Understanding farmland abandonment in the Polish Carpathians

For more than 100 years, forest cover in Europe has increased substantially due to afforestation and natural forest expansion. The latter, resulting typically from farmland abandonment and subsequent secondary forest succession, has played a major role in marginal mountain areas and possesses various highly important environmental and economic consequences. In the Polish Carpathians, farmland abandonment is a spatially dispersed, locally specific process because of small farm and land parcel sizes, and its extent in the entire region is not well known. This study aims therefore to map current farmland abandonment in the Polish Carpathians and to identify its spatial determinants. To map farmland abandonment we detected secondary forest succession on abandoned fields using Airborne Laser Scanning (ALS) point clouds and topographic data in 230 sample areas (tiles) distributed throughout the Carpathian communes. To reveal the spatial determinants of current farmland abandonment, we investigated variables describing the accessibility and environmental, land cover, and socioeconomic conditions of communes, using best subset regression modelling. The results showed that 13.9% of agricultural land was abandoned and underwent secondary forest succession in recent decades. Topography (mainly slope gradients) and employment outside of agriculture were the two most important spatial determinants of farmland abandonment. Consequently, a substantial forest expansion may be observed in the coming decades throughout the Polish Carpathians if no counteractions are taken.     

Land use/cover change in central Tibet, c. 1830–1990: devising a GIS methodology to study a historical Tibetan land decree

In this study, historical Tibetan tax-related data pertaining to cultivated land in central Tibet are studied by means of GIS and compared with contemporary patterns. A Tibetan land decree from 1830 contains aggregated data on the amount of land-based tax units for estates in 57 districts of central Tibet. The purpose of this study is to devise a GIS methodology to study the potential utility of these data for historical geographical research, and to determine the approximate changes in cultivated land areas between 1830 and 1990. Traditional Tibetan tax data are significant for current efforts to construct historical land cover databases of the Tibetan Plateau region for the study of the human dimensions of global change.     

Rural sustainability under threat in Zimbabwe – Simulation of future land use/cover changes in the Bindura district based on the Markov-cellular automata model

Spatially explicit land use/cover models are indispensable for sustainable rural land use planning, particularly in southern African countries that are experiencing rapid land use/cover changes. Using Zimbabwe as an example, we simulated future land use/cover changes up to 2030 based on a Markov-cellular automata model that integrates Markovian transition probabilities computed from satellite-derived land use/cover maps and a cellular automata spatial filter. A multicriteria evaluation (MCE) procedure was used to generate transition potential maps from biophysical and socioeconomic data. Dynamic adjustments of transition probabilities and transition potential map thresholds were implemented in the Markov-cellular automata model through a multi-objective land allocation (MOLA) procedure. Using the normalised transition probabilities, the Markov-cellular automata model simulated future land use/cover changes (up to 2030) under the 2000 calibration scenario, predicting a continuing downward trend in woodland areas and an upward trend in bareland areas. Future land use/cover simulations indicated that if the current land use/cover trends continue in the study area without holistic sustainable development measures, severe land degradation will ensue.