Land Use Occurrence Research Articles

Understanding farmers' influence on land-use change using a participatory Bayesian network approach in a pre-Alpine region in Switzerland

Land-use models can be used to assess the importance of different drivers of land-use change. Local actors make land-use decisions on the basis of both biophysical and policy aspects, but they can also be considered as autonomous drivers as their attitudes and beliefs influence land-use substantially. We use a Bayesian network-based Land-use Modeling Approach (BLUMAP) to analyze influences of local actor characteristics on land-use change in a spatially explicit manner. Our analysis shows that local actor characteristics have a greater influence on land-use change than changes in agricultural policy schemes. Furthermore, focusing on the probabilities of land-use occurrence under different scenarios facilitates the quantification of influences of local actor characteristics on land-use changes and aids in the detection of where land-use changes are more likely to occur. We demonstrate that local actor characteristics could override land-use policy trends; thus, greater consideration should be paid to actors in land-use development processes.

Considerations about the land use and conversion trends in the savanna environments of Central Brazil under a geomorphological perspective

Assuming that the landscape physiographic characteristics strongly determine the occurrence of land use and land cover types, this study assessed the distribution patterns of natural and converted classes in relation to the major geomorphological units and slope ranges in the central area of continuous savanna formations in Brazil (Cerrado biome), the country’s most important region for cattle ranching and intensive commodity crops. Our results showed that 93% of the agriculture activities are concentrated at slopes of less than 5°, mostly associated to old regional planation surfaces (RPSs). Considering the amount of remnant vegetation and the occupation and land use deterministic trends, we estimated that between 58,041 km2 and 79,677 km2 of conversions may occur in the near future. If the priority areas for biodiversity conservation are properly enforced and effectively incorporated into the system of fully protected areas and areas of sustainable use, a decrease of approximately 24% in the expected potential deforestation could be achieved.

Explanation of land use in mountainous area, China: from field to village level

Few studies of land use change were particularly considered the hierarchical data structure originating from different scales and levels. Using interviewing data collected from 107 villages, 1,050 households and 4,780 fields between November 2003 and August 2005, the objective of this paper is to predict the occurrence of land use from field to village level in mountainous area, China, and to improve our understanding of the causes of land use. Household’s behavior in the choice of land use type is guided by multiple, often confiding, household objectives, subject to the available resources, possible productive activities, and external economic and biophysical constraints. For rice model, the household level variables cannot be substituted by village level aggregates. Aggregated variables at village level do not capture any of the variability at the household level. Village level variables can virtually be explained in virtue of the variables of field and household level. The households and the villages show significant clustering of the occurrence of rice, and they explain the 11.3 and 4.5% variance, respectively. For corn model, corn as dependent variable does not show any significant variance component. The variables of household and village level have lower effects on the occurrence of corn. There is a significant relation between slope of a field and the choice to cultivate corn and a significant random effect at the village level. However, cropland size, input–output, transportation cost, even family income in household level and road density and food market development in village level, at some extent, are controlled by slope. These variables do not influence corn cultivation significantly and that those are predominantly determined by slope. In a word, the household level can be crucial in explaining land use at the field level. Multilevel analysis can be applied to statistically model the occurrence of land use, and to explore a number of cross-scale propositions.

Multilevel modelling of land use from field to village level in the Philippines

In land use research regression techniques are a widely used approach to explore datasets and to test hypotheses between land use variables and socio-economic, institutional and environmental variables. Within land use science researchers have argued the importance of scale and levels. Nevertheless, the incorporation of multiple scales and levels and their interactions in one analysis is often lacking. Ignoring the hierarchical data structure originating from scale effects and levels, may lead to erroneous conclusions due to invalid specification of the regression model. The objective of this paper is to apply a multilevel analysis to construct a predictive statistical model for the occurrence of land use. Multilevel modelling is a statistically sound methodology for the analysis of hierarchically structured data with regression models that explicitly takes variability at different levels into account. For a land use study in the Philippines multilevel models are presented for two land use types that incorporate the field, household and village level. The value of multilevel modelling for land use studies and the implications of multilevel modelling for data collection will be discussed. The results show that explanatory variables can account for group level variability, but in most cases a multilevel approach is necessary to construct a sound regression model. Although land use studies often show clear hierarchical structures, it is not always possible to use a multilevel approach due to the structure of most land use datasets and due to data quality. Potentially, multilevel models can address many important land use issues involving scales and levels. Therefore, it is important in land use change research to formulate hypotheses that explicitly take scale and levels into account and then collect the appropriate data to answer these questions with approaches such as multilevel analysis.