Modelling farmland abandonment: A study combining GIS and data mining techniques

Zaragozí, Benito; Rabasa, A.; Rodríguez-Sala, Jesús Javier; Navarro, J.T.; Belda, Antonio; Ramón, A.

doi:10.1016/j.agee.2012.03.019

Cited by 51 publications

(27 citation statements)

References 32 publications

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“…As a result of this changing dynamic, there is an expansion of natural ecological land (Pueyo and Beguería, 2007;Seeborg et al, 2000;Mullan et al, 2011;, also known as "transformation from farmland to forest" (Sluiter and de Jong, 2007;Milenov et al, 2014). This problem will continue to worsen with the further migration of rural labor and the aging of those staying in their villages (Zaragozí et al, 2012;Shao et al, 2014;Li et al, 2014). However, with goals of maintaining at least 1.8 billion mu of arable land and ensuring food safety, an important question is posed: how can the waste of farmland resources be reduced, especially those providing good farming conditions?…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of farmland transfer in alleviating farmland abandonment in mountain regions

Shao

Zhang

2015

J. Geogr. Sci.

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Abstract:Farmland abandonment is a type of land use change in the mountain region, and this change is under rapid development. Whether farmland transfer can prevent this process and promote the effective allocation of land resources or not is a question worth studying and discussion. With the help of the previous research findings, the objective of this paper was to find out the role of farmland transfer on preventing farmland abandonment, by using the methods of multiple view with two factors, and single factor correlation analysis. The results showed that: (1) At village level, a significant negative correlation between farmland transfer and farmland abandonment existed in the study site, with R 2 = 0.7584. This correlation of farmland with high grade farming conditions presented more outstandingly. The fitted curve for the farmland at Level I had the largest R 2 at 0.288, while that for the farmland at Level IV had the smallest R 2 at 0.103. Which indicated that farmland transfer could prevent the abandonment of farmland with high grade farming conditions? (2) At plot level, the abandonment rate of farmland with high grade farming conditions was significantly lower than that of farmland with poor grade farming conditions. It was the lowest at 10.49% for the farmland with Level I farming conditions, whereas the farmland with Level I farming conditions was 26.21%. Abandoned farmland was mainly contributed by farmland with Level IV farming conditions in the study site. (3) At village level, the role of farming conditions on farmland abandonment was insignificant. The univariate correlation analysis revealed that the abandonment ratio was negatively correlated with the proportions of farmland at Levels I and II and their accumulated proportion; however, their R 2 were small at 0.194, 0.258, and 0.275, respectively. The abandonment of farmland with high farming conditions still existed. The abandonment ratios of farmland at Levels I and II were high at 9.96% and 10.60%, respectively. This presented that farmland transfer on behalf of the land rental market was still not developed. (4) However, the village possessed the high rate of farmland transfer, and its rate of farmland abandonment with high grade farming conditions was all lower. When the transfer ratios of farmland were over 20%, the abandonment ratios of farmland at Levels I and II were 6.47% and 6.92%, respectively. Farmland abandonment was still controlled by the improvement of land rental market. And the functions of land rental market optimizing the utilization 204 Journal of Geographical Sciences of farmland resources have been presented to a certain degree. (5) To further improve the marketing degree of land rental, the probability of farmland abandonment could be reduced. Especially, their function to farmland with high grade farming conditions was very obvious, and could avoid the waste of farmland resources with high grade farming conditions.

