF categories are not clearly separable; for example, political and economic DFs are closely interrelated with political steering of economic mechanisms.…”

Section: Introductionmentioning

confidence: 99%

Quantifying the Driving Forces of Informal Urbanization in the Western Part of the Greater Cairo Metropolitan Region

Osman

Divigalpitiya²,

Takafumi

2016

Environments

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This paper discusses the driving forces (DFs) of informal urbanization (IU) in the greater Cairo metropolitan region (GCMR) using the Analytic Hierarchy Process (AHP). The IU patterns in the GCMR have been extremely influenced by seven DFs: geographical characteristics, availability of life facilities, economic incentives, land demand and supply, population increase, administrative function, and development plans. This research found that these forces vary significantly in how they influence urban growth in the three study sectors, namely, the middle, north, and south areas in the western part of the GCMR. The forces with the highest influence were economic incentives in the middle sector, population increase in the north sector, and the administrative function in the south sector. Due to the lower availability of buildable land in the middle sector, the land demand and supply force had a lesser influence in this sector compared to in the north and south sectors. The development plans force had medium influence in all sectors. The geographical characteristics force had little influence in both the middle and the north sectors, but higher influence than economic incentives, availability of life facilities, and development plans in the south sector. Because of the spatial variances in life facilities organizations in the GCMR, the life facilities availability force had little effect on IU in the south sector.

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“…The driving forces that are propelling change are often categorised as political, economic, cultural, technological and environmental forces (Hersperger and Bürgi 2009;Kristensenet al 2009). The scale at which they operate also defines the stakeholders that are relevant.…”

Section: 2 Drivers and Processes Of Landscape Changementioning

confidence: 99%

“…Time series for at least two periods were used. The first period for comparison lies between 1972 (establishment of the EEC) and 1992, since EU legislation may be considered one of the key policy drivers of landscape processes in Europe in recent decades (Bürgi et al 2004;Hersperger and Bürgi 2009;Van Vliet et al 2015), a key theme in the analysis of this paper. The latter was chosen because from 1992 onwards the MacSharry reform of the European Common Agricultural Policy (CAP) introduced accompanying measures, as the first step towards de-coupling of farmers' agricultural support from production (Primdahl 2014).…”

Section: Data Acquisition and Processingmentioning

confidence: 99%

Europe: the paradox of landscape change : A case-study based contribution to the understanding of landscape transitions

Sluis

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Going beyond landscape change description: Quantifying the importance of driving forces of landscape change in a Central Europe case study

Cited by 174 publications

References 32 publications

Drivers of grassland loss in Hungary during the post-socialist transformation (1987–1999)

Drivers of grassland loss in Hungary during the post-socialist transformation (1987–1999)

Quantifying the Driving Forces of Informal Urbanization in the Western Part of the Greater Cairo Metropolitan Region

Europe: the paradox of landscape change : A case-study based contribution to the understanding of landscape transitions

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