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Section: Introductionmentioning

confidence: 99%

Effectiveness of farmland transfer in alleviating farmland abandonment in mountain regions

Shao

Zhang

2015

J. Geogr. Sci.

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“…In addition, a wealth of digital information such as images (e.g., satellite, panoramic, and others) can be collected and stored in such a database. Recent technology developments can also help to process and analyze large and complex datasets using data mining based on such databases [37]. For instance, Zaragozi (2012) [37] stated that there can be "too many variables" contributing to abandonment and data mining can be used to help select the most important variables.…”

Section: Alternative Methodologies and Datamentioning

confidence: 99%

“…There is no universal definition of land abandonment or housing abandonment, and vacancy-related data often exist in different formats with different spatial extents and are compiled by various agencies or organizations for different purposes and years [6,11,37]. Few cities have an inventory of vacant and abandoned houses at the property level across the years that is systematically organized [9].…”

Section: Alternative Methodologies and Datamentioning

confidence: 99%

Housing Abandonment and Demolition: Exploring the Use of Micro-Level and Multi-Year Models

Yin

Silverman

2015

IJGI

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Policies focusing on enforcing property code violations and the improvement of vacant properties are argued to be more efficacious than demolition policies to fight urban blight. This study applies parcel level data to a multi-year hybrid modeling structure. A fine-grained analysis is conducted on the dynamic patterns of abandonment and demolition for a unique period of four years before and after the City of Buffalo's stepped-up demolition efforts. Results showed that proximity to vacant and abandoned properties, sustained over the years, had the greatest impact on the possibility of a property being abandoned. The second greatest positive impact on property abandonment was small lot front size. Results also showed that neighborhood vacancy density had the greatest negative impact on surrounding housing sales prices over the years. There was no significant impact of demolition on housing sales prices. These findings suggested that the City should aim to have more incentive programs that are tailored to control the number of vacant properties, rather than focusing primarily on demolition-oriented programs.

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“…Following the claims of existing studies [10,21,31], we set the explanatory variables (see Table 1) from the following four aspects of the social and environmental dimensions: natural environment features, socioeconomic conditions, farming system facilities and locations.…”

Section: Explanatory Variablesmentioning

confidence: 99%

“…It has brought about many positive effects, such as forest re-growth [3], recovery of ecosystem services [4], and enhancement of carbon sink capacity and biodiversity [3,[5][6][7]. However, many negative effects have also been found, including the disappearance of traditional farming practices; loss of habitats with high ecological, cultural, and aesthetic value; increased risk of wildfires; and species invasion [8][9][10][11][12][13]. What is worthy of more attention is the consequent challenges for food security, especially in areas where arable land is highly scarce, such as China and Japan [12,14].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Factors Driving Seasonal Farmland Abandonment: A Case Study at the Regional Level in Hunan Province, Central China

Liu

Zhang

et al. 2017

Sustainability

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Farmland abandonment, including perennial and seasonal abandonment, is an important process of land use change that matters most to food security. Although there is a great deal of studies on farmland abandonment, seasonal abandonment, which is as serious as perennial abandonment, has attracted little academic attention. This paper takes Hunan Province in central China as its study area and uses a spatial regression model to examine the driving factors of seasonal farmland abandonment at the county level. Our results show that farmland abandonment has striking spatial relativity, and there are two clustering zones with a high index of farmland abandonment (IFA) in the Dongting plain and the basin in south-central Hunan, while a clustering zone of low IFA can be found in the mountains of southwest Hunan. Farmland abandonment at the regional level is negatively affected by the land productive potentialities, proportion of mechanized planting, ratio of effective irrigation, and distance to provincial capital, while it is positively associated with the variables mountainous terrain, per capita farmland area, and labor shortage. Additionally, farmland abandonment is also affected by adjacent areas through its spatial dependence. In short, seasonal farmland abandonment is also driven integratedly by the socioeconomic and environmental dimensions and spatial interaction of farm abandonment.

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Modelling farmland abandonment: A study combining GIS and data mining techniques

Cited by 51 publications

References 32 publications

Effectiveness of farmland transfer in alleviating farmland abandonment in mountain regions

Effectiveness of farmland transfer in alleviating farmland abandonment in mountain regions

Housing Abandonment and Demolition: Exploring the Use of Micro-Level and Multi-Year Models

Exploring the Factors Driving Seasonal Farmland Abandonment: A Case Study at the Regional Level in Hunan Province, Central China

